tag:blogger.com,1999:blog-78541422024-02-28T00:51:18.090-08:00Saint GISKeep watching as to what this Saint GIS has to say about the Geographical Information Systems (GIS) and his favourite Spatial ETL tool FME (Feature Manipulation Engine).
He calls himself Saint GIS, know why? In his world of GIS; GIS file formats do not matter!
Anything to do with data and maps/GIS as long as it is using FMESaint GIShttp://www.blogger.com/profile/03296153994051314633noreply@blogger.comBlogger17125tag:blogger.com,1999:blog-7854142.post-71245206844235679262023-12-12T01:49:00.000-08:002023-12-12T02:34:02.262-08:00Thirty Days of Mapping (FME-ing) #30DayMapChallenge 2023<p></p><div style="text-align: justify;"><span style="font-size: medium;"><a href="https://tjukanov.org/" target="_blank">Topi Tjukanov</a> of Finland launched the #30DayMapChallenge in 2019 where hundreds of maps were made and shared on social media using the #30DayMapChallenge hashtag. Each days presents a map challenge focused on a different spatial feature or topic.</span></div><div style="text-align: justify;"><span style="font-size: medium;"><br /></span></div><div style="text-align: justify;"><span style="font-size: medium;">The topics for #30dayMapChallenge 2023 were:</span></div><div style="text-align: justify;"><span style="font-size: medium;"><br /></span></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjqW00BijRZN_f1ZRng1C6FTmHyib1X3HpCvCsTu4119GDJxzUMiufLtjYMopco1crrnuiejJ0NLvw5Cr55oP0u4fE4iRhEvsDH23WA2PE7t-pOzJyyRcXPE5MFwlME2Ss0F2vQQpRW0r7oTpck9fTekg7bwt781DaCRllNrHE8zqxNuAkVIuqjow/s960/30dmc-2023.png" style="margin-left: 1em; margin-right: 1em;"><span style="font-size: medium;"><img border="0" data-original-height="540" data-original-width="960" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjqW00BijRZN_f1ZRng1C6FTmHyib1X3HpCvCsTu4119GDJxzUMiufLtjYMopco1crrnuiejJ0NLvw5Cr55oP0u4fE4iRhEvsDH23WA2PE7t-pOzJyyRcXPE5MFwlME2Ss0F2vQQpRW0r7oTpck9fTekg7bwt781DaCRllNrHE8zqxNuAkVIuqjow/s16000/30dmc-2023.png" /></span></a></div><div style="text-align: left;"><span style="font-size: medium;"><br /><span><a name='more'></a></span></span></div><div style="text-align: justify;"><span style="font-size: medium;"><span style="text-align: left;">As a die hard user of FME from (</span><a href="https://www.safe.com" style="text-align: left;" target="_blank">Safe Software</a><span style="text-align: left;">),what could be a better opportunity to put my FME skills to test!</span></span></div><p style="text-align: left;"></p><div style="text-align: justify;"><div class="separator" style="clear: both; text-align: left;"><span style="font-size: medium;">I have been participating in #30DayMapChallenge <a href="https://twitter.com/tjukanov" target="_blank">@tjukanov </a>since 2019.</span></div><div class="separator" style="clear: both; text-align: left;"><span style="font-size: medium;">Since 2020, I have been able to post an entry on all the 30 days of #30DayMapChallenge.</span></div><div class="separator" style="clear: both; text-align: left;"><span style="font-size: medium;">And that calls for a celebration! because it is a haul! (fourth consecutive year of posting all 30 days of the challenge)</span></div><div class="separator" style="clear: both; text-align: left;"><span style="font-size: medium;"><br /></span></div><div class="separator" style="clear: both; text-align: left;"><span style="font-size: medium;">This post is a collection of all entries for #30DayMapChallenge 2023 by <a href="https://twitter.com/saint_gis" target="_blank">@Saint_GIS</a>, most of which have been accomplished only using FME and in few cases, due to the nature of the challenge, the data prepared using FME.</span></div><div class="separator" style="clear: both; text-align: left;"><span style="font-size: medium;"><br /></span></div><div class="separator" style="clear: both; text-align: left;"><div class="separator" style="clear: both; text-align: left;"><span style="font-size: medium;">Special thanks to <a href="https://www.linkedin.com/in/spatialmark" target="_blank">Mark Ireland</a>, <a href="https://twitter.com/dmitriatsafe" target="_blank">Dmitri Bagh</a> at <a href="https://www.safe.com/" target="_blank">Safe Software</a> for all the inspiration!</span></div><div class="separator" style="clear: both; text-align: left;"><span style="font-size: medium;"><br /></span></div><div class="separator" style="clear: both; text-align: left;"><span style="font-size: medium;">Happy FME-ing :-) reading my #30DayMapChallenge 2023 entries!</span></div><div class="separator" style="clear: both; text-align: left;"><span style="font-size: medium;"><br /></span></div><div class="separator" style="clear: both; text-align: left;"><span><span style="font-size: medium;"><!--more--></span></span></div><div class="separator" style="clear: both;"><div style="text-align: left;"><span style="font-size: medium;"><span><!--more--></span>First entry for the #30DayMapChallenge 2023- Some places (Points) with population more than 1.5 million generated using FME from Safe Software.</span></div><div style="text-align: left;"><span style="font-size: medium;"><br /></span></div><div style="text-align: left;"><div><span style="font-size: medium;">01-Nov-2023 Day 1: Points #30DayMapChallenge 2023</span></div><div><span style="font-size: medium;">Some places in India with more than 1.5 million population (2023)</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Visualization generated using FME from Safe Software and Google Earth for visualization.</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Thanks to Simplemaps for their free World Cities Database! </span></div></div><div style="text-align: left;"><span style="font-size: medium;">https://simplemaps.com/data/world-cities</span></div><div><div class="separator" style="clear: both; text-align: center;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiPmH-igZuKA5MuMkPDJtLk3D8VI_wiITIFP8EOGCdYAPk8ZQ4g98wpD6AScv1CeinUbCNCsOKecjf8XL0QDcJedSQ6s5QBPJctLxyYdkuohMMYUZll-lrzW6-iAIU4gTgoRL8cFei5OX01q1qlQfxhzsnuTS6UfbsIZbYSQBjCiYpfrIxJNXJcvg/s1920/Day1-Points-01Nov23-SomePlaces1.5MillionPopulation2023.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1056" data-original-width="1920" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiPmH-igZuKA5MuMkPDJtLk3D8VI_wiITIFP8EOGCdYAPk8ZQ4g98wpD6AScv1CeinUbCNCsOKecjf8XL0QDcJedSQ6s5QBPJctLxyYdkuohMMYUZll-lrzW6-iAIU4gTgoRL8cFei5OX01q1qlQfxhzsnuTS6UfbsIZbYSQBjCiYpfrIxJNXJcvg/s16000/Day1-Points-01Nov23-SomePlaces1.5MillionPopulation2023.png" /></a></div><br /><div class="separator" style="clear: both;"><br /></div><p style="text-align: left;"></p><hr /><span style="font-size: medium;"><span style="font-family: inherit;">02-Nov-2023 Day 2: Lines #30DayMapChallenge 2023</span></span></div><div><span style="font-size: medium;"><br /><span style="font-family: inherit;">Major Cities On or Near the Equator Line</span></span></div><div><span style="font-size: medium;"><br /><span style="font-family: inherit;">Visualization generated using MapnikRasterizer in FME from Safe Software</span></span></div><div><span style="font-size: medium;"><br /><span style="font-family: inherit;">Thanks to Simplemaps for their free World Cities Database! </span><br /><span style="font-family: inherit;">https://simplemaps.com/data/world-cities</span></span></div><div><span style="font-size: medium;"><br /><span style="font-family: inherit;">Made with Natural Earth Data</span><br />https://www.naturalearthdata.com</span><p></p><p style="text-align: left;"></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgTVHmbX8Y8qX-iEtuiyCbZI2O2EPsfmbEzvFKzgy59K5oasoNVYylrrKGRg4Qb614LfF7VuKT0iNPqjSOO-teOGeppb9WNhxXCEVr6QGowjlUX7vZWrcpKwOePpHb2XP21if6L-pi954ry4hPBXp7E3VRshsPozzzakd4BZ-kDaQsBnWdgYU2AnA/s1920/Day2-02Nov23-MajorCitiesNear-or-on-Equator4Post.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1056" data-original-width="1920" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgTVHmbX8Y8qX-iEtuiyCbZI2O2EPsfmbEzvFKzgy59K5oasoNVYylrrKGRg4Qb614LfF7VuKT0iNPqjSOO-teOGeppb9WNhxXCEVr6QGowjlUX7vZWrcpKwOePpHb2XP21if6L-pi954ry4hPBXp7E3VRshsPozzzakd4BZ-kDaQsBnWdgYU2AnA/s16000/Day2-02Nov23-MajorCitiesNear-or-on-Equator4Post.png" /></a></div><br /><span style="font-size: medium;"><br /></span><p></p><div class="separator" style="clear: both; text-align: center;"><br /></div><br /></div><div class="separator" style="clear: both; text-align: justify;"><span><!--more--></span></div><div class="separator" style="clear: both; text-align: justify;"><span style="font-size: medium; text-align: left;">03-Nov-2023 Day 3: Polygons </span><span style="font-size: large; text-align: left;">#30DayMapChallenge 2023</span></div><div class="separator" style="clear: both; text-align: justify;"><span style="font-size: large; text-align: left;"><br /></span></div><div class="separator" style="clear: both;"><span style="font-size: medium;">Minimum Bounding Rectangle (MBR) Polygons for World Countries by Sovereignty </span></div><div class="separator" style="clear: both;"><span style="font-size: medium;"><br /></span></div><div class="separator" style="clear: both;"><span style="font-size: large;">Data prepared using FME from Safe Software and visualization using QGIS</span></div><div class="separator" style="clear: both;"><span style="font-size: large;"><br /></span></div><div class="separator" style="clear: both;"><span style="font-size: medium;">Data Source: </span></div><div class="separator" style="clear: both;"><span style="font-size: large;">Made with Natural Earth Data</span></div><span style="font-size: large;">https://www.naturalearthdata.com</span><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg8pC2bh4Woz0AYku2YW2arNMSulMh9TYmRH202rOIM21N0hcrS3izh4IpdR9oC9o3GjbAWdb8oGWu6WGemFvZ0yln_afft8FlMOnvWnLQQLymp9Gt_uDqKgNSo52TvxUxTUGIXc0opad-pEaEXPgTfma1lAMlkf2CJ_wOlW4x57GY9kPYCkycbMA/s7015/Day3-03Nov23-Polygons-WorldCountriesBySovereigntyMBR-Polygons.png" style="margin-left: 1em; margin-right: 1em; text-align: center;"><img border="0" data-original-height="7015" data-original-width="4960" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg8pC2bh4Woz0AYku2YW2arNMSulMh9TYmRH202rOIM21N0hcrS3izh4IpdR9oC9o3GjbAWdb8oGWu6WGemFvZ0yln_afft8FlMOnvWnLQQLymp9Gt_uDqKgNSo52TvxUxTUGIXc0opad-pEaEXPgTfma1lAMlkf2CJ_wOlW4x57GY9kPYCkycbMA/s16000/Day3-03Nov23-Polygons-WorldCountriesBySovereigntyMBR-Polygons.png" /></a></div><div class="separator" style="clear: both;"><div><div class="separator" style="clear: both;"><br /></div><hr /><div class="separator" style="clear: both; text-align: justify;"><div class="separator" style="clear: both;"><span style="font-size: medium;">04-Nov-23 Day 04: A Bad Map </span><span style="font-size: large;">#30DayMapChallenge 2023</span></div><div class="separator" style="clear: both;"><span style="font-size: large;"><br /></span></div><div class="separator" style="clear: both;"><span style="font-size: medium;">Top 10 Countries by Crime Rate (2023)</span></div><div class="separator" style="clear: both;"><span style="font-size: medium;"><br /></span></div><div class="separator" style="clear: both;"><span style="font-size: large; text-align: left;">Visualization generated using MapnikRasterizer in FME from Safe Software</span></div><div class="separator" style="clear: both;"><span style="font-size: large; text-align: left;"><br /></span></div><div class="separator" style="clear: both;"><span style="font-size: medium;">Data Sources: </span></div><div class="separator" style="clear: both;"><span style="font-size: medium;">Made with Natural Earth</span></div><div class="separator" style="clear: both;"><span style="font-size: large; text-align: left;">https://www.naturalearthdata.com</span></div><div class="separator" style="clear: both;"><span style="font-size: large; text-align: left;"><br /></span></div><div class="separator" style="clear: both;"><span style="font-size: medium;">"Crime Rate by Country 2023", World Population Review</span></div><div class="separator" style="clear: both;"><span style="font-size: medium;">https://worldpopulationreview.com/country-rankings/crime-rate-by-country</span></div><div class="separator" style="clear: both;"><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhL7ENN4tJCy7rxDZc2T1RsC6C4uz-P_pwOUABjj8zO4dRMAsudQ4rchnxDk06kWvYZSXV7ZCLAi-9lPBkYOCt7wB2HTRA7oL2-QR2NkPifeWxbqc1na3HbEUEVf3NEfcyIBD-wbehQwBf1Lpl5u_glSc8KC-eEcFAS0-KuZrhDwmj9IPe_Avd3Sw/s3840/04nov23-BadMap-WorldCountriesCrimeIndex4Post.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2160" data-original-width="3840" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhL7ENN4tJCy7rxDZc2T1RsC6C4uz-P_pwOUABjj8zO4dRMAsudQ4rchnxDk06kWvYZSXV7ZCLAi-9lPBkYOCt7wB2HTRA7oL2-QR2NkPifeWxbqc1na3HbEUEVf3NEfcyIBD-wbehQwBf1Lpl5u_glSc8KC-eEcFAS0-KuZrhDwmj9IPe_Avd3Sw/s16000/04nov23-BadMap-WorldCountriesCrimeIndex4Post.png" /></a></div><br /><span style="font-size: medium;"><br /></span></div><div class="separator" style="clear: both;"><span style="font-size: medium;">Second Entry for Day 4</span></div><div class="separator" style="clear: both;"><span style="font-size: medium;"><div class="separator" style="clear: both;">04-Nov-23 Day 04: A Bad Map #30DayMapChallenge 2023</div><div class="separator" style="clear: both;"><br /></div><div class="separator" style="clear: both;">The World’s Most War-Torn Countries (2023)</div><div class="separator" style="clear: both;"><br /></div><div class="separator" style="clear: both;"><div class="separator" style="clear: both;"><span style="text-align: left;">Visualization generated using MapnikRasterizer in FME from Safe Software</span></div><div class="separator" style="clear: both;"><span style="text-align: left;"><br /></span></div><div class="separator" style="clear: both;"><span style="font-size: medium;">Data Sources: </span></div><div class="separator" style="clear: both;"><span>"World's Most War Torn Countries", World Population Review</span></div><div class="separator" style="clear: both;">https://worldpopulationreview.com/country-rankings/war-torn-countries</div><div class="separator" style="clear: both;"><span><br /></span></div><div class="separator" style="clear: both;"><span style="font-size: medium;">Made with Natural Earth</span></div><div class="separator" style="clear: both;"><span style="text-align: left;">https://www.naturalearthdata.com</span></div></div><div class="separator" style="clear: both;"><br /></div><div class="separator" style="clear: both;">"If we don't end war, war will end us" H.G. Wells</div><div class="separator" style="clear: both;">Anything war can do, peace can do better.</div><div class="separator" style="clear: both;">Let peace prevail on planet earth!</div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhWfaDMl3_YX1FAXkKov5Tcr0iab_w-byakD5UgfjjFjxNh8bdQyRIWxU_IiGnz4HloycaMmklVH2AQXN107dw0L80W5Qrc1wThG9XITvkavCo-mKD4KfQQNGeM94xvkUsjFhHKzQLXhhIhmVCuD2mAJHu1njpDz3FubeGwcM3eRySdxGLm-mC4kw/s3840/04nov23-BadMap-WarTornCountries4Post.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2160" data-original-width="3840" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhWfaDMl3_YX1FAXkKov5Tcr0iab_w-byakD5UgfjjFjxNh8bdQyRIWxU_IiGnz4HloycaMmklVH2AQXN107dw0L80W5Qrc1wThG9XITvkavCo-mKD4KfQQNGeM94xvkUsjFhHKzQLXhhIhmVCuD2mAJHu1njpDz3FubeGwcM3eRySdxGLm-mC4kw/s16000/04nov23-BadMap-WarTornCountries4Post.png" /></a></div><br /><div class="separator" style="clear: both;"><br /></div><div><br /></div></span></div><div class="separator" style="clear: both;"><br /></div></div><hr /><div style="text-align: justify;"><span style="font-size: medium;"><span>05-Nov-23 Day 05: Analog Map </span><span>#30DayMapChallenge 2023</span></span></div><div style="text-align: justify;"><span style="font-size: medium;"><br /></span></div><div style="text-align: justify;"><span style="font-size: medium;">FME Snake and Ladder Analog Map Board Game</span></div><div style="text-align: justify;"><span style="font-size: medium;">Conceived by Raghavendran S (@Saint_GIS)</span></div><div style="text-align: justify;"><span style="font-size: medium;"><br /></span></div><div style="text-align: justify;"><span style="font-size: medium;">The FME Snakes and Ladders Analog Map Board Game is a hand-crafted map based game devised using an old discarded A0 size plot of a District Map. The game track and other features are hand drawn, in some cases stickers used. Thanks to Safe Software for the stickers.</span></div><div style="text-align: justify;"><span style="font-size: medium;"><br /></span></div><div style="text-align: justify;"><span style="font-size: medium;">This analog map based board game is all about reaching the kingdom of interoperability where formats and data types do not matter! Of course one has to overcome all the obstacles mid-way. Thanks to FME from Safe Software.</span></div><div style="text-align: justify;"><span style="font-size: medium;">These obstacles can be overcome easily :-)</span></div><div style="text-align: justify;"><span style="font-size: medium;"><br /></span></div><div style="text-align: justify;"><span style="font-size: medium;">This analog map based board game is a reflection of my endless love for FME!</span></div></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjaQDP5t1wr0OvsJ2DZ1JTWgQuQ9txZyznplNEbBIo03hWR5-YWAh34Z-jrhDEf5yZcQdzNme7neGhflC9BG4IxLN0zahpS2zBZWVMYcoYNBMjEr6qFhtA1FlyHDoucC4ztmW7WBJs-Mk3vwkqI5ZaSSfCmvq4mhokpOcvqxnVlUNF-THgvCb7EEw/s6400/FME_SnakeLadderGameMap-LR.jpg" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="3592" data-original-width="6400" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjaQDP5t1wr0OvsJ2DZ1JTWgQuQ9txZyznplNEbBIo03hWR5-YWAh34Z-jrhDEf5yZcQdzNme7neGhflC9BG4IxLN0zahpS2zBZWVMYcoYNBMjEr6qFhtA1FlyHDoucC4ztmW7WBJs-Mk3vwkqI5ZaSSfCmvq4mhokpOcvqxnVlUNF-THgvCb7EEw/s16000/FME_SnakeLadderGameMap-LR.jpg" /></a></div><br /><div><br /></div><div><hr /><div><span style="font-size: medium;">06-Nov-23 Day 06: Asia #30DayMapChallenge 2023</span></div><div><span style="font-size: medium;">Physicians per 1,000 people for some Asian Countries for 2020</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Visualization generated using MapnikRasterizer in FME from Safe Software</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Data Sources: </span></div><div><span style="font-size: medium;">The World Bank</span></div><div><span style="font-size: medium;">Physicians (per 1,000 people)</span></div><div><span style="font-size: medium;">World Health Organization's Global Health Workforce Statistics, OECD, supplemented by country data.</span></div><div><span style="font-size: medium;">https://data.worldbank.org/indicator/SH.MED.PHYS.ZS</span></div><div><span style="font-size: medium;"><br /></span></div><div><div class="separator" style="clear: both; text-align: justify;"><span style="font-size: medium;">Made with Natural Earth</span></div><div class="separator" style="clear: both; text-align: justify;"><span style="text-align: left;"><span style="font-size: medium;">https://www.naturalearthdata.com</span></span><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjUZtm_9g0qVyfCelKT-g-2fjIxZs6IS8yUIPsQU_uiLRAGZUqdQyLfu75Fo-3aBbk1X7iPzFktadblHArzxNTh9TOKQPZH7OY3zlyKYzjO2dZGEXEn6nZG8gBcfq9lFD0jVK2sW0uE1lGnvS7ujkqw7zDd03QO5hqSWmfRB11uPQ-dTIeFdylM2w/s4096/Day06-06nov23-Asia-DoctorsPer1000People2020_4Post.png" style="margin-left: 1em; margin-right: 1em; text-align: center;"><img border="0" data-original-height="2160" data-original-width="4096" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjUZtm_9g0qVyfCelKT-g-2fjIxZs6IS8yUIPsQU_uiLRAGZUqdQyLfu75Fo-3aBbk1X7iPzFktadblHArzxNTh9TOKQPZH7OY3zlyKYzjO2dZGEXEn6nZG8gBcfq9lFD0jVK2sW0uE1lGnvS7ujkqw7zDd03QO5hqSWmfRB11uPQ-dTIeFdylM2w/s16000/Day06-06nov23-Asia-DoctorsPer1000People2020_4Post.png" /></a></div></div></div><div class="separator" style="clear: both; text-align: justify;"><span style="text-align: left;"><br /><span><!--more--></span></span><div style="text-align: left;"><span style="font-size: medium;">07-Nov-23 Day 7: Navigation </span><span style="font-size: large;">#30DayMapChallenge 2023</span></div><div style="text-align: left;"><span style="font-size: medium;"><br /></span></div><div style="text-align: left;"><span style="font-size: medium;">The Longest Walking Route in the World</span></div><div style="text-align: left;"><span style="font-size: medium;">Cape Town (South Africa) to Magadan (Russia)</span></div><div style="text-align: left;"><span style="font-size: medium;"><br /></span></div><div style="text-align: left;"><div><span style="font-size: large;">Visualization generated using MapnikRasterizer in FME from Safe Software</span></div><div><br /></div></div><div style="text-align: left;"><span style="font-size: medium;">Data Sources:</span></div><div style="text-align: left;"><span style="font-size: medium;">Google Maps</span></div><div style="text-align: left;"><span style="font-size: medium;"><br /></span></div><div style="text-align: left;"><span style="font-size: medium;">Made with Natural Earth</span></div><div style="text-align: left;"><span style="font-size: large;">https://www.naturalearthdata.com</span></div></div><div><div><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjwgNVSZbL6x5Wel4fWlkScOu0713IF4yRkRFMG4JH1c6CBt74KlCAx4OjAE2dCrAvQJg1p0uZHlP5r7G8TPIXxgF-GeGp7Jo4lY2UTpR_6aMWAlGvIoqCIV1MO69HGtRS7w0Lbp0kfL5wXf-ml-OJVoqvXskpBlxsAmda0t_4yWNDn0qqInOka8Q/s5760/Day07-07nov23-Navigation-LongestWalkingRoute_4Post.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="3168" data-original-width="5760" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjwgNVSZbL6x5Wel4fWlkScOu0713IF4yRkRFMG4JH1c6CBt74KlCAx4OjAE2dCrAvQJg1p0uZHlP5r7G8TPIXxgF-GeGp7Jo4lY2UTpR_6aMWAlGvIoqCIV1MO69HGtRS7w0Lbp0kfL5wXf-ml-OJVoqvXskpBlxsAmda0t_4yWNDn0qqInOka8Q/s16000/Day07-07nov23-Navigation-LongestWalkingRoute_4Post.png" /></a></div><div><br /></div><div><br /></div><br /><span><!--more--></span><div><div><span style="font-size: medium;">08-Nov-23 Day 8: Africa </span><span style="font-size: large;">#30DayMapChallenge 2023</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Life Expectancy at Birth (years) for African Countries (2021)</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: large;">Visualization generated using MapnikRasterizer in FME from Safe Software</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Data Sources:</span></div><div><span style="font-size: medium;">The World Bank</span></div><div><span style="font-size: medium;">https://data.worldbank.org/indicator/SP.DYN.LE00.IN</span></div><div><br /></div><div><span style="font-size: medium;">Made with Natural Earth</span></div><div><span style="font-size: large;">https://www.naturalearthdata.com</span></div></div><div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgswV5foHQt05ZUfx8IN8qhRt9CMoLBo_D3TtuuM9d_WwWRw4-XEBqGLfCe8ObvN1CaGleYs0tYrhYwnrFUhdD6YuMnH-okqXotrT4xORnfkyTzdGMGlX-wS6r5NqizkInDNqzi7THD6kJWiK0SCxIOTPXwRkvGMiQJGZo8rNNr1fFQnp9xPZpERA/s4096/Day08-08nov23-africa-life-expectancy-at-birth-2021-4Post.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2160" data-original-width="4096" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgswV5foHQt05ZUfx8IN8qhRt9CMoLBo_D3TtuuM9d_WwWRw4-XEBqGLfCe8ObvN1CaGleYs0tYrhYwnrFUhdD6YuMnH-okqXotrT4xORnfkyTzdGMGlX-wS6r5NqizkInDNqzi7THD6kJWiK0SCxIOTPXwRkvGMiQJGZo8rNNr1fFQnp9xPZpERA/s16000/Day08-08nov23-africa-life-expectancy-at-birth-2021-4Post.png" /></a></div><br /><span><!--more--></span><div><span style="font-size: medium;">09-Nov-23 Day 9: Hexagons </span><span style="font-size: large;">#30DayMapChallenge 2023</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Human Development Index (2021) for World Countries as Hexagons</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: large;">Visualization generated using MapnikRasterizer in FME from Safe Software</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Data Sources: </span></div><div><span style="font-size: medium;">UNDP "Human Development Report"</span></div><div><span style="font-size: medium;">https://hdr.undp.org/data-center/human-development-index#/indicies/HDI</span></div><div><br /></div><div><span style="font-size: medium;">Made with Natural Earth</span></div><div><span style="font-size: large;">https://www.naturalearthdata.com</span></div></div><div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgvSQfpCWhe17n2W78rzlccNJ0ipvl7MQ2g0geIRSb0V71LP1mX-J74yGJEAovNj3re0Pd195mps43SxumnI6wBZcJxY9o7KEdXRLg5QemKazwNgnDj3yThJXVLtuIHtmv_k1q9romhrsgrni44zBzBWXVyAA4z_ii4UpXdlnEWAMzioIIat8qb2Q/s4096/09nov23-hexagons-hdi-2021-4post.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2160" data-original-width="4096" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgvSQfpCWhe17n2W78rzlccNJ0ipvl7MQ2g0geIRSb0V71LP1mX-J74yGJEAovNj3re0Pd195mps43SxumnI6wBZcJxY9o7KEdXRLg5QemKazwNgnDj3yThJXVLtuIHtmv_k1q9romhrsgrni44zBzBWXVyAA4z_ii4UpXdlnEWAMzioIIat8qb2Q/s16000/09nov23-hexagons-hdi-2021-4post.png" /></a></div><br /><span><!--more--></span><div><span style="font-size: medium;">10-Nov-23 Day 10: North America </span><span style="font-size: large;">#30DayMapChallenge 2023</span></div><div><span style="font-size: medium;"><br /></span></div><div><div><span style="font-size: medium;">Electric Vehicle Registrations (2022)-North America Continent</span></div><div><span style="font-size: medium;">(Light-duty all electric vehicles only)</span></div></div><div><br /></div><div><span style="font-size: large;">Visualization generated using MapnikRasterizer in FME from Safe Software</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Data Sources: </span></div><div><div><span style="font-size: medium;">Alternative Fuels Data Center, U.S. Department of Energy</span></div><div><span style="font-size: medium;">https://afdc.energy.gov/data/10962</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">DIVA-GIS</span></div><div><span style="font-size: medium;">https://www.diva-gis.org/</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: large;">Made with Natural Earth</span></div></div><div><span style="font-size: large;">https://www.naturalearthdata.com</span></div></div><div><span style="font-size: large;"><br /></span></div><div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjoJL_fhEMpUgGzE4RHpYqA0A1NDbtoPNVdyrnpbdCQ8Gk0NlKJ_A74yNmfu-StB9kIz9ZfMmcJnuUOxPlwvr50ZBjgghReBWDz8l361uV0dUjyld_oI11P2oEKjydpsuk2VAT8fxEsDTvphKOzUL5MSj4fvUEXBKHyyXaS1sQq8KqcO9ZhrqpM4A/s4084/Day10-10nov23-north-america-ev-registrations-statewise-2022-4Post.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2136" data-original-width="4084" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjoJL_fhEMpUgGzE4RHpYqA0A1NDbtoPNVdyrnpbdCQ8Gk0NlKJ_A74yNmfu-StB9kIz9ZfMmcJnuUOxPlwvr50ZBjgghReBWDz8l361uV0dUjyld_oI11P2oEKjydpsuk2VAT8fxEsDTvphKOzUL5MSj4fvUEXBKHyyXaS1sQq8KqcO9ZhrqpM4A/s16000/Day10-10nov23-north-america-ev-registrations-statewise-2022-4Post.png" /></a></div><br /><span><!--more--></span><div><span style="font-size: medium;">11-Nov-23 Day 11: Retro </span><span style="font-size: large;">#30DayMapChallenge 2023</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Pulicat Lake and Environs (1955) overlaid with current OpenStreetMap layers</span></div><div><br /></div><div><span style="font-size: large;">Visualization generated using MapnikRasterizer in FME from Safe Software</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Data Sources: </span></div><div><div><div><span style="font-size: medium;">ND 44-10 Madras. Tile of the Map India and Pakistan 1:250,000. Series U502, U.S. Army Map Service, 1955</span></div><div><span style="font-size: medium;">https://maps.lib.utexas.edu/maps/ams/india/</span></div></div><div><span style="font-size: medium;"><br /></span></div><div><div><span style="font-size: large;">© OpenStreetMap</span></div><div><span style="font-size: medium;">Accessed on 10-November-2023</span></div></div></div></div><div><span style="font-size: medium;"><br /></span></div><div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjlfhtDQjH3XmivXTyQYNH2A9mI05JU5LUP2dgv8nPLtGoOyKe43yxFPVbJbKqC_b7U_gscSfYfenW5r0NwZgNeBAet3-OkbCwxNeu2VxyvAD3VNnZj6DpkfXOzqJaajShDzE3T4Uunm10w2clvhyphenhyphendoQJtJhyphenhyphendpjMJpr-aeCg3FrHzJXaZHXHOEXQ/s4084/Day11-11nov23-retro-pulicat_lake_1955-4Post.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2136" data-original-width="4084" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjlfhtDQjH3XmivXTyQYNH2A9mI05JU5LUP2dgv8nPLtGoOyKe43yxFPVbJbKqC_b7U_gscSfYfenW5r0NwZgNeBAet3-OkbCwxNeu2VxyvAD3VNnZj6DpkfXOzqJaajShDzE3T4Uunm10w2clvhyphenhyphendoQJtJhyphenhyphendpjMJpr-aeCg3FrHzJXaZHXHOEXQ/s16000/Day11-11nov23-retro-pulicat_lake_1955-4Post.png" /></a></div><br /><span><!--more--></span><div><span style="font-size: medium;">12-Nov-23 Day 12: South America </span><span style="font-size: large;">#30DayMapChallenge 2023</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">UNESCO World Heritage Sites in South America</span></div><div><br /></div><div><span style="font-size: large;">Visualization generated using MapnikRasterizer in FME from Safe Software</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Data Sources: </span></div><div><div><div><span style="font-size: medium;">UNESCO World Heritage List</span></div><div><span style="font-size: medium;">https://whc.unesco.org/en/list/</span></div></div><div><span style="font-size: medium;"><br /></span></div><div><div><span style="font-size: large;">Made with Natural Earth</span></div><div><div><span style="font-size: large;">https://www.naturalearthdata.com<br /></span></div></div></div></div></div><div><span style="font-size: large;"><br /></span></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiLoFH8lE_L5U_dOu8TuzKja-rtE-Kn0vnttQCA3kCcdPtXzDNBsSI-QgvyMXnC6v25ueggc-0RSeFkePDkEe3Q26FaxiRvKUCrk0KnKE7YcCyzW7jT0AO1zUxzgzDGXsRRuum-ML_Vosy7OlcgOFM0iWoXSmI_t0_rGjxJKWwSsJte77kdN1wLoQ/s8933/Day12-12nov23-south-america-world_heritage_sites-4Post.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="8933" data-original-width="6434" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiLoFH8lE_L5U_dOu8TuzKja-rtE-Kn0vnttQCA3kCcdPtXzDNBsSI-QgvyMXnC6v25ueggc-0RSeFkePDkEe3Q26FaxiRvKUCrk0KnKE7YcCyzW7jT0AO1zUxzgzDGXsRRuum-ML_Vosy7OlcgOFM0iWoXSmI_t0_rGjxJKWwSsJte77kdN1wLoQ/s16000/Day12-12nov23-south-america-world_heritage_sites-4Post.png" /></a></div><br /><span><!--more--></span><div><div><span style="font-size: medium;">13-Nov-23 Day 13: Choropleth </span><span style="font-size: large;">#30DayMapChallenge 2023</span></div><div><span style="font-size: medium;"><br /></span></div><div><div><span style="font-size: medium;"><div>Life Expectancy at Birth,total (years) for World Countries (2021)</div><div><br /></div></span></div></div><div><span style="font-size: large;">Visualization generated using MapnikRasterizer in FME from Safe Software</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Data Sources: </span></div><div><div><div><span style="font-size: medium;">The World Bank</span></div><div><span style="font-size: medium;">https://data.worldbank.org/indicator/SP.DYN.LE00.IN</span></div></div><div><br /></div><div><div><span style="font-size: large;">Made with Natural Earth</span></div><div><span style="font-size: large;">https://www.naturalearthdata.com</span></div></div></div></div><div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgF6mkWXkAvenyJsYtKLydQ55zc0p-TBVaSiQhc7hRl8vMzloopnWRDF6YDGBq1I4Etp235JeGKAiLBeTDbbLtW8OmYbxK0rdQoO5Sz5fLcknam-O72VyHAM5vlHlnpgg_pGh_EVQDlF5q_fk_ypJZxEZJjQLCNOsVjVl58ryNAAkJcy4g9AwwKVA/s4096/Day13-13nov23-Choropleth-LifeExpectancyatBirth2021-4Post.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2160" data-original-width="4096" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgF6mkWXkAvenyJsYtKLydQ55zc0p-TBVaSiQhc7hRl8vMzloopnWRDF6YDGBq1I4Etp235JeGKAiLBeTDbbLtW8OmYbxK0rdQoO5Sz5fLcknam-O72VyHAM5vlHlnpgg_pGh_EVQDlF5q_fk_ypJZxEZJjQLCNOsVjVl58ryNAAkJcy4g9AwwKVA/s16000/Day13-13nov23-Choropleth-LifeExpectancyatBirth2021-4Post.png" /></a></div><br /><span><!--more--></span><div><span style="font-size: medium;">14-Nov-23 Day 14: Europe </span><span style="font-size: large;">#30DayMapChallenge 2023</span></div><div><span style="font-size: medium;"><br /></span></div><div><div><span style="font-size: medium;"><div>Percentage of Total Population aged 65 years and above for European Countries (2022)</div><div><br /></div></span></div></div><div><span style="font-size: large;">Visualization generated using MapnikRasterizer in FME from Safe Software</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Data Sources: </span></div><div><div><div><span style="font-size: medium;">The World Bank</span></div><div><span style="font-size: medium;">https://data.worldbank.org/indicator/SP.POP.65UP.TO.ZS</span></div></div><div><br /></div><div><div><span style="font-size: large;">Made with Natural Earth</span></div><div><span style="font-size: large;">https://www.naturalearthdata.com</span></div></div></div></div><div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg1E9EjVQu-BptCZo2fyq1_lMJTznnmh10TTzZX-WCpxNQz5nv5k3q21fzeFSGoagIMt9GgESAca_OIVh-rQSvI07J1-4320JSbTCXj_fZvz7padYOMS0Reo6RmiN-QAx0iDHxviQmkgQD57vivsCESt9b0Z2IbUZ5lZHDw6skt64gPQiVH6_WjHQ/s4096/Day14-14nov23-europe-percent_pop-aged65-above-2022-4Post.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2147" data-original-width="4096" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg1E9EjVQu-BptCZo2fyq1_lMJTznnmh10TTzZX-WCpxNQz5nv5k3q21fzeFSGoagIMt9GgESAca_OIVh-rQSvI07J1-4320JSbTCXj_fZvz7padYOMS0Reo6RmiN-QAx0iDHxviQmkgQD57vivsCESt9b0Z2IbUZ5lZHDw6skt64gPQiVH6_WjHQ/s16000/Day14-14nov23-europe-percent_pop-aged65-above-2022-4Post.png" /></a></div><br /><span><!--more--></span><div><span style="font-size: medium;">15-Nov-23 Day 15: OSM #30DayMapChallenge 2023</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">What an auspicious day!</span></div><div><span style="font-size: medium;">GIS Day 2023</span></div><div><span style="font-size: medium;">With #iccworldcup2023 #worldcup2023 #worldcupcricket fever gripping everyone and #indiancricketteam facing the #newzealand team today in the semi-finals of #worldcup2023 #cricket was my natural choice for the #30daymapchallenge post today!</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">#cricket Pitches and Cricket Nets in and around Chennai from Open Street Map (Leisure Layer: "pitch")</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Visualization generated using MapnikRasterizer in FME from Safe Software</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Data Sources: </span></div><div><span style="font-size: medium;">OpenStreetMap</span></div><div><span style="font-size: medium;">Accessed on 13-November-2023</span></div></div><div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhnUlMDgdIfzKUSh6Pzj7zLfxveDVvCQVoVk8sFv0u70FDOQe_iWEE9oUi-Vgf06_t8rmAah0l8PNRzb47Z2p1l_E9MnLgvDTZ3-kMFWDLdj9zZgW-lrtLkJJ6SoOdh5OiPENinAoz9iw_zu2NCfJUmGpOV31KtzRBfekrtFaLK5rBrHPk8391OeA/s6700/15nov23-osm-chennai-cricket-pitches-4Post.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="6700" data-original-width="4826" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhnUlMDgdIfzKUSh6Pzj7zLfxveDVvCQVoVk8sFv0u70FDOQe_iWEE9oUi-Vgf06_t8rmAah0l8PNRzb47Z2p1l_E9MnLgvDTZ3-kMFWDLdj9zZgW-lrtLkJJ6SoOdh5OiPENinAoz9iw_zu2NCfJUmGpOV31KtzRBfekrtFaLK5rBrHPk8391OeA/s16000/15nov23-osm-chennai-cricket-pitches-4Post.png" /></a></div><br /><span><!--more--></span><span style="font-size: medium;"><div>16-Nov-23 Day 16: Oceania #30DayMapChallenge 2023</div><div><br /></div><div>Life Expectancy at Birth, total (years) for 14 Oceania Countries (2021)</div><div><br /></div><div>Visualization generated using MapnikRasterizer in FME from Safe Software</div><div><br /></div><div>Data Sources: </div><div>The World Bank</div><div>https://data.worldbank.org/indicator/SP.DYN.LE00.IN</div><div><br /></div><div>Made with Natural Earth</div><div>https://www.naturalearthdata.com</div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi-xhgUH2pDrCNwP3LQ24TLxwyudE_o71RJ3XTHM02zMNUTPd-g3tYEwrhR1tk3x_R_bGVskQWOCVW9fIBXewsStesf6Boow0OiB3KIr-KOGm3Vqed3CG_gp9yJLfx0qGGPGtQLbhbGZaWeAWbAkKFNvctxNIhWqbo9DzryIPUB-FsQO1mV_flPIQ/s4083/Day16-16nov23-oceania-life-expectancy-at-birth-2021-4Post.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2152" data-original-width="4083" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi-xhgUH2pDrCNwP3LQ24TLxwyudE_o71RJ3XTHM02zMNUTPd-g3tYEwrhR1tk3x_R_bGVskQWOCVW9fIBXewsStesf6Boow0OiB3KIr-KOGm3Vqed3CG_gp9yJLfx0qGGPGtQLbhbGZaWeAWbAkKFNvctxNIhWqbo9DzryIPUB-FsQO1mV_flPIQ/s16000/Day16-16nov23-oceania-life-expectancy-at-birth-2021-4Post.png" /></a></div><br /><span><!--more--></span><div><div>17-Nov-23 Day 17: Flow #30DayMapChallenge 2023</div><div><br /></div><div>Traffic Index by Country (2023)</div><div><br /></div><div>Visualization generated using MapnikRasterizer in FME from Safe Software</div><div><br /></div><div>Data Sources: </div><div>Numbeo</div><div>https://www.numbeo.com/traffic/rankings_by_country.jsp?title=2023</div><div><br /></div><div>Made with Natural Earth</div><div>https://www.naturalearthdata.com</div></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh4qg3u_wto8v31FoVSYJ_b3XmKWLIQ-p6zkSo23UdUqHAWXePePCJoyVwj47crCmChMQZzFSC0gG_LJMeduWzaXDbqAWYqpGON0ztb0609Fd0rCe03lt1xrGAaDueAkp7Ks-wd4khsc4v4BSadsnkasgENboFrBAEkFy_mqmiBvgvoWxxtWhhu2A/s3840/Day17-17nov23-flow-traffic_index-2023-4Post.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2196" data-original-width="3840" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh4qg3u_wto8v31FoVSYJ_b3XmKWLIQ-p6zkSo23UdUqHAWXePePCJoyVwj47crCmChMQZzFSC0gG_LJMeduWzaXDbqAWYqpGON0ztb0609Fd0rCe03lt1xrGAaDueAkp7Ks-wd4khsc4v4BSadsnkasgENboFrBAEkFy_mqmiBvgvoWxxtWhhu2A/s16000/Day17-17nov23-flow-traffic_index-2023-4Post.png" /></a></div><br /><span><!--more--></span><div><div>18-Nov-23 Day 18: Atmosphere #30DayMapChallenge 2023</div><div><br /></div><div>Average Precipitation in Depth (mm per year) for 2020</div><div><br /></div><div>Average hashtag#precipitation is the long-term average in depth (over space and time) of annual precipitation in the country. Precipitation is defined as any kind of water that falls from clouds as a liquid or a solid.</div><div><br /></div><div>Visualization generated using MapnikRasterizer in FME from Safe Software</div><div><br /></div><div>Data Sources: </div><div>The World Bank</div><div>https://data.worldbank.org/indicator/AG.LND.PRCP.MM</div><div><br /></div><div>Made with Natural Earth</div><div>https://www.naturalearthdata.com</div></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjAG3u01SuSyZWRF_i_3uPg4BvWgdeAured_aQwhsJHn7K_mbLp-8jH7IDfU32RcAOl3KIOE38oLsg-9ks3OSgUvuOle27vMsNEGhYY74Drfd883ACx-D5qUwdxsV0tya9Mfy9cAwwCuc9r2GbhjtxCj6RQEqhyphenhyphen0aiyL1wM0bdX8__DGnBlxRNIPg/s4083/Day18-18Nov23-Atmosphere-AvgAnnualPrecipitation2020-4Post.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2152" data-original-width="4083" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjAG3u01SuSyZWRF_i_3uPg4BvWgdeAured_aQwhsJHn7K_mbLp-8jH7IDfU32RcAOl3KIOE38oLsg-9ks3OSgUvuOle27vMsNEGhYY74Drfd883ACx-D5qUwdxsV0tya9Mfy9cAwwCuc9r2GbhjtxCj6RQEqhyphenhyphen0aiyL1wM0bdX8__DGnBlxRNIPg/s16000/Day18-18Nov23-Atmosphere-AvgAnnualPrecipitation2020-4Post.png" /></a></div><br /><span><!--more--></span><div><div>19-Nov-23 Day 19: A 5-minute map #30DayMapChallenge 2023</div><div><br /></div><div>A map generated in 5 minutes to demonstrate the Speed of Data Integration using MapnikRasterizer and FeatureShuffler in FME from Safe Software</div><div><br /></div><div>Visualization generated using MapnikRasterizer in FME from Safe Software</div><div><br /></div><div>Data Sources: </div><div>https://engage.safe.com/fme/formats-matrix/</div><div>Accessed on 19-Nov-23</div><div><br /></div><div>Made with Natural Earth</div><div>https://www.naturalearthdata.com</div></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiSP7XAPyiZRBxetYkz1dxkQ2IboEGkYmGJTZkod6dKqm6xWxnbUNHB-KsvxMM20IUMBtgxqZH7VqGe0z9JUuBmbsDuU7hupSo7WgVL7w-vb-pzvIxA95XsTytZQCCtjgx9f7iC7trFT06aEXozdEPBStgSWNcGkfNR2JEQ6M1ZAjE-nzl1wvImxA/s4096/19nov23-5minutemap-fme-formats-4post.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2160" data-original-width="4096" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiSP7XAPyiZRBxetYkz1dxkQ2IboEGkYmGJTZkod6dKqm6xWxnbUNHB-KsvxMM20IUMBtgxqZH7VqGe0z9JUuBmbsDuU7hupSo7WgVL7w-vb-pzvIxA95XsTytZQCCtjgx9f7iC7trFT06aEXozdEPBStgSWNcGkfNR2JEQ6M1ZAjE-nzl1wvImxA/s16000/19nov23-5minutemap-fme-formats-4post.png" /></a></div><br /><span><!--more--></span><div><div>20-Nov-23 Day 20: Outdoors #30DayMapChallenge 2023</div><div><br /></div><div>Kalindi Khal Trek Route (Gangotri to Badrinath ~100Km)</div><div><br /></div><div>Kalindi Khal Trek is a high altitude mountain pass connecting Gangotri and Badrinath.The pass is heavily glaciated. The glacier west of the pass flows into the Gangotri Glacier which forms the source of the Ganges. Even though the Kalindi khal is the most famous trekking pas in the Garhwal Himalaya, it is nevertheless a challenging high altitude glacial trek. This is the 2nd Highest pass of The Himalayan Range. The trek takes minimum of 6 days if already acclimatized. The trek is usually done in summer from mid-June to mid-September.</div><div>Maximum Altitude: 5950 m or 19,500 ft (Approx)</div><div><br /></div><div>Visualization generated using MapnikRasterizer in FME from Safe Software</div><div><br /></div><div>Data Sources: </div><div>Sharada Prasad Chitradurga Srinivasa Murthy</div><div>GPX file – Kalindi Khal pass trek</div><div>https://sharadaprasad.com/post/465/</div><div>contact@sharadaprasad.com</div><div><br /></div><div>Cartosat-1 DEM - Version-3R1</div><div>Bhuvan NOEDA Data </div><div>National Remote Sensing Centre, ISRO</div><div><br /></div><div>OpenStreetMap</div></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhSHYTamORt1KCH_aqyggiRX1hHjqZ3qbEt8McvteZ6u-lM2CoMx4RFU7MkpmrSCSEMyPoHJF8kdzU_0ru6QVhU2CjAzVkPYYJNL93a3wwZx7DCHHrUlrirYem5j051q7JatEklJR4sABXG93EOl9I0P0YbGcOHBxas0tQ1iaFSei2EtMo2Y_u1FQ/s4096/Day20-20Nov23-Outdoors-KalindiKhalTrek4Post.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2159" data-original-width="4096" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhSHYTamORt1KCH_aqyggiRX1hHjqZ3qbEt8McvteZ6u-lM2CoMx4RFU7MkpmrSCSEMyPoHJF8kdzU_0ru6QVhU2CjAzVkPYYJNL93a3wwZx7DCHHrUlrirYem5j051q7JatEklJR4sABXG93EOl9I0P0YbGcOHBxas0tQ1iaFSei2EtMo2Y_u1FQ/s16000/Day20-20Nov23-Outdoors-KalindiKhalTrek4Post.png" /></a></div><br /><div><br /></div><div class="separator" style="clear: both; text-align: center;"><br /></div><div><span><!--more--></span><span style="font-size: medium;"><div>21-Nov-23 Day 21: Raster #30DayMapChallenge 2023</div><div><br /></div><div>K2 or Kanchenjunga</div><div><br /></div><div style="text-align: justify;">Kangchenjunga, also spelled hashtag#Kanchenjunga, Kanchanjanghā and Khangchendzonga (The five treasures of the high snow), is the third-highest mountain in the world. Its summit lies at 8,586 m (28,169 ft) in a section of the Himalayas, the Kangchenjunga Himal, which is bounded in the west by the Tamur River, in the north by the Lhonak River and Jongsang La, and in the east by the Teesta River. It lies in the border region between Nepal and Sikkim state of India, with three of the five peaks, namely Main, Central and South, directly on the borderand the peaks West and Kangbachen in Nepal's Taplejung District. [Wikipedia, the Free Encyclopedia]</div><div style="text-align: justify;"><br /></div><div>Visualization generated using MapnikRasterizer in FME from Safe Software</div><div><br /></div><div>Data Sources: </div><div>Cartosat-1 DEM - Version-3R1</div><div>Bhuvan NOEDA Data </div><div>National Remote Sensing Centre, ISRO</div></span></div><div></div></span></div><div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiHMk3_nyPjlvZNiLzIPckRXGOT3EBXyKgQhBXRSnxcD7xjh44qvniOen3n9VY9bvN2aZd5bS3NP3tW-yn_8A2hvIHkECmLMyVxhcjvsn-FcAPZUJRNtFjxY9hzsVKxAmFiw4fpy_l_RLwht1ObnoZpThuB9dm2xfYNgX364V0nZeH7W6GxOWEXUw/s3376/21nov23-raster-the-kanchenjunga4Post.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="3376" data-original-width="2159" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiHMk3_nyPjlvZNiLzIPckRXGOT3EBXyKgQhBXRSnxcD7xjh44qvniOen3n9VY9bvN2aZd5bS3NP3tW-yn_8A2hvIHkECmLMyVxhcjvsn-FcAPZUJRNtFjxY9hzsVKxAmFiw4fpy_l_RLwht1ObnoZpThuB9dm2xfYNgX364V0nZeH7W6GxOWEXUw/s16000/21nov23-raster-the-kanchenjunga4Post.png" /></a></div></div><span><!--more--></span><div class="separator" style="clear: both; text-align: center;"><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">22-Nov-23 Day 22: North #30DayMapChallenge 2023</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">South Up or Upside Down or Reversed Map of the World (of course using FME from Safe Software)</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">South-up map orientation is the orientation of a map with south up, at the top of the map, amounting to a 180-degree rotation of the map from the standard convention of north-up. Maps in this orientation are sometimes called upside down maps or reversed maps.</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">The history of south-up map orientation as political statement can be traced back to the early 1900s. Joaquín Torres García, a Uruguayan modernist painter, created one of the first maps to make a political statement related to north-south map positions entitled "América Invertida". "Torres-García placed the South Pole at the top of the earth, thereby suggesting a visual affirmation of the importance of the (South American) continent."</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">A popular example of a south-up oriented map designed as a political statement is "McArthur's Universal Corrective Map of the World" (1979). An insert on this map explains that the Australian, Stuart McArthur, sought to confront "the perpetual onslaught of 'downunder' jokes—implications from Northern nations that the height of a country's prestige is determined by its equivalent spatial location on a conventional map of the world".McArthur's Universal Corrective Map of the World (1979) has sold over 350,000 copies to date. [Wikipedia, the Free Encyclopedia]</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Visualization generated using MapnikRasterizer in FME from Safe Software</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Data Sources: </span></div><div><span style="font-size: large;">Made with Natural Earth</span></div><div><span style="font-size: medium;">https://www.naturalearthdata.com</span></div><div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhv4woUY0x27lhaob4vXcT4bJlYfKQm2GKw2k-tpOzbAF4hZjOrDy73JITzCNGUYYdYvms6N_x_JcBQ1IvJTvzqQHCjO8XJe5NvOgX3GAeZ6LXjviTtxtWBhcHoF0sJhFd1AokFSchElEOI8FyJpab0iCPTplKZCdbf95Y43XD3C-aNeajFf7WjIA/s4096/Day22-22nov23-north-down-4post.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2160" data-original-width="4096" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhv4woUY0x27lhaob4vXcT4bJlYfKQm2GKw2k-tpOzbAF4hZjOrDy73JITzCNGUYYdYvms6N_x_JcBQ1IvJTvzqQHCjO8XJe5NvOgX3GAeZ6LXjviTtxtWBhcHoF0sJhFd1AokFSchElEOI8FyJpab0iCPTplKZCdbf95Y43XD3C-aNeajFf7WjIA/s16000/Day22-22nov23-north-down-4post.png" /></a></div><span><!--more--></span><div class="separator" style="clear: both; text-align: center;"><div class="separator" style="clear: both; text-align: justify;"><span style="font-size: medium;">23-Nov-23 Day 23: 3D #30DayMapChallenge 2023</span></div><div class="separator" style="clear: both; text-align: justify;"><span style="font-size: medium;"><br /></span></div><div class="separator" style="clear: both; text-align: justify;"><span style="font-size: medium;">K2 or Kanchenjunga in 3D</span></div><div class="separator" style="clear: both; text-align: justify;"><span style="font-size: medium;"><br /></span></div><div class="separator" style="clear: both; text-align: justify;"><span style="font-size: medium;">Kangchenjunga, also spelled hashtag#Kanchenjunga, Kanchanjanghā and Khangchendzonga (The five treasures of the high snow), is the third-highest mountain in the world. Its summit lies at 8,586 m (28,169 ft) in a section of the Himalayas [Wikipedia, the Free Encyclopedia]</span></div><div class="separator" style="clear: both; text-align: justify;"><span style="font-size: medium;"><br /></span></div><div class="separator" style="clear: both; text-align: justify;"><span style="font-size: medium;">Visualization using FME Data Inspector utility in FME from Safe Software</span></div><div class="separator" style="clear: both; text-align: justify;"><span style="font-size: medium;"> </span></div><div class="separator" style="clear: both; text-align: justify;"><span style="font-size: medium;">The FME Data Inspector is a utility that allows you to view and save data in any FME-supported format. It is used primarily to preview data before translation and to verify it after the translation. It can also be used to check data at any point during a translation; as you use FME, you'll find the FME Data Inspector is useful when setting up complex transformations because you can examine the output at each step.</span></div><div class="separator" style="clear: both; text-align: justify;"><span style="font-size: medium;"><br /></span></div><div class="separator" style="clear: both; text-align: justify;"><span style="font-size: medium;">Data Sources: </span></div><div class="separator" style="clear: both; text-align: justify;"><span style="font-size: medium;">Cartosat-1:DEM - Version-3R1: Bhuvan NOEDA Data</span></div><div class="separator" style="clear: both; text-align: justify;"><span style="font-size: medium;">National Remote Sensing Centre, ISRO</span></div></div><div style="text-align: justify;"><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgY1a_4lk9plRWAdTDvV_x9h8q16RPe1LI1_3W53JL1A00xZ3-ikbhVCV4T2ZNJqZqGKUrHHD4H7YWiwe2NcY8JdOG93eI9kMPJSrJKjMO4-IOLlAhrT-66upfXFeyLPSNzXuNYXUc-HWMXbvLrKa1q4uqO0gnLPcgWCdW8r7f8pkthL7ngdeq12w/s3376/23nov23-3d-kanchenjunga4Post.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="3376" data-original-width="2159" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgY1a_4lk9plRWAdTDvV_x9h8q16RPe1LI1_3W53JL1A00xZ3-ikbhVCV4T2ZNJqZqGKUrHHD4H7YWiwe2NcY8JdOG93eI9kMPJSrJKjMO4-IOLlAhrT-66upfXFeyLPSNzXuNYXUc-HWMXbvLrKa1q4uqO0gnLPcgWCdW8r7f8pkthL7ngdeq12w/s16000/23nov23-3d-kanchenjunga4Post.png" /></a></div><span><!--more--></span><div class="separator" style="clear: both; text-align: center;"><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">24-Nov-23 Day 24: Two Colours #30DayMapChallenge 2023</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Continents Surrounded (Black) and Not Surrounded (White) Completely by Ocean in Two Colors</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Of the seven most globally recognized continents, only Antarctica and Australia are completely separated from other continents by the ocean. Several continents are defined not as absolutely distinct bodies but as "more or less discrete masses of land".</span></div><div><span style="font-size: medium;">https://en.wikipedia.org/wiki/Continent</span></div><div><span style="font-size: medium;">[Wikipedia, the Free Encyclopedia]</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Visualization generated using MapnikRasterizer in FME from Safe Software</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Data Sources: </span></div><div><span style="font-size: medium;">Shepherd, Stephanie (2020). Continent Polygons. figshare. </span></div><div><span style="font-size: medium;">Dataset. </span></div><div><span style="font-size: medium;">https://figshare.com/articles/dataset/Continent_Polygons/12555170/3<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiKv1b21hTcnVAqzz1iZS23XOlPkTWp_vo9SJSM1eNfd1fDQKuDHRjtJTHsxPMMZ64AU9FCv2qTPKpItRA4X3_HOL37UnFhutoRaXzSFgiC_QzhYEXU2SKUOQqJsKWq6rMW5CF7vxMU4euBjDJYLKmGHQawjtOqhrqTuBf_mr4VLmPzEWSxEqQd1A/s4083/Day24-24Nov23-TwoColors-Continents_SurroundedByWater-4Post.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2152" data-original-width="4083" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiKv1b21hTcnVAqzz1iZS23XOlPkTWp_vo9SJSM1eNfd1fDQKuDHRjtJTHsxPMMZ64AU9FCv2qTPKpItRA4X3_HOL37UnFhutoRaXzSFgiC_QzhYEXU2SKUOQqJsKWq6rMW5CF7vxMU4euBjDJYLKmGHQawjtOqhrqTuBf_mr4VLmPzEWSxEqQd1A/s16000/Day24-24Nov23-TwoColors-Continents_SurroundedByWater-4Post.png" /></a></div><span><!--more--></span><div class="separator" style="clear: both; text-align: center;"><div class="separator" style="clear: both; text-align: justify;">25-Nov-23 Day 25: Antarctica #30DayMapChallenge 2023</div><div class="separator" style="clear: both; text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: justify;">Antarctica: Contour Map with Places</div><div class="separator" style="clear: both; text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: justify;">Visualization generated using MapnikRasterizer in FME from Safe Software</div><div class="separator" style="clear: both; text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: justify;">Data Sources: </div><div class="separator" style="clear: both; text-align: justify;">British Antarctic Survey</div><div class="separator" style="clear: both; text-align: justify;">Gerrish, L., Fretwell, P., & Cooper, P. (2020). High resolution vector contours for Antarctica (7.3) [Data set]. UK Polar Data Centre, Natural Environment Research Council, UK Research & Innovation. </div><div class="separator" style="clear: both; text-align: justify;">https://data.bas.ac.uk/items/4bd20a2b-df7d-46a2-acdf-5104c82ff4c7/</div><div class="separator" style="clear: both; text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: justify;">MapCruzin</div><div class="separator" style="clear: both; text-align: justify;">https://mapcruzin.com/free-antarctica-country-city-place-gis-shapefiles.htm</div><div class="separator" style="clear: both; text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjbMb6zy1_YWGIbXuiELaN9M_60ze0I8Zup0V_W3JIH_-HulUANH7jzDFN4dR_9OZWeKL6FihRcBBGrmeCISkGAekRp3TgQqQFmS4ntYShpcVeZOAVLiGNxzbOO9LxTV7lmbJxmbh814vA-LpnX6PxyKx7nYZrv-lNP3SWi6Z1XWz9VXCv8dflSlA/s4083/25nov23-antarctica-4Post.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2152" data-original-width="4083" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjbMb6zy1_YWGIbXuiELaN9M_60ze0I8Zup0V_W3JIH_-HulUANH7jzDFN4dR_9OZWeKL6FihRcBBGrmeCISkGAekRp3TgQqQFmS4ntYShpcVeZOAVLiGNxzbOO9LxTV7lmbJxmbh814vA-LpnX6PxyKx7nYZrv-lNP3SWi6Z1XWz9VXCv8dflSlA/s16000/25nov23-antarctica-4Post.png" /></a></div><br /><span><!--more--></span><div class="separator" style="clear: both; text-align: justify;"><div class="separator" style="clear: both;">26-Nov-23 Day 26: Minimal #30DayMapChallenge 2023</div><div class="separator" style="clear: both;"><br /></div><div class="separator" style="clear: both;">25 Least Polluted Cities in the World (2023)</div><div class="separator" style="clear: both;"><br /></div><div class="separator" style="clear: both;">Visualization generated using MapnikRasterizer in FME from Safe Software</div><div class="separator" style="clear: both;"><br /></div><div class="separator" style="clear: both;">Data Sources: </div><div class="separator" style="clear: both;">Smart Air</div><div class="separator" style="clear: both;">25 Least Polluted Cities and Countries in the World (2023 Rankings)</div><div class="separator" style="clear: both;">https://smartairfilters.com/en/blog/25-least-polluted-cities-in-world-2023-rankings/</div><div class="separator" style="clear: both;"><br /></div><div class="separator" style="clear: both;">Shepherd, Stephanie (2020). Continent Polygons. figshare. Dataset. </div><div class="separator" style="clear: both;">https://figshare.com/articles/dataset/Continent_Polygons/12555170/3</div><div class="separator" style="clear: both;"><br /></div></div></div></span></div></div></div><div><br /><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhgEakdqkQRXobaJAGvPwTdf8ZMI3YGRFwk4XE9NS4blfolIz7On1fX6lfg9D94OpzrgYSrImLqW8a94mpgygGZThU5pg4kCyV13xRAUOkggpLG_6CIpp8ofvmgDVYYPXsVwh2oCF1QSBpi388xUSQRf29MSCKQseLXVZ8z4Eeic2k2HG76m3mSow/s4096/26nov23-minimal-least-polluted-cities-4Post.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2160" data-original-width="4096" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhgEakdqkQRXobaJAGvPwTdf8ZMI3YGRFwk4XE9NS4blfolIz7On1fX6lfg9D94OpzrgYSrImLqW8a94mpgygGZThU5pg4kCyV13xRAUOkggpLG_6CIpp8ofvmgDVYYPXsVwh2oCF1QSBpi388xUSQRf29MSCKQseLXVZ8z4Eeic2k2HG76m3mSow/s16000/26nov23-minimal-least-polluted-cities-4Post.png" /></a></div></div><span><!--more--></span><div class="separator" style="clear: both; text-align: center;"><div class="separator" style="clear: both; text-align: justify;"><span style="font-size: medium;">27-Nov-23 Day 27: Dot #30DayMapChallenge 2023</span></div><div class="separator" style="clear: both; text-align: justify;"><span style="font-size: medium;"><br /></span></div><div class="separator" style="clear: both; text-align: justify;"><span style="font-size: medium;">World Countries by Sovereignty using Different Colored Dots (69,313 Points) </span></div><div class="separator" style="clear: both; text-align: justify;"><span style="font-size: medium;"><br /></span></div><div class="separator" style="clear: both; text-align: justify;"><span style="font-size: medium;">Visualization generated using MapnikRasterizer in FME from Safe Software</span></div><div class="separator" style="clear: both; text-align: justify;"><span style="font-size: medium;"><br /></span></div><div class="separator" style="clear: both; text-align: justify;"><span style="font-size: large;">Data Sources: </span></div><div class="separator" style="clear: both; text-align: justify;"><span style="font-size: medium;">Made with Natural Earth</span></div><div class="separator" style="clear: both; text-align: justify;"><span style="font-size: medium;">https://www.naturalearthdata.com</span></div><div class="separator" style="clear: both; text-align: justify;"><span style="font-size: medium;"><br /></span></div><div class="separator" style="clear: both; text-align: justify;"><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjHTVrOUKUckOYthaYbpNhMEY1lpjvTStO5m4eR8TLCXcvtWjkPQES-zFS8tt7j7v_bQULwx_OsKryhordHV4P2TI3xLDo_B9ctXQ9jlOYjg1iwO62LRSWtCWkLKRtHATqfkWOEnb_xAprA_95xPMrj9KWkWiIwpf1xldBe8fyoqUgEX8uqKgIqwQ/s4096/Day27-27nov23-dot-world-countries-sovrgnty4Post.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2160" data-original-width="4096" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjHTVrOUKUckOYthaYbpNhMEY1lpjvTStO5m4eR8TLCXcvtWjkPQES-zFS8tt7j7v_bQULwx_OsKryhordHV4P2TI3xLDo_B9ctXQ9jlOYjg1iwO62LRSWtCWkLKRtHATqfkWOEnb_xAprA_95xPMrj9KWkWiIwpf1xldBe8fyoqUgEX8uqKgIqwQ/s16000/Day27-27nov23-dot-world-countries-sovrgnty4Post.png" /></a></div><br /><span><!--more--></span><span style="font-size: medium;"><div class="separator" style="clear: both;">28-Nov-23 Day 28: Is this a chart or a map? #30DayMapChallenge 2023</div><div class="separator" style="clear: both;"><br /></div><div class="separator" style="clear: both;">Women in National Parliaments (October 2023): Top 25</div><div class="separator" style="clear: both;"><br /></div><div class="separator" style="clear: both;">Visualization generated using MapnikRasterizer in FME from Safe Software</div><div class="separator" style="clear: both;"><br /></div><div class="separator" style="clear: both;">Data Sources: </div><div class="separator" style="clear: both;">Inter-Parliamentary Union</div><div class="separator" style="clear: both;">Inter-Parliamentary Union: Women in National Parliaments, October 2023</div><div class="separator" style="clear: both;">https://data.ipu.org/women-ranking?month=10&year=2023</div><div class="separator" style="clear: both;"><br /></div><div class="separator" style="clear: both;">Made with Natural Earth</div><div class="separator" style="clear: both;">https://www.naturalearthdata.com</div><div class="separator" style="clear: both;"><br /><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhxmFhQrnGTM95a8uylIAzdiYdRfFkrJJHD7K9wsI7AAsguahIylAWM-grjLLen_drhB2vCu_cB1ermHQbS4N2gpZUX8Udj2495jXlUz9scftDyAW4Aw9osS7etlJDRqnbv2PDfwRL4yjYaEEKKVf9Ie6jiqH9acMiHDYqQQqr0W5bi95IDkDyXOg/s4096/Day28-28nov23-ChartMap-WomenInParliamentOct2023-4Post.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2159" data-original-width="4096" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhxmFhQrnGTM95a8uylIAzdiYdRfFkrJJHD7K9wsI7AAsguahIylAWM-grjLLen_drhB2vCu_cB1ermHQbS4N2gpZUX8Udj2495jXlUz9scftDyAW4Aw9osS7etlJDRqnbv2PDfwRL4yjYaEEKKVf9Ie6jiqH9acMiHDYqQQqr0W5bi95IDkDyXOg/s16000/Day28-28nov23-ChartMap-WomenInParliamentOct2023-4Post.png" /></a></div><div class="separator" style="clear: both; text-align: center;"><br /></div><div class="separator" style="clear: both; text-align: center;"><br /></div></div></span></div></div><span><!--more--></span><div><div><span style="font-size: medium;">29-Nov-23 Day 29: Population #30DayMapChallenge 2023</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Population Density (people per sq.km of land area) 2021</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Visualization generated using MapnikRasterizer in FME from Safe Software</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Data Sources: </span></div><div><span style="font-size: medium;">The World Bank</span></div><div><span style="font-size: medium;">https://data.worldbank.org/indicator/EN.POP.DNST</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Made with Natural Earth</span></div><div><span style="font-size: medium;">https://www.naturalearthdata.com</span></div></div><div><span style="font-size: medium;"><br /></span></div><div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjluVe0K5B2LxRH79DqWWtk5Kz1xBIO1tBRXpPHmPMn9tiilqjugZcrfDTI6WHdkSTJxB0l0KlN23hsHHsf6Jy3ZfO_eSzLqyJDtSn8qtRj1Jv6ezBBzPE64dHqobDFlEKBE9Rx48fzsQO-mFWw3lxv7lSv2VR-oZVuRXLv-p5DkEgJJ8OMEb30ww/s4096/Day29-29nov23-population-density2023-4post.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2160" data-original-width="4096" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjluVe0K5B2LxRH79DqWWtk5Kz1xBIO1tBRXpPHmPMn9tiilqjugZcrfDTI6WHdkSTJxB0l0KlN23hsHHsf6Jy3ZfO_eSzLqyJDtSn8qtRj1Jv6ezBBzPE64dHqobDFlEKBE9Rx48fzsQO-mFWw3lxv7lSv2VR-oZVuRXLv-p5DkEgJJ8OMEb30ww/s16000/Day29-29nov23-population-density2023-4post.png" /></a></div><br /><span style="font-size: medium;"><br /></span></div><div><br /></div><span><!--more--></span><div><div><span style="font-size: medium;">30-Nov-23 Day 30: My Favourite! #30DayMapChallenge 2023</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">My Favourite!</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Of course my favourite is FME from Safe Software</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">I take this last day of #30DayMapChallenge 2023 opportunity to show my affinity for FME by creating a world map flooded with my affinity for FME !</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Without FME from Safe Software, the #30DayMapChallenge 2023 would have been a herculean task!</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Visualization generated using MapnikRasterizer in FME from Safe Software</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Data Sources: </span></div><div><span style="font-size: medium;">Made with Natural Earth</span></div><div><span style="font-size: medium;">https://www.naturalearthdata.com</span></div></div><div><span style="font-size: medium;"><br /></span></div><div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh2UCzi0i6oxP6nEJzdsN_Ht5YxGvmu6X27Q_oNkY-xWv-g_BRlrhkj8AHKZT-OXOiSsNLIn_QYX09bdncd4FHXrOAfVm3_klhbKkKMOOV1pj09iRYBLt2Wt8hLyISnpvf_oPbuUTjzNnNv3AOlqH9ZfVLOXJngMuzdaJSbRHFvAUAxdtjJhdZebg/s4096/Day30-30nov23-favourite-ilovefme4post.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2160" data-original-width="4096" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh2UCzi0i6oxP6nEJzdsN_Ht5YxGvmu6X27Q_oNkY-xWv-g_BRlrhkj8AHKZT-OXOiSsNLIn_QYX09bdncd4FHXrOAfVm3_klhbKkKMOOV1pj09iRYBLt2Wt8hLyISnpvf_oPbuUTjzNnNv3AOlqH9ZfVLOXJngMuzdaJSbRHFvAUAxdtjJhdZebg/s16000/Day30-30nov23-favourite-ilovefme4post.png" /></a></div><span><!--more--></span><div class="separator" style="clear: both; text-align: center;"><br /></div><div><span style="font-size: medium;">30-Nov-23 Day 30: My Favourite! (second entry) #30DayMapChallenge 2023</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">My Favourite!</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">A happy world is what I like more than anything else!</span></div><div><span style="font-size: medium;">Let peace prevail!</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Visualization generated using MapnikRasterizer in FME from Safe Software</span></div><div><span style="font-size: medium;"><br /></span></div><div><span style="font-size: medium;">Data Sources: </span></div><div><span style="font-size: medium;">Made with Natural Earth</span></div><div><span style="font-size: medium;">https://www.naturalearthdata.com</span></div></div><div><span style="font-size: medium;"><br /></span></div><div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEheW3q26vQ-kiuKx1rXvNO2EH2tKRwsbleVgWo1WqJ_Ay-f6Ep9dwa7_r9m7A4JneQliRSDAI2HNhm2D-sO8nsFPW2rFXyk_67mxVwazi_Frh4yQpEYQar5x-M8yClYFjmkT0sQY9Yp4u4bxkxIKHIH9VXF-X3f97oe9FXqfIcko7mWraK8I2vc0g/s4096/Day30-30nov23-favourite-happy-world4post.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2160" data-original-width="4096" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEheW3q26vQ-kiuKx1rXvNO2EH2tKRwsbleVgWo1WqJ_Ay-f6Ep9dwa7_r9m7A4JneQliRSDAI2HNhm2D-sO8nsFPW2rFXyk_67mxVwazi_Frh4yQpEYQar5x-M8yClYFjmkT0sQY9Yp4u4bxkxIKHIH9VXF-X3f97oe9FXqfIcko7mWraK8I2vc0g/s16000/Day30-30nov23-favourite-happy-world4post.png" /></a></div></div><br /><hr /><div style="text-align: justify;"><span style="font-size: medium;">It may be 30 days of grueling, brainstorming; putting all your learning and experience into practice or self test To me, the whole idea of participating and contributing to #30DayMapChallenge 2023 is about promoting #GIS</span></div><div style="text-align: justify;"><span style="font-size: medium;"><br /></span></div><div style="text-align: justify;"><b><span style="color: #2b00fe; font-size: medium;">But then the satisfaction in having contributed to promotion of GIS outweighs everything else!</span></b></div><div style="text-align: justify;"><span style="color: #2b00fe; font-size: medium;"><br /></span></div><b><div style="text-align: justify;"><b><span style="color: #2b00fe; font-size: medium;">GIS Temper, Let us not lose it!</span></b></div></b><div style="text-align: justify;"><span style="font-size: medium;"><br /></span></div><div style="text-align: justify;"><span style="font-size: medium;">I take this opportunity to thank all those who contributed in some way or the other, to my career and to what I am today in the field of GIS!</span></div><div style="text-align: justify;"><span style="font-size: medium;"><br /></span></div><div style="text-align: justify;"><span style="font-size: medium;">Thanks to Safe Software for such a wonderful product/platform "FME" that helped me to convert,transform,share and integrate data from multi-farious sources and types, not just for this #30DayMapChallenge 2023, but for the last 23 years of my career in GIS</span></div><div style="text-align: justify;"><span style="font-size: medium;"><br /></span></div><div style="text-align: justify;"><span style="font-size: medium;">Last but not the least, special thanks to my family (my wife and son) for all the patience, understanding and support, while I meticulously worked on the submission every day!</span></div><div style="text-align: justify;"><span style="font-size: medium;"><br /></span></div><div style="text-align: justify;"><span style="font-size: medium;">More information about Topi Tjukanov (#30DayMapChallenge conceptualizer) https://medium.com/@tjukanov</span></div><div style="text-align: justify;"><span style="font-size: medium;">https://twitter.com/tjukanov</span></div></div></div></div></div>Saint GIShttp://www.blogger.com/profile/03296153994051314633noreply@blogger.com0tag:blogger.com,1999:blog-7854142.post-33530242855584835362022-12-31T02:19:00.003-08:002022-12-31T02:19:50.085-08:00Thirty Days of Mapping (FME-ing) #30DayMapChallenge 2022<a href="https://tjukanov.org/" target="_blank">Topi Tjukanov</a> of Finland launched the #30DayMapChallenge in 2019 where hundreds of maps were made and shared on social media using the
#30DayMapChallenge hashtag. Each days presents a map challenge focused on a different spatial feature or topic.
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The topics for #30dayMapChallenge 2022 were:<div>
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<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgYE7nz-DJIUJFwexW2k8goOAO0u8iGevu58wEbF_SlcCWQqriNpvg71VGV53pjMCPlpt4FEXcMOzuKWDrjFdER__4qjCWSiK1fKkbr4bUm_6X70Xciyp4buDutA8CISpuvcP-MBsXq4Als3LjGcCkKcPktS_pkNQnXU0a-dJFkAU3fscWxTqo/s960/30dmc-2022.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="540" data-original-width="960" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgYE7nz-DJIUJFwexW2k8goOAO0u8iGevu58wEbF_SlcCWQqriNpvg71VGV53pjMCPlpt4FEXcMOzuKWDrjFdER__4qjCWSiK1fKkbr4bUm_6X70Xciyp4buDutA8CISpuvcP-MBsXq4Als3LjGcCkKcPktS_pkNQnXU0a-dJFkAU3fscWxTqo/s16000/30dmc-2022.png" /></a></div><div class="separator" style="clear: both;">As a die hard user of FME from (<a href="https://www.safe.com" target="_blank">Safe Software</a>),what could be a better opportunity to put my FME skills to test!</div></div><div class="separator" style="clear: both;"><br /></div><div class="separator" style="clear: both;">I have been participating in #30DayMapChallenge @tjukanov since 2019.</div><div class="separator" style="clear: both;">Since 2020, I have been able to post an entry on all the 30 days of #30DayMapChallenge.</div><div class="separator" style="clear: both;">And that calls for a celebration! because it is a hat-trick.</div><div class="separator" style="clear: both;"><br /></div><div class="separator" style="clear: both;">This post is a collection of all entries for #30DayMapChallenge 2022 by @Saint_GIS, most of which have been accomplished only using FME and in few cases, due to the nature of the challenge, the data prepared using FME.</div><div class="separator" style="clear: both;"><br /></div><div class="separator" style="clear: both;">Some entries additionally have their #FMEAR Augmented Reality versions as well.</div><div class="separator" style="clear: both;"><div class="separator" style="clear: both;">Special thanks to <a href="https://twitter.com/dmitriatsafe" target="_blank">Dmitri Bagh</a> and <a href="https://ca.linkedin.com/in/lenabagh" target="_blank">Lena Bagh</a> at Safe Software for all the inspiration!</div><div class="separator" style="clear: both;"><br /></div><div class="separator" style="clear: both;">Happy FME-ing :-) reading my #30DayMapChallenge 2022 entries!</div></div>
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Day 1: Points
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First entry for the #30DayMapChallenge 2022- Some places (Points) with population more than 1.5 million generated using FME from Safe Software</div><div><br /><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhf_soojrZKKORx60bpnXQfVXCXPFIuCreiIYRTs5_CW-q2AC54CwbwPNUjXSOI8GkRdbAjZgCs0OkyxP9eMk--8iedAA3DPdVRR5oRQL02BRchb5_7y23JiZpZ27PWoqiU_qv8Aoww60f9M4WVMUkTHvUn6_aWlHUZBTI_pZQMLfPpTp_HxUE/s1920/Day1-Points-01Nov22-SomePlaces1.5MillionPopulation2022.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1080" data-original-width="1920" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhf_soojrZKKORx60bpnXQfVXCXPFIuCreiIYRTs5_CW-q2AC54CwbwPNUjXSOI8GkRdbAjZgCs0OkyxP9eMk--8iedAA3DPdVRR5oRQL02BRchb5_7y23JiZpZ27PWoqiU_qv8Aoww60f9M4WVMUkTHvUn6_aWlHUZBTI_pZQMLfPpTp_HxUE/s16000/Day1-Points-01Nov22-SomePlaces1.5MillionPopulation2022.png" /></a></div><div><br /></div>Additionally here is a #FMEAR version of this post</div><div class="separator" style="clear: both; text-align: center;"><iframe allowfullscreen='allowfullscreen' webkitallowfullscreen='webkitallowfullscreen' mozallowfullscreen='mozallowfullscreen' width='383' height='319' src='https://www.blogger.com/video.g?token=AD6v5dzih1iIVG3KEW5nIg1VYjw8x8DSowsoRyv4p2e0AJzDFzUEmxgxJg9tGp3PBOf8RAU2Q4wfRBFUV4w' class='b-hbp-video b-uploaded' frameborder='0'></iframe></div><div>
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Day 2: Lines
<br /><div>NH548 and NH118 are supposed to be the two shortest National Highway in #India 5 Km (3.1 mi) </div>
Data prepared using FME from Safe Software.<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhJ-3n-BG8wYh4z6Aw4fVmogFPBecUW-LPE0U4mzIVky_kiNCQOT6K0OpbxtJG4o5sKkgkna7u59Ghd9-_R856EWj_O6tnQyU7E7zHuMFUYlgCatltYKiilGWIX9IeGrVorqIXdB7jThN8PmbcdmEDAvPg6T6GX_YIls797d4dWPCIwKUPt4Ug/s1474/Day2-Lines-02Nov22-ShortestHighwayIndia_NH548_NH118.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="768" data-original-width="1474" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhJ-3n-BG8wYh4z6Aw4fVmogFPBecUW-LPE0U4mzIVky_kiNCQOT6K0OpbxtJG4o5sKkgkna7u59Ghd9-_R856EWj_O6tnQyU7E7zHuMFUYlgCatltYKiilGWIX9IeGrVorqIXdB7jThN8PmbcdmEDAvPg6T6GX_YIls797d4dWPCIwKUPt4Ug/s16000/Day2-Lines-02Nov22-ShortestHighwayIndia_NH548_NH118.png" /></a></div><br /><div class="separator" style="clear: both;">Additionally here is a #FMEAR version of this post</div><div class="separator" style="clear: both; text-align: center;"><iframe allowfullscreen='allowfullscreen' webkitallowfullscreen='webkitallowfullscreen' mozallowfullscreen='mozallowfullscreen' width='361' height='300' src='https://www.blogger.com/video.g?token=AD6v5dzGPfIHjCyniGmxPZCTFXzKGASmWSuWkeivbkgDMTxva3WbwoyIAY2Ih_MU65gx2az1aFNmuMlcLHI' class='b-hbp-video b-uploaded' frameborder='0'></iframe></div><br /><div class="separator" style="clear: both;"><br /></div>
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Day 3: Polygons
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World Countries by Sovereignty (Sovereignty represented through Concave Hull Polygons) using FME from Safe Software
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<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgA2zrPM-KEc1sCDoBfph6MlVt5wj_9LHc2xKYbJmW3MHXZj9ZIDhQaCgPNKskZUp1WH-FfcXkhMoCHIUqsNWm3yTlUyY6cLm6_-WvBjZpzWw5jMpJKRP2nTlNmoZmBlTKr8AazyOTdlbQA2o2yw08vZpv7mr3XAtrh2VoKQHuKTf_eSV4yZew/s7015/Day3_03Nov22-Polygons-WorldCountriesBySovereignty_ConcaveHullPolygons.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="7015" data-original-width="4960" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgA2zrPM-KEc1sCDoBfph6MlVt5wj_9LHc2xKYbJmW3MHXZj9ZIDhQaCgPNKskZUp1WH-FfcXkhMoCHIUqsNWm3yTlUyY6cLm6_-WvBjZpzWw5jMpJKRP2nTlNmoZmBlTKr8AazyOTdlbQA2o2yw08vZpv7mr3XAtrh2VoKQHuKTf_eSV4yZew/s16000/Day3_03Nov22-Polygons-WorldCountriesBySovereignty_ConcaveHullPolygons.png" /></a></div>Additionally here is a #FMEAR version of this post</div><div class="separator" style="clear: both; text-align: center;"><iframe allowfullscreen='allowfullscreen' webkitallowfullscreen='webkitallowfullscreen' mozallowfullscreen='mozallowfullscreen' width='352' height='293' src='https://www.blogger.com/video.g?token=AD6v5dx6--10XvydFXLIKxK6XHto3JSmrcoIGxq_qSE9U4B_EVdro3MTdvu6DUukKDiHBpsnZJxtKKQXeVY' class='b-hbp-video b-uploaded' frameborder='0'></iframe></div><br /><div><div class="separator" style="clear: both;"><br /></div>
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Day 4: Green<br /><div>Map of National Trees of Some Countries rendered using MapnikRasterizer in FME from Safe Software</div>
<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiDYySS0hgTJnajCegwD7wsXVKheMVNjp4k0WtPqLb9QkMqHBtIk0Hbj7aTYlnrBRwm0Re8XTD_gMwmk7w-_2tn7QAnPySNUa3t5vMCvRZJo6wcWScSRzeFZkk6HcLWOYyyqpG8zZKj2u4AlTUzKimJ9aQRvdFliJVXrFi2eCCqgaQAgyri_y4/s4096/Day4-04Nov22-Green-WorldCountriesNationalTrees4Post.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2160" data-original-width="4096" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiDYySS0hgTJnajCegwD7wsXVKheMVNjp4k0WtPqLb9QkMqHBtIk0Hbj7aTYlnrBRwm0Re8XTD_gMwmk7w-_2tn7QAnPySNUa3t5vMCvRZJo6wcWScSRzeFZkk6HcLWOYyyqpG8zZKj2u4AlTUzKimJ9aQRvdFliJVXrFi2eCCqgaQAgyri_y4/s16000/Day4-04Nov22-Green-WorldCountriesNationalTrees4Post.png" /></a></div><br /><div class="separator" style="clear: both;"><br /></div>
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Day 5: Ukraine<br />3D map of Mt Hoverla in Ukraine generated using FME from Safe Software</div><div>
<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi4a_5xy8D0e9MlrmOmBnzDfRlEqLux-xx6fZ2wdri6xqgoVRkGNNFR-BQQgEP_N4gDFWUWL7i8p9idx3G9YXshYhH3SxcCB0J1ldASpGcDRbDBUjQpcx_WqevjjrPKFOTfebp_eQbsz2KgQgfQf1fSxLJPOz2xt90JLWfNqHYWOAyvMP20d3E/s3849/Day5-05-Nov-22-Ukraine-MtHoverla-4Post.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2159" data-original-width="3849" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi4a_5xy8D0e9MlrmOmBnzDfRlEqLux-xx6fZ2wdri6xqgoVRkGNNFR-BQQgEP_N4gDFWUWL7i8p9idx3G9YXshYhH3SxcCB0J1ldASpGcDRbDBUjQpcx_WqevjjrPKFOTfebp_eQbsz2KgQgfQf1fSxLJPOz2xt90JLWfNqHYWOAyvMP20d3E/s16000/Day5-05-Nov-22-Ukraine-MtHoverla-4Post.png" /></a></div><br /><div class="separator" style="clear: both;"><br /></div>
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Day 6: Network<br /><div>3D Visualization of Traffic Signals Network from OpenStreetMap for Chennai using MapnikRasterizer in FME from Safe Software</div>
<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhfDfWO_lsVb1fvIt6ei6BwScpovKVRvUuon9FgmmfdtSmFyiiFs9Qtw3HpY8CftoYhwkBeG72dIwCCJhRjT9dMlPAZA7ejLXRjiFoeWgBXd8G8AVHKQ4E7V4Zx7ZnrCofs8JYXHcU2UBMdv6p3kq-RTP8ani1Lsa2YkU8bgebNZ-G3w5EErvY/s1920/Day6-Network-06Nov22-ChennaiTrafficSignals-3D.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1080" data-original-width="1920" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhfDfWO_lsVb1fvIt6ei6BwScpovKVRvUuon9FgmmfdtSmFyiiFs9Qtw3HpY8CftoYhwkBeG72dIwCCJhRjT9dMlPAZA7ejLXRjiFoeWgBXd8G8AVHKQ4E7V4Zx7ZnrCofs8JYXHcU2UBMdv6p3kq-RTP8ani1Lsa2YkU8bgebNZ-G3w5EErvY/s16000/Day6-Network-06Nov22-ChennaiTrafficSignals-3D.jpg" /></a></div><br /><div class="separator" style="clear: both;"><br /></div>
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Day 7: Raster<br />DEM Raster visualization of Mt Hoverla in Ukraine using MapnikRasterizer in FME from Safe Software
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<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg2_tBwjf9pk4oO0Q3JHdiq74ht0kvtadyS4-0TVZ7e6L3DiNuSOitI1NJOMkOcB7BOMT88oDWKnSzEiTqGHai2GD-zVU_Ws40o_pYfVXVmw9EGrhLZGj8lf41UXR6AZqzq0UBoH8eCTEQp-Zh9q8zjNZ22YTtcOs-BV-oWEbEc6P_dpK11z8g/s4094/Day7-07-Nov-22-Raster-MtHoverla-Ukraine4Post.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2159" data-original-width="4094" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg2_tBwjf9pk4oO0Q3JHdiq74ht0kvtadyS4-0TVZ7e6L3DiNuSOitI1NJOMkOcB7BOMT88oDWKnSzEiTqGHai2GD-zVU_Ws40o_pYfVXVmw9EGrhLZGj8lf41UXR6AZqzq0UBoH8eCTEQp-Zh9q8zjNZ22YTtcOs-BV-oWEbEc6P_dpK11z8g/s16000/Day7-07-Nov-22-Raster-MtHoverla-Ukraine4Post.png" /></a></div><br /><div class="separator" style="clear: both;"><br /></div>
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Day 8: Data: OSM<br />Restaurants in Chennai within 50m from certain OSM Highway types using MapnikRasterizer in FME from Safe Software</div><div>
<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhocBeABRyPIelmhea-Z95EQZfkOBFB1sz1vdkrfEjFWyIpjThUOqETdmmGpDuBnRkoCrr0Z5R70dYtix-abaHUl3UifeLRawVTFX1KiVYRolEHmV7jSIacZYiT70vXnAOQDnsFOiJZ27cc9_ItatyQh9BHW7ZfWB-0wYqEXbKEYv2IUTMpE1M/s1920/08nov22-OSM-Chennai_Restaurants-3D-4Post.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1080" data-original-width="1920" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhocBeABRyPIelmhea-Z95EQZfkOBFB1sz1vdkrfEjFWyIpjThUOqETdmmGpDuBnRkoCrr0Z5R70dYtix-abaHUl3UifeLRawVTFX1KiVYRolEHmV7jSIacZYiT70vXnAOQDnsFOiJZ27cc9_ItatyQh9BHW7ZfWB-0wYqEXbKEYv2IUTMpE1M/s16000/08nov22-OSM-Chennai_Restaurants-3D-4Post.png" /></a></div><div class="separator" style="clear: both;"><br /></div>
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Day 9: Space (space: a place or an area that is empty or not used)</div><div>Devon Island, Canada: The largest uninhabited island in the world</div><div>Visualization generated using FME from Safe Software
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<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj17MM4MdM_KNN96PddjzdYhQgrgtxVDr2JvGHQnqz1urCrfxojSv7N4cL1bquvOofWakxThOX7-jp-AOSsJqSi6-8IIOQQErmzE2SQWPL0Vph6MML1Fq4A8oI_i2g1nRRkUhf84iIf-ZttNJBLMVR4XrRwNWVHInGBt3zdMJRrt9D_76jPPpI/s3840/Day9-09Nov22-Space-DevonIsland4Post.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2160" data-original-width="3840" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj17MM4MdM_KNN96PddjzdYhQgrgtxVDr2JvGHQnqz1urCrfxojSv7N4cL1bquvOofWakxThOX7-jp-AOSsJqSi6-8IIOQQErmzE2SQWPL0Vph6MML1Fq4A8oI_i2g1nRRkUhf84iIf-ZttNJBLMVR4XrRwNWVHInGBt3zdMJRrt9D_76jPPpI/s16000/Day9-09Nov22-Space-DevonIsland4Post.png" /></a></div><div class="separator" style="clear: both;"><br /></div>
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Day 10: A Bad Map<br />
Top 5 Countries by Crime Rate (2022) using MapnikRasterizer in FME from Safe Software
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<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEicyoDa-O0JUMDbDeLDOIn_U07NMvdJ4FnNRQk-264Q6hMHcWY79WqQGvW7bUmLgwr_hWgBH1LIeMX0JuYQKMzw6GDMTEE90R3X2NXcyfyJ6WIewWCgOhTLkHInOvyyLwFMqPWULB2aasndv0CWfLw4oGlda3Xi41R1WnMTL9re-tVRhCtggS4/s3840/Day10-10Nov22-Bad-WorldCountriesCrimeIndex4Post.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2160" data-original-width="3840" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEicyoDa-O0JUMDbDeLDOIn_U07NMvdJ4FnNRQk-264Q6hMHcWY79WqQGvW7bUmLgwr_hWgBH1LIeMX0JuYQKMzw6GDMTEE90R3X2NXcyfyJ6WIewWCgOhTLkHInOvyyLwFMqPWULB2aasndv0CWfLw4oGlda3Xi41R1WnMTL9re-tVRhCtggS4/s16000/Day10-10Nov22-Bad-WorldCountriesCrimeIndex4Post.png" /></a></div><div class="separator" style="clear: both; text-align: justify;"><br /></div><div class="separator" style="clear: both; text-align: justify;">Another entry for <span style="text-align: center;">(An Intentionally) Bad Map</span></div><div class="separator" style="clear: both; text-align: justify;"><span style="text-align: center;">For some fun, World Map with Countries Offset Randomly in X & Y Direction from their Original Location using custom FME Workspace.</span></div><div class="separator" style="clear: both; text-align: justify;"><span style="text-align: center;">(Original position shown in black outline without fill)</span></div><div class="separator" style="clear: both; text-align: justify;"><span style="text-align: center;"><br /></span></div><div class="separator" style="clear: both; text-align: justify;"><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhJZ_jQajS_Qw1iZC9KuvOkn-bJBYZlf4mdZs9AJBlD96uSYOmem9hqScSqNOVfRW7MloRxYQLdfLhmg_l5_R9NgqUQUUaF8pyb33wL6UFJ8s_nngW0_9iEeWF5XR9U1fyu1TAFuaRtC53zPKLHTC73tZrwQpm11QUMYe-uch0MDGaUq3pESIY/s3840/Day10-10Nov22-IntentionallyBadMap_Offset4Post.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2160" data-original-width="3840" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhJZ_jQajS_Qw1iZC9KuvOkn-bJBYZlf4mdZs9AJBlD96uSYOmem9hqScSqNOVfRW7MloRxYQLdfLhmg_l5_R9NgqUQUUaF8pyb33wL6UFJ8s_nngW0_9iEeWF5XR9U1fyu1TAFuaRtC53zPKLHTC73tZrwQpm11QUMYe-uch0MDGaUq3pESIY/s16000/Day10-10Nov22-IntentionallyBadMap_Offset4Post.png" /></a></div><br /><span style="text-align: center;"><br /></span></div><br /><div class="separator" style="clear: both;"><br /></div>
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Day 11: Colour Friday: Red<div>Infant Mortality Rate >=10 per 1000 Live Births (2020)</div>
Map generated using MapnikRasterizer in FME from Safe Software<br />
<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg3GIsHRIRRLPNmj3o12BMU1kwA2jg5N4Z9dpJ4NIaBmoRCTIpDV8dDFthE_qHPSZMB_w_fH8gV-a9W1kG3lEbOLLo1QasbMeEO0YV0Qx9A_NedOxC8RNeFXqbsy02Qe2FkO05QXeLyOPDYJNoHMXE12WIyO2Nu2ugwI6dnovyyBskhp5YHYGc/s4096/Day11-11nov22-Red-InfantMortalityRate2020_4Post.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2160" data-original-width="4096" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg3GIsHRIRRLPNmj3o12BMU1kwA2jg5N4Z9dpJ4NIaBmoRCTIpDV8dDFthE_qHPSZMB_w_fH8gV-a9W1kG3lEbOLLo1QasbMeEO0YV0Qx9A_NedOxC8RNeFXqbsy02Qe2FkO05QXeLyOPDYJNoHMXE12WIyO2Nu2ugwI6dnovyyBskhp5YHYGc/s16000/Day11-11nov22-Red-InfantMortalityRate2020_4Post.png" /></a></div><br /><div class="separator" style="clear: both;"><br /></div>
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Day 12: Scale<br /><div>Map to Demonstrate the Significance of Scale</div><div>Africa Continent Administrative Boundaries at 1:10 million and 1:110 million Scale overlaid using FME from Safe Software</div>
Map generated using MapnikRasterizer in FME from Safe Software</div><div><br /></div><div>Boundaries in Red at 1:110 million scale (Small Scale=Less details)</div><div>Boundaries in Black at 1:10 million scale (Large Scale=More details) <br />
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Day 13:A 5 minute map<br /><div>Map to Demonstrate the Speed of Data Integration using FME from Safe Software with MapnikRasterizer and MapTextLabeller</div><div><br /></div><div>OpenStreetMap of Chennai with Road Names replaced with some formats supported by FME 2022</div>
Map generated using MapnikRasterizer in FME from Safe Software
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Day 14:Hexagons<br /><div>Our World in 112,269 Hexagons generated using FME from Safe Software and QGIS</div><div> </div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj8tSXdjMy5-dBpR24F2xhGindICyX9oHRBU0i2QW4oDMHUv3tkgTOIgD4khe1WAk3BYXx9IExvY_IRLCXJmk0j3y3UNVzSa3R5gOPaqSvvXQe2pdSKtFHirYN-6G3XuvMUQpiFfUwZNtSqJd0TMgR4UJnhQVR2r6ipNxBNnWP-q3Qt9b8wyPY/s7015/Day14-14nov22-Hexagons-WorldAsHexagonsByContinents.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="4960" data-original-width="7015" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj8tSXdjMy5-dBpR24F2xhGindICyX9oHRBU0i2QW4oDMHUv3tkgTOIgD4khe1WAk3BYXx9IExvY_IRLCXJmk0j3y3UNVzSa3R5gOPaqSvvXQe2pdSKtFHirYN-6G3XuvMUQpiFfUwZNtSqJd0TMgR4UJnhQVR2r6ipNxBNnWP-q3Qt9b8wyPY/s16000/Day14-14nov22-Hexagons-WorldAsHexagonsByContinents.png" /></a></div><br /><div class="separator" style="clear: both;"><br /></div>
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Day 15:Food/Drink<br /><div>National Food (Official/Unofficial) of some countries</div><div>Visualization generated using MapnikRasterizer in FME from Safe Software</div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiMKxeqzKgbsfSGecKx1N-3LIfu51MGGeFyqc9WHcuCwpS7f0ySpfwhBhXAvMxW8Z6MsUg8hYbk6PjMwujgPRJVNfBGHE73c5lAIcpXIMYu0xxfOV9MdNeIdoyaP9iMjH20ES3kt6vL2CmBK7Fj_Wj8Im2La4N9BAqmW02V6r-Mhn-q9L4lVEU/s4164/Day15-15nov22-Food_Drink-WorldCountriesDishes_4Post.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2196" data-original-width="4164" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiMKxeqzKgbsfSGecKx1N-3LIfu51MGGeFyqc9WHcuCwpS7f0ySpfwhBhXAvMxW8Z6MsUg8hYbk6PjMwujgPRJVNfBGHE73c5lAIcpXIMYu0xxfOV9MdNeIdoyaP9iMjH20ES3kt6vL2CmBK7Fj_Wj8Im2La4N9BAqmW02V6r-Mhn-q9L4lVEU/s16000/Day15-15nov22-Food_Drink-WorldCountriesDishes_4Post.png" /></a></div><div><br /></div><div><br /></div><hr />
Day 16: Minimal</div><div>The Republic of #Nauru (Pleasant Island), Smallest Island Nation<br />
Map generated using FME from Safe Software
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Day 17:Map without a computer<br /><div><br /></div><div>A hand drawn sketch map of the neighborhood of a die hard #FME fan, FME user, FME Certified Professional & Trainer, FME Server Certified Professional and FME Business Certified Professional</div>
<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiixCJFMOyWvS4_Fq86ES90XpEMKuQKHsL1mqgd-BKE982qIPZB-vtlrb7T99qNfY9L4MpWiTDJckr8rzfX72RnwGI_e1wBwqLWoT0bqct0NbG4g-lidktMy60t3twhXsnsfdxFznZ3wSY8p0PqenVN87iZr5CnwHj7JUx0OlKEo53-M_ngJj8/s3508/Day17-17Nov22-A-Map-Without-A-Computer-Abode-of-SaintGIS.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="3508" data-original-width="2480" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiixCJFMOyWvS4_Fq86ES90XpEMKuQKHsL1mqgd-BKE982qIPZB-vtlrb7T99qNfY9L4MpWiTDJckr8rzfX72RnwGI_e1wBwqLWoT0bqct0NbG4g-lidktMy60t3twhXsnsfdxFznZ3wSY8p0PqenVN87iZr5CnwHj7JUx0OlKEo53-M_ngJj8/s16000/Day17-17Nov22-A-Map-Without-A-Computer-Abode-of-SaintGIS.jpg" /></a></div><br /><div class="separator" style="clear: both;"><br /></div>
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Day 18: Colour Friday: Blue<div>Global Lakes (area ≥ 50 km2) and Reservoirs (storage capacity ≥ 0.5 km3) </div><div>Visualization generated using MapnikRasterizer in FME from Safe Software</div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg5eZO8dEYS33rU5FpUuTcZ5cySbgx7BX7C5Pj71ZP927J7b87jybkR-PUsPUTs9bBSDFjf7LrWZWQUHiRSX8euGyur_h_f97JTW63gc9_62dcdjA3vg1gdddyJsPiak9ayKvA6rN2o-aoAbIARKZIU95drxohweU5CrQJqth2fsvvHrtQvDzc/s3840/Day18-18Nov22-Blue-GlobalLakesReservoirs-WWF4Post.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2196" data-original-width="3840" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg5eZO8dEYS33rU5FpUuTcZ5cySbgx7BX7C5Pj71ZP927J7b87jybkR-PUsPUTs9bBSDFjf7LrWZWQUHiRSX8euGyur_h_f97JTW63gc9_62dcdjA3vg1gdddyJsPiak9ayKvA6rN2o-aoAbIARKZIU95drxohweU5CrQJqth2fsvvHrtQvDzc/s16000/Day18-18Nov22-Blue-GlobalLakesReservoirs-WWF4Post.png" /></a></div><br /><div><br /></div><hr />
Day 19:Globe<br /><div>Earth is not flat and that is why we have this completely FME from Safe Software</div><div>3D globe generated using Dmitri Bagh's (Safe Software) original workspace with changes</div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEghyVwibC5LmQXBtOWL_2zwWqWkpdiJcYF3lB-zauhm8JOvrImaR4HDSROZSiEGr4V86FCGcDKF8kqr0ouicJiYHPGcm-naoK6-fRySdAhGmVH0nN0fuPS_Hku-WtivLCfBcBxVFneISagvAZNa4B-w_QpF4wlp9Yw5TVbsRLMfHw1Gd7FiwWw/s2008/Day19-19Nov22-Globe.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1564" data-original-width="2008" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEghyVwibC5LmQXBtOWL_2zwWqWkpdiJcYF3lB-zauhm8JOvrImaR4HDSROZSiEGr4V86FCGcDKF8kqr0ouicJiYHPGcm-naoK6-fRySdAhGmVH0nN0fuPS_Hku-WtivLCfBcBxVFneISagvAZNa4B-w_QpF4wlp9Yw5TVbsRLMfHw1Gd7FiwWw/s16000/Day19-19Nov22-Globe.png" /></a></div><br /><div><br /></div>
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Day 20:My Favourite: Human Development Index (2022)</div><div><div>Human Development Index (2022) of some Countries</div>
Map generated using MapnikRasterizer in FME from Safe Software</div><div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhvxhLTc0TDpKigpzI3_ikpiv-ewjpjOTn_Y0j9pS8f70buQkp5sUzS4mw_THLcWE-dvUxk7dr4r-2ahdnpxNJgBTfJeLv1H267rFmEqMKUF5dBgbfToJmu6ktyXKnElmo6qIHUuUWCndYqQqj0fYuUozo09KkW5h7p2i5elO7dMTNFcTms00w/s3840/Day20-20nov22-my-favourite-hdi2022_4Post.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2196" data-original-width="3840" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhvxhLTc0TDpKigpzI3_ikpiv-ewjpjOTn_Y0j9pS8f70buQkp5sUzS4mw_THLcWE-dvUxk7dr4r-2ahdnpxNJgBTfJeLv1H267rFmEqMKUF5dBgbfToJmu6ktyXKnElmo6qIHUuUWCndYqQqj0fYuUozo09KkW5h7p2i5elO7dMTNFcTms00w/s16000/Day20-20nov22-my-favourite-hdi2022_4Post.png" /></a></div><br />
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Day 21:Data Kontur Population Dataset</div><div>(Global Population Density for 400m H3 Hexagons)</div><div><div><br /></div><div>400m hexagon grid with population >=5000 #TamilNadu #India</div><div>Hexagons in red means population >=5000</div><div>Map generated using MapnikRasterizer in FME from Safe Software</div>
<div class="separator" style="clear: both;"><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiUJZ54q3dQPC8jel0BUNxZXCJMgAZMmEbNxGGzJgsq26K00CGpB78uKIZ8rPgDTmaEITDx5ayVutUXJdxv66ZClKxJZtNDG86k33DI3i81zdH5_QzaXwWcC94Y3lDt3JZDLJd8vIL9iOUAHvsnI2XaSXLeo1BwPwjyT6O0PZVAme4deOh8tlo/s3840/21nov22-data-kontur-population-tamilnadu4post.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2196" data-original-width="3840" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiUJZ54q3dQPC8jel0BUNxZXCJMgAZMmEbNxGGzJgsq26K00CGpB78uKIZ8rPgDTmaEITDx5ayVutUXJdxv66ZClKxJZtNDG86k33DI3i81zdH5_QzaXwWcC94Y3lDt3JZDLJd8vIL9iOUAHvsnI2XaSXLeo1BwPwjyT6O0PZVAme4deOh8tlo/s16000/21nov22-data-kontur-population-tamilnadu4post.png" /></a></div><br /><div class="separator" style="clear: both;"><br /></div>
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Day 22:Null<br /><div>World Map using 82,922 "NULL" text string</div><div>Map generated using MapnikRasterizer in FME from Safe Software</div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgQmFQiRwZtDlyAy7wFtiFozARFwqi9R8WxaRByojS_cXNe2xxZmdW-CuYGV5lcUvmRg2J0K_4hjVEGC-CpOQU4fCU5RbpHO97jWx5dVXJrFPYYO_SwRbOpA3BQ3JC5HI-S51RMmIlWIU0QSgEU7y5x8xHw35USR1qpxf5gsZQKFDZE9a354-g/s3840/Day22-22nov22-null-world-in-null4post.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2196" data-original-width="3840" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgQmFQiRwZtDlyAy7wFtiFozARFwqi9R8WxaRByojS_cXNe2xxZmdW-CuYGV5lcUvmRg2J0K_4hjVEGC-CpOQU4fCU5RbpHO97jWx5dVXJrFPYYO_SwRbOpA3BQ3JC5HI-S51RMmIlWIU0QSgEU7y5x8xHw35USR1qpxf5gsZQKFDZE9a354-g/s16000/Day22-22nov22-null-world-in-null4post.png" /></a></div><div><br /></div>
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Day 23:Movement<div>Traffic Index of some Countries (2022)</div>
Map generated using MapnikRasterizer in FME from Safe Software</div><div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg5adnU77QmgNTiutIRZVmYu8wC8HE-h6vwyfJeruzLkQ6FMvIV9Hs1Hie6r32dfHUz0g5CRVTYUi_prQz6dKbItySgXXIbUn6Xi24SSMJVcyCPau52xN7trrR8P6aAyMXSzw4ZseQieUrtL8Z54lMUMitkmUET6jKQTQcHBatKsn2VvoHyya8/s3840/Day23-23nov22-movement-traffic_index-2022-4Post.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2196" data-original-width="3840" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg5adnU77QmgNTiutIRZVmYu8wC8HE-h6vwyfJeruzLkQ6FMvIV9Hs1Hie6r32dfHUz0g5CRVTYUi_prQz6dKbItySgXXIbUn6Xi24SSMJVcyCPau52xN7trrR8P6aAyMXSzw4ZseQieUrtL8Z54lMUMitkmUET6jKQTQcHBatKsn2VvoHyya8/s16000/Day23-23nov22-movement-traffic_index-2022-4Post.png" /></a></div><br />
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Day 24:Fantasy</div><div><div>The Fantasy World of FME Lizards and FME Zipsters FME Lizard</div><div><br /></div><div>Fantasy map completely generated using MapnikRasterizer in FME from Safe Software</div><div><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjfiAtOF2QxaLFDZWgART6toh8xemeGRrIIzTeA4R5aF6mt-DOv670hQVLRVwHpiHiwgpLK-VY85H-7JCmRiYTxGZrczogW9MWxTo4JlWdnI5d8lwsAQFgfKToN-eyCYfaSHCWt8AJL_g4qgQA5HU0Ff5jGuV0xn82AmyJp68IrvurNtpM8Hrk/s3840/Day24-24nov22-fantasy4post.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2196" data-original-width="3840" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjfiAtOF2QxaLFDZWgART6toh8xemeGRrIIzTeA4R5aF6mt-DOv670hQVLRVwHpiHiwgpLK-VY85H-7JCmRiYTxGZrczogW9MWxTo4JlWdnI5d8lwsAQFgfKToN-eyCYfaSHCWt8AJL_g4qgQA5HU0Ff5jGuV0xn82AmyJp68IrvurNtpM8Hrk/s16000/Day24-24nov22-fantasy4post.png" /></a></div><div><br /></div>
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Day 25:Colour Friday-2 Colours<br />Some countries with bicolour flag Day 26:Choropleth
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Worldwide Estimated Cancer Deaths (2020)
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Map generated using MapnikRasterizer in FME from Safe Software</div><div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgYNot6QBHWJfoRpj9a6z4y6eC-PxZSKtuXXiSWUS3T80GvGannZSBIcJesGPxoVImw5FKRBHQaqG3uGOSmeCXQWSnb6p9681mtMKULWhikTHw0a7OYb4ym03LIyhXx6m1GyELeCPhNxD6YkRPyq77UbAHgTyvC4gH6gZ7w_XOxo7uLcD3cpvQ/s3840/Day25-25nov22-color-friday-two-colors-bicolor-flag-countries4Post.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2196" data-original-width="3840" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgYNot6QBHWJfoRpj9a6z4y6eC-PxZSKtuXXiSWUS3T80GvGannZSBIcJesGPxoVImw5FKRBHQaqG3uGOSmeCXQWSnb6p9681mtMKULWhikTHw0a7OYb4ym03LIyhXx6m1GyELeCPhNxD6YkRPyq77UbAHgTyvC4gH6gZ7w_XOxo7uLcD3cpvQ/s16000/Day25-25nov22-color-friday-two-colors-bicolor-flag-countries4Post.png" /></a></div><br /> <hr />
Day 26:Island(s)<div>Flevopolder, The Netherlands</div><div>Largest man-made island</div><div>Map generated using MapnikRasterizer in FME from Safe Software</div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhFvl29zz3oT-BLfLdCFHBNDJB1E5S12FgdIzpYQg4LVOF-2GhXjk9aydxnqNW0YhFDB5WeYPple3X0j14HWTZno9BX4Rn4UOBaM0PsuE633_rLCvUESiAZAUEj7-vQ5lDROdCUGPOsO47lP1W8Ip1zA_wPgnxY778UJ89kINfQNqJNFvRgTBs/s3840/Day26-26Nov22-Islands-Flevopolder4Post.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2196" data-original-width="3840" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhFvl29zz3oT-BLfLdCFHBNDJB1E5S12FgdIzpYQg4LVOF-2GhXjk9aydxnqNW0YhFDB5WeYPple3X0j14HWTZno9BX4Rn4UOBaM0PsuE633_rLCvUESiAZAUEj7-vQ5lDROdCUGPOsO47lP1W8Ip1zA_wPgnxY778UJ89kINfQNqJNFvRgTBs/s16000/Day26-26Nov22-Islands-Flevopolder4Post.png" /></a></div><div><br /></div>
<hr />Day 27:Music<br /><div>National Music Instruments of Some Countries</div><div>(Official & Unofficial)</div>Map generated using MapnikRasterizer in FME from Safe Software<br /><br /></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhfyjHihk1kDqCFtGMRX7SU6nAZHeL-j0qFvAt_mjLuPUC27vP3cNVZyus0SNmrmOYWHZn3wad03G87vecBJzJUgCVrYEXvLse2VSK_iwZRt_8gGwwvdYUc3ejFSp10M2eqxpuispd_ClEuDA5ddiiJIRIOyIDw4BPdsjMCiFk_hJy_LYkR464/s3840/Day27-27nov22-music-national-instruments-of-countries4post.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2196" data-original-width="3840" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhfyjHihk1kDqCFtGMRX7SU6nAZHeL-j0qFvAt_mjLuPUC27vP3cNVZyus0SNmrmOYWHZn3wad03G87vecBJzJUgCVrYEXvLse2VSK_iwZRt_8gGwwvdYUc3ejFSp10M2eqxpuispd_ClEuDA5ddiiJIRIOyIDw4BPdsjMCiFk_hJy_LYkR464/s16000/Day27-27nov22-music-national-instruments-of-countries4post.png" /></a></div><br /><div><br /></div><div><hr /></div><div>Day 28:3D</div><div>3D view of Kotagiri in The Nilgiris, India</div><div><div>3D Map generated using #FME from Safe Software</div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiaf-maEQiGUsVoMjGCJSxtnjbsQEl5TLsLPiF0og1gKudilGGkjYaNFhX79DEOXlPoBa9KAFbuT9d9BQ5DPtfJ76qexYiGiJ6WEqunZGI9eIixbLiADlbJ-3qN-g6K14LMIyvo1fMH_uQc9mAMTOjlMeGuDziqJyRsS2SJrgGc67Am46f1Eb4/s3840/Day28-28Nov22-3D-Kotagiri4Post.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2160" data-original-width="3840" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiaf-maEQiGUsVoMjGCJSxtnjbsQEl5TLsLPiF0og1gKudilGGkjYaNFhX79DEOXlPoBa9KAFbuT9d9BQ5DPtfJ76qexYiGiJ6WEqunZGI9eIixbLiADlbJ-3qN-g6K14LMIyvo1fMH_uQc9mAMTOjlMeGuDziqJyRsS2SJrgGc67Am46f1Eb4/s16000/Day28-28Nov22-3D-Kotagiri4Post.png" /></a></div><br /><div><br /></div>
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Day 29:Out of my comfort zone<div>Life Expectancy at Birth in Years (2019) for some Countries</div><div>Visualization using Qlik Sense Desktop from <a href="https://www.qlik.com/" target="_blank">Qlik</a></div><div>Data loading and data preparation using FME from Safe Software</div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEilyvzPftFCofE-I7m9aygjXqCzavV94iUArVDKLEoEt4HcKSEuznhRjOBr6Uvb8yE7CYjKIp638M3ybs0KaaT72a25J1OLt5041GqJcQzGr6W5uuDE9vq4MO-9oMNTMx6R322dW7V8n2Y7nmbJQnawAS9mmFfA5QTI2Cu_8QqNMRIc22Udoa8/s3840/29nov22-out-of-my-comfort-zone-qlik-life%C4%93xpectancy%C4%81t-birth-2019.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2160" data-original-width="3840" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEilyvzPftFCofE-I7m9aygjXqCzavV94iUArVDKLEoEt4HcKSEuznhRjOBr6Uvb8yE7CYjKIp638M3ybs0KaaT72a25J1OLt5041GqJcQzGr6W5uuDE9vq4MO-9oMNTMx6R322dW7V8n2Y7nmbJQnawAS9mmFfA5QTI2Cu_8QqNMRIc22Udoa8/s16000/29nov22-out-of-my-comfort-zone-qlik-life%C4%93xpectancy%C4%81t-birth-2019.png" /></a></div><br /><div><br /></div><div><br /></div><hr />
Day 30: Remix</div><div><div>A newer versionof a map that I had done during the #30DayMapChallenge 2022 or a map done by someone else and do your own version.I wanted to post on the dangers of climate change on atleast one of the #30DayMapChallenge days.</div><div>I was planning to do a 3D on Day 28 using #MapnikRasterizer</div><div>But finally got to do it on Day 30:Remix</div><div>Kind of 3D visualization effect using MapnikRasterizer in FME from Safe Software</div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi-E1V7KRoD-2AJ35IqOosPJYvLjqTjcgZcBbXKIMmcOtuHz2XVJO3uwiyCkPXg9qaEZNp7oOg7kw7C_kFV3R3ksjyw_0_9h6rCrXxm4e0dUL_p35pTBcEYiVhaS9ubuBg254Gzx1msEkWv6rwgoyxW6sN69_2rNDNdeZPHFsXsRkEd8FVDIFQ/s3840/Day30-30nov22-remix-climate-risk-index-3d-4post.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2196" data-original-width="3840" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi-E1V7KRoD-2AJ35IqOosPJYvLjqTjcgZcBbXKIMmcOtuHz2XVJO3uwiyCkPXg9qaEZNp7oOg7kw7C_kFV3R3ksjyw_0_9h6rCrXxm4e0dUL_p35pTBcEYiVhaS9ubuBg254Gzx1msEkWv6rwgoyxW6sN69_2rNDNdeZPHFsXsRkEd8FVDIFQ/s16000/Day30-30nov22-remix-climate-risk-index-3d-4post.png" /></a></div><br /><div><br /></div><hr />
<br />It may be 30 days of gruelling, brainstorming; putting all your learning and experience into practice or self test
To me, the whole idea of participating and contributing to #30DayMapChallenge 2022 is about promoting #GIS<br />
But then the satisfaction in having contributed to promotion of GIS outweighs everything else!
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<b>GIS Temper, Let us not lose it!</b>
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I take this opportunity to thank all those who contributed in some way or the other, to my career and to what I am today in the field of GIS!
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Thanks to Safe Software for such a wonderful product/platform "FME" that helped me to convert,transform,share and integrate data from multi-farious sources and types, not just for this #30DayMapChallenge 2022, but for the last 22 years of my career in GIS
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Last but not the least, special thanks to my family (my wife and son) for all the patience, understanding and support, while I meticulously worked on the submission every day!
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More information about Topi Tjukanov (#30DayMapChallenge conceptualizer)
https://medium.com/@tjukanov
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https://twitter.com/tjukanov</div>Saint GIShttp://www.blogger.com/profile/03296153994051314633noreply@blogger.com0tag:blogger.com,1999:blog-7854142.post-82506957872670321072021-11-29T03:58:00.002-08:002021-11-29T03:58:52.062-08:00Thirty Days of Mapping (FME-ing) #30DayMapChallenge 2021<a href="https://tjukanov.org/" target="_blank">Topi Tjukanov</a> of Finland launched the #30DayMapChallenge in 2019 where hundreds of maps were made and shared on social media using the
#30DayMapChallenge hashtag. Each days presents a map challenge focused on a different spatial feature or topic.
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The topics for #30dayMapChallenge 2021 were:
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href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjbD2NOISkf-NbNpfo-adDRbdt9P_Pi1rYJ0GU-hGEWkZU-gQckILGg9PFeCAD-xaf-qo2Z6ndLaYRli5qtkUVrJ5AtIYvp-RQznOoaze7vQpEf_Fq_lcFU8hc6I9F-u8XudpvkFQ/s0/30day-map-challenge-categories-daywise.png"
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As a die hard user of FME from (<a href="https://www.safe.com" target="_blank">Safe Software</a>),what could be a better opportunity to put my FME skills to test!
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This post is a collection of all entries for #30DayMapChallenge 2021 by @Saint_GIS, most of which have been accomplished only using FME and in few cases, due to the nature of the challenge, the data prepared using FME.
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Happy FME-ing :-) reading my #30DayMapChallenge 2021 entries!
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Day 1: Points
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First entry for the #30DayMapChallenge 2021- 101 Random Points generated using FME from Safe Software
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href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjZ2yf_mTDuybWQ6YzfhwYsp398Eivwlt7zM5DYZ6-IPts4oLRVDJA6gnT2DWfkUxhwa0EQ9rNC6WcjNmSkCJZqMOyBGD57CRLe16jxfHHwZ9b9UFzGBk7y4MFsz8XsDosTYP1bqg/s0/Day1-Points-01Nov21.png"
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Another entry for Day 1 Points-Some places (Points) with population more than 1.5 million generated using FME from Safe Software
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<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhO_osxg0H8yPhZjebwFrOuNAVyrCKgWRG_4Fsdfr_AbaUkgXbGTuXSdA4WMOi_wyq1pBPDg197c1OnfjzMzpfY965OoRj43eACdfDGodxLfm_pLRwZbUFQOUbAATAZXNKtQ7C-mw/s0/Day1-Points-01Nov21-SomePlaces1.5MillionPopulation.png" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" data-original-height="768" data-original-width="1474" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhO_osxg0H8yPhZjebwFrOuNAVyrCKgWRG_4Fsdfr_AbaUkgXbGTuXSdA4WMOi_wyq1pBPDg197c1OnfjzMzpfY965OoRj43eACdfDGodxLfm_pLRwZbUFQOUbAATAZXNKtQ7C-mw/s0/Day1-Points-01Nov21-SomePlaces1.5MillionPopulation.png"/></a></div>
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Day 2: Lines
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NH548: Shortest National Highways in India (Length 5Km (3 miles)
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Data prepared using FME from Safe Software
<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhYLOVJmywddwVfET91voCaJGMbAOUzbKyrSXryczDI2yjFVlrfTRrJvtU9vSjaWraEk1s6C0m8GAJN8NpnY4-G2tdVwHH5R63ByPQ0L6T6RanBvnLeiAiGf28QVJrSBSOs7mgBUQ/s0/Day2-Lines-02Nov21-ShortestHighwayIndia_NH548.png" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" data-original-height="768" data-original-width="1474" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhYLOVJmywddwVfET91voCaJGMbAOUzbKyrSXryczDI2yjFVlrfTRrJvtU9vSjaWraEk1s6C0m8GAJN8NpnY4-G2tdVwHH5R63ByPQ0L6T6RanBvnLeiAiGf28QVJrSBSOs7mgBUQ/s0/Day2-Lines-02Nov21-ShortestHighwayIndia_NH548.png"/></a></div>
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Day 3: Polygons
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World Countries by Sovereignty (Sovereignty represented through Concave Hull Polygons) using FME from Safe Software
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<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjlVV4PPP5aMwo-miYImUIRQJTR6YjOmiOxwD8hyphenhyphenXvGf1r-k5N5DY3IlurPJOOzUsofLPzpNzEEdtdKcMckKVg5CPASpQcoa13abd_LuaoMl_ET7mbSMuwTUWJUKdi6GTWMbEIQEA/s0/Day3_Polygons-WorldCountriesBySovereignty_ConcaveHullPolygons.png" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" data-original-height="2048" data-original-width="1448" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjlVV4PPP5aMwo-miYImUIRQJTR6YjOmiOxwD8hyphenhyphenXvGf1r-k5N5DY3IlurPJOOzUsofLPzpNzEEdtdKcMckKVg5CPASpQcoa13abd_LuaoMl_ET7mbSMuwTUWJUKdi6GTWMbEIQEA/s0/Day3_Polygons-WorldCountriesBySovereignty_ConcaveHullPolygons.png"/></a></div>
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Day 4: Hexagons
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Our World as Hexagons using FME from Safe Software
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<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj8ZonJyBmqOJq1Y0CEiZcypsOkEVJ_jNx_5t8Cq7z1lGEHD0bLkFwt2jzVYhUgp_P6-od53PfUeQdX5TPhdNSsMTC65MTp2hT7h0vuCr8WGnwDjSwv1YXAu55mb2AkxUwvkDGM6A/s0/Day4_OurWorld-as-Hexagons.png" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" data-original-height="1448" data-original-width="2048" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj8ZonJyBmqOJq1Y0CEiZcypsOkEVJ_jNx_5t8Cq7z1lGEHD0bLkFwt2jzVYhUgp_P6-od53PfUeQdX5TPhdNSsMTC65MTp2hT7h0vuCr8WGnwDjSwv1YXAu55mb2AkxUwvkDGM6A/s0/Day4_OurWorld-as-Hexagons.png"/></a></div>
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Day 5: Data challenge 1: OpenStreetMap
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OpenStreetMap extract for a part of Chennai City rendered using MapnikRasterizer in FME from Safe Software
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<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjX69aLBb05JualnnjMC6zHvj23Vg2gYHmOn2_IW73VwXBO-I8-8ckrWeld5abhRj9jqHmBUF_2Km_gv9tlh1s9uOv68eIB76YkaQuaRkCgnJWXpZWrYfe_Soyiq26W9J5_DBqJYw/s0/Day5-DataChallenge1-OSM-ChennaiMapnikRasterizer.png" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" data-original-height="2048" data-original-width="1557" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjX69aLBb05JualnnjMC6zHvj23Vg2gYHmOn2_IW73VwXBO-I8-8ckrWeld5abhRj9jqHmBUF_2Km_gv9tlh1s9uOv68eIB76YkaQuaRkCgnJWXpZWrYfe_Soyiq26W9J5_DBqJYw/s0/Day5-DataChallenge1-OSM-ChennaiMapnikRasterizer.png"/></a></div>
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Day 6: Red
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Infant Mortality Rate per 1000 Live Births (2018) rendered using MapnikRasterizer in FME from Safe Software
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<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh3VsDorxhkkiZ0_P2R7LiyZNvaqgbu1ws71NSYlnZFhGJs2uG_piB8g0rgDOH7v_ykhdSPBbfB43TJN5PAQOQg0My2SA_yG2Em2j6EORrU8gkgkpIuCpdKvv-ivcxN4S9molEbgA/s0/InfantMortalityRate10-or-more-per1000LiveBirths4Post.png" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" data-original-height="1080" data-original-width="2048" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh3VsDorxhkkiZ0_P2R7LiyZNvaqgbu1ws71NSYlnZFhGJs2uG_piB8g0rgDOH7v_ykhdSPBbfB43TJN5PAQOQg0My2SA_yG2Em2j6EORrU8gkgkpIuCpdKvv-ivcxN4S9molEbgA/s0/InfantMortalityRate10-or-more-per1000LiveBirths4Post.png"/></a></div>
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Day 7: Green
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Map of National Trees of Some Countries rendered using MapnikRasterizer in FME from Safe Software
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<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiUbr_1ve2D2P5hQ_GWOzgY0OWG8BakE_29yDhSs_BlhdFT7lG2ZQ9irP7cOg2e1p62YigcDDwe_HoRneXDJFGqqkAWlFDeWfPjsWGR3DTQh11eVkYZt51qDIapmXDYcQispELBiw/s0/Day7-Green-WorldCountriesNationalTrees4Post.png" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" data-original-height="1080" data-original-width="2048" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiUbr_1ve2D2P5hQ_GWOzgY0OWG8BakE_29yDhSs_BlhdFT7lG2ZQ9irP7cOg2e1p62YigcDDwe_HoRneXDJFGqqkAWlFDeWfPjsWGR3DTQh11eVkYZt51qDIapmXDYcQispELBiw/s0/Day7-Green-WorldCountriesNationalTrees4Post.png"/></a></div>
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Day 8: Blue
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Global Lakes (area ≥ 50 km2) and Reservoirs (storage capacity ≥ 0.5 km3) rendered using MapnikRasterizer in FME from Safe Software
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<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjVvOIVx3QQ0n3no39uaDkvEHfW9HD1cpWx9dZp1Jb0XLIAXMUoYTPgqg-MXNlqzjBHiwGz-D2Pw8tshbwmOUNNWvUXgfB892W-2_0pjodCwvPlGKZG4dTvGkmCpRaDYzLjJezGKg/s0/Day8-08Nov21-Blue-GlobalLakesReservoirs-WWF.png" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" data-original-height="1325" data-original-width="2048" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjVvOIVx3QQ0n3no39uaDkvEHfW9HD1cpWx9dZp1Jb0XLIAXMUoYTPgqg-MXNlqzjBHiwGz-D2Pw8tshbwmOUNNWvUXgfB892W-2_0pjodCwvPlGKZG4dTvGkmCpRaDYzLjJezGKg/s0/Day8-08Nov21-Blue-GlobalLakesReservoirs-WWF.png"/></a></div>
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Day 9: Monochrome
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OpenStreetMap extract for a part of #Chennai City rendered in Monochrome using MapnikRasterizer in FME from Safe Software
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<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiuX7-N9jIqT-NO-w8xlierDtT8icO3a5oVOQlGrVQIytKqdFzr0GdlBKgVDifT7hyaRyW-VXXMMddPli91PkmteQC1rOEsdBXv-neISex_GEUJAmjdrDJY6DrsIYjeh_R_ilnq2g/s0/Day9-Monochrome-OSM-ChennaiExtractMapnikRasterizerFME-Monochrome.png" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" data-original-height="2048" data-original-width="1549" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiuX7-N9jIqT-NO-w8xlierDtT8icO3a5oVOQlGrVQIytKqdFzr0GdlBKgVDifT7hyaRyW-VXXMMddPli91PkmteQC1rOEsdBXv-neISex_GEUJAmjdrDJY6DrsIYjeh_R_ilnq2g/s0/Day9-Monochrome-OSM-ChennaiExtractMapnikRasterizerFME-Monochrome.png"/></a></div>
<hr>
Day 10: Raster
<br>
World Map with Flags of Countries as Collage using MapnikRasterizer in FME from Safe Software
<br>
<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjedqYK_8EvfqrRSvgUSJXs_gqzs4rzwuZuhWMY6G5lXbEuDxu397KsWVlb_K-2Uk36vJmUDuSI8bsqX_5aS0CcGOu7pKT_vfBj-mNLCW64FjYnfmZtsmmMNeA6uYnd1K7-vP6IAA/s0/Day10-10Nov21-Raster-WorldFlagsCollage.png" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" data-original-height="1325" data-original-width="2048" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjedqYK_8EvfqrRSvgUSJXs_gqzs4rzwuZuhWMY6G5lXbEuDxu397KsWVlb_K-2Uk36vJmUDuSI8bsqX_5aS0CcGOu7pKT_vfBj-mNLCW64FjYnfmZtsmmMNeA6uYnd1K7-vP6IAA/s0/Day10-10Nov21-Raster-WorldFlagsCollage.png"/></a></div>
<hr>
Day 11: 3D
<br>
3D of Tirumala and environs
<br>
https://en.wikipedia.org/wiki/Tirumala
<br>
Coordinates: 13.680916°N 79.350600°E
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Map generated using FME from SafeSoftware and visualized using Google Earth
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<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEimg_CbN3AAnIB7Cv9yIf_xBoUnMizrkPRDW04SAOCkr1Tv3hg4AtibCeuWR6kz25XGqPmQMe5SdPQ3uQZGPSK1QbEw80pLUL1u1s6hdxohrzWCfSeN_duMRNsdvmQX5sT1UBaL5g/s0/Day11-11Nov21-3D-Tirumala.png" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" data-original-height="1640" data-original-width="2048" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEimg_CbN3AAnIB7Cv9yIf_xBoUnMizrkPRDW04SAOCkr1Tv3hg4AtibCeuWR6kz25XGqPmQMe5SdPQ3uQZGPSK1QbEw80pLUL1u1s6hdxohrzWCfSeN_duMRNsdvmQX5sT1UBaL5g/s0/Day11-11Nov21-3D-Tirumala.png"/></a></div>
<hr>
Day 12: Population
<br>
Population Density (2020) of World Countries
<br>
Map generated using MapnikRasterizer in FME from Safe Software
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<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiGoejLH0BB61Zv-MY1QSU20hyvKLt89Cjnl52xQt6vPg-bqs2GcdLMtt2HocLnEQ8Go9Zt-ilx9LrvMZOsW4fCSQuASnt93FLBMaFuFtBbSS0dZNrnmBwSrMXXfqDNevPiQJO5Zw/s0/Day12-12Nov21-PopulationPPD-Final.png" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" data-original-height="1080" data-original-width="2048" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiGoejLH0BB61Zv-MY1QSU20hyvKLt89Cjnl52xQt6vPg-bqs2GcdLMtt2HocLnEQ8Go9Zt-ilx9LrvMZOsW4fCSQuASnt93FLBMaFuFtBbSS0dZNrnmBwSrMXXfqDNevPiQJO5Zw/s0/Day12-12Nov21-PopulationPPD-Final.png"/></a></div>
<hr>
Day 13:Data Challenge 2: Natural Earth
<br>
World Countries Color Coded by Time Zone (UTC Offset)
<br>
Map generated using MapnikRasterizer in FME from Safe Software
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<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhieZLVlWmdFcpvZDxRJCFotiRus4YJCueeFoINYw9k720aHOb2OtGI9v85Hojx6ijZ8iOCG6C7TbI-SA-FYro7OKYqyTYoaRSQ_dwIn8ZAvhiBqaqCLGSyP_-KqSKG4ZB1IIKqxA/s0/Day13-13Nov21-DataChallenge2-NaturalEarthTimeZone-Final.png" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" data-original-height="1080" data-original-width="2048" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhieZLVlWmdFcpvZDxRJCFotiRus4YJCueeFoINYw9k720aHOb2OtGI9v85Hojx6ijZ8iOCG6C7TbI-SA-FYro7OKYqyTYoaRSQ_dwIn8ZAvhiBqaqCLGSyP_-KqSKG4ZB1IIKqxA/s0/Day13-13Nov21-DataChallenge2-NaturalEarthTimeZone-Final.png"/></a></div>
<hr>
Day 14:New Tool
<br>
World Countries in 62,004 points Color Coded by Continent using <a href="https://kepler.gl/" target="_blank">Kepler.gl</a>
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Point data generated using FME from Safe Software
<br>
<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhiLmxJ7AvLDGvK3MtwgzVRZcXda6kU3v6-OtfpOpp5nv9giyQxnjAMa5Lyrt3g6_ELTw10grvBqmHxo9hym7O1_8Vws8JNqMl1EmtR7tSU3Bdozm3woLWdtFfpRh4_ulgL2BR3qw/s0/Day14-14Nov21-NewToolKeplerWorldCountriesinPoints.png" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" data-original-height="1080" data-original-width="1825" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhiLmxJ7AvLDGvK3MtwgzVRZcXda6kU3v6-OtfpOpp5nv9giyQxnjAMa5Lyrt3g6_ELTw10grvBqmHxo9hym7O1_8Vws8JNqMl1EmtR7tSU3Bdozm3woLWdtFfpRh4_ulgL2BR3qw/s0/Day14-14Nov21-NewToolKeplerWorldCountriesinPoints.png"/></a></div><div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiHFL1MpiAXAGrL7H9l3dGfavojKC1-6-CreD47nuVswpkK3xQCX0dj9SkDaKGOQY_3MfmHzk-lEeFpV0PxKiSlYgjBP767W3Y2YdG5591TGs7SrWaDqvzvYk2WHuUOA37X3Jr_fQ/s0/Day14-14Nov21-NewToolKeplerZoomIn.png" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" data-original-height="1075" data-original-width="1848" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiHFL1MpiAXAGrL7H9l3dGfavojKC1-6-CreD47nuVswpkK3xQCX0dj9SkDaKGOQY_3MfmHzk-lEeFpV0PxKiSlYgjBP767W3Y2YdG5591TGs7SrWaDqvzvYk2WHuUOA37X3Jr_fQ/s0/Day14-14Nov21-NewToolKeplerZoomIn.png"/></a></div>
<hr>
Day 15:Map made without using a computer
<br>
Inspired by my endless love for FME from Safe Software and my favourite entry
<br>
Map of the City of FME data expressways, XML park formats lake, data mountains, data type buildings and the lovely FME Central!
<br>
<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjVlQmoouTFtKKSJUIo1E0OATmW0PpUaCxxW_fv14MPZNBQpnF4z7eJyjHAvAB5Kesg2_01fVpP7nMB6610l1p18SCYxYzF31SdIg5bgkSjn88wlGiZcWtjlvVz51EJVbQwYtHTPQ/s0/Day15-15Nov21-MapWithoutComputer-City-of-FME.jpg" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" data-original-height="1448" data-original-width="2048" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjVlQmoouTFtKKSJUIo1E0OATmW0PpUaCxxW_fv14MPZNBQpnF4z7eJyjHAvAB5Kesg2_01fVpP7nMB6610l1p18SCYxYzF31SdIg5bgkSjn88wlGiZcWtjlvVz51EJVbQwYtHTPQ/s0/Day15-15Nov21-MapWithoutComputer-City-of-FME.jpg"/></a></div>
<hr>
Day 16: Urban/Rural
World Countries with Urban Population >=75% of its total population (2018)
<br>
Map generated using MapnikRasterizer in FME from Safe Software
<br>
<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhUiKsfrCD4sthAT1yat-g0LhOzoDahJwuembFjBwNexRqAway3Kv7enGgtfrM0fSHNDKxgMqDNaisP9BIEro8HRH2N2vYsGy1yrMxcZL8wZoC97tNPewu6LTBCK2CMDp6pEjH9UQ/s0/Day16-16Nov21-Urbanization-Final.png" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" data-original-height="1080" data-original-width="2048" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhUiKsfrCD4sthAT1yat-g0LhOzoDahJwuembFjBwNexRqAway3Kv7enGgtfrM0fSHNDKxgMqDNaisP9BIEro8HRH2N2vYsGy1yrMxcZL8wZoC97tNPewu6LTBCK2CMDp6pEjH9UQ/s0/Day16-16Nov21-Urbanization-Final.png"/></a></div>
<hr>
Day 17:Land
<br>
Largest Countries in the World (by area)
<br>
Land Area more than or equal to 1% of World Land Mass
<br>
Map generated using MapnikRasterizer in FME from Safe Software
<br>
<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjAZeHleDDVYssDQP-x5ljd9KBlm08orVBs2hAfzC_U0273vdWmGByVSOM5awfn1cLCycmIfR8WYYwxPnL-uEOQBh-PUgP_xgRCh82ebA1_5wMmdsXiVWI0iGJ_tD8KThqTp4DcCQ/s0/Day17-17Nov21-LargestLandAreaCountries-Final.png" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" data-original-height="1080" data-original-width="2048" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjAZeHleDDVYssDQP-x5ljd9KBlm08orVBs2hAfzC_U0273vdWmGByVSOM5awfn1cLCycmIfR8WYYwxPnL-uEOQBh-PUgP_xgRCh82ebA1_5wMmdsXiVWI0iGJ_tD8KThqTp4DcCQ/s0/Day17-17Nov21-LargestLandAreaCountries-Final.png"/></a></div>
<hr>
Day 18:Water
<br>
World Countries and their Water Stress (2018)
<br>
Some Countries with Water Stress >=100%
<br>
Map generated using MapnikRasterizer in FME from Safe Software
<br>
<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiTHvLeCH8ZW0GKUjcs9gnxLiS94LLEYBtKnpEYdMyV3xOS1pse0aA6Ap57Ywv7NpxclmlN44fz75CWB01ZtPcqWOI9s2SwRxgGXRhcBPkAOHDvjee2QKIZp6_w6HvsHwv9tuMCoQ/s0/Day18-18Nov21-WaterStress-Final.png" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" data-original-height="1080" data-original-width="2048" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiTHvLeCH8ZW0GKUjcs9gnxLiS94LLEYBtKnpEYdMyV3xOS1pse0aA6Ap57Ywv7NpxclmlN44fz75CWB01ZtPcqWOI9s2SwRxgGXRhcBPkAOHDvjee2QKIZp6_w6HvsHwv9tuMCoQ/s0/Day18-18Nov21-WaterStress-Final.png"/></a></div>
<hr>
Day 19:Islands
<br>
Andrott and Bitra Islands,Lakshadweep,India
<br>
Map generated using MapnikRasterizer in FME from Safe Software
<br>
<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjkjWC_ZsdoSFmDDNJPPDqrRAXr5Fcwkb8jd9XQtoew5rl6jA2NmcDPoruF6wAbvdJArXSP3POGiPSh9VxjVXCDM_TC3CBBSG1xFnm3B8IeCdrhN3Y-r69T-CNYgz6OM6Ki6DkDog/s0/Day19-19Nov21-Islands%25C4%2580ndrottBitra-Final.png" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" data-original-height="1080" data-original-width="2048" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjkjWC_ZsdoSFmDDNJPPDqrRAXr5Fcwkb8jd9XQtoew5rl6jA2NmcDPoruF6wAbvdJArXSP3POGiPSh9VxjVXCDM_TC3CBBSG1xFnm3B8IeCdrhN3Y-r69T-CNYgz6OM6Ki6DkDog/s0/Day19-19Nov21-Islands%25C4%2580ndrottBitra-Final.png"/></a></div>
<hr>
Day 20:Movement
<br>
Traffic Index by Country (2020)
<br>
Map generated using MapnikRasterizer in FME from Safe Software
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<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEju4t7ynrjxcbTEOJxeLu2XBBCsgtUiQfRKc7Woh_s8pb4biOQM5Xd5PkKaCeGNAPlzIn6qoPsTWsmJ8Cdiw2Q4zugdkIeKNJk4n2N7LWuLCXJLBMYi3aA1LLbhbINM0t5xs-Wvug/s0/Day20-20Nov21-Movement-TrafficIndex2020-Final.png" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" data-original-height="1080" data-original-width="2048" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEju4t7ynrjxcbTEOJxeLu2XBBCsgtUiQfRKc7Woh_s8pb4biOQM5Xd5PkKaCeGNAPlzIn6qoPsTWsmJ8Cdiw2Q4zugdkIeKNJk4n2N7LWuLCXJLBMYi3aA1LLbhbINM0t5xs-Wvug/s0/Day20-20Nov21-Movement-TrafficIndex2020-Final.png"/></a></div>
<hr>
Day 21:Elevation
<br>
Indian States and UTs by Highest Point
<br>
Map generated using MapnikRasterizer in FME from Safe Software
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<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiX9exBtkSFdfA4V7iK5jaOWtPDTZtkBYmammanxaGBJNIoqe7hz8WgB0PTOOX5Dhmykxe4zv0IrarHTUmUrtmn0sG7QdKD1gXYbb90OmnUw5d6lAUq0WwyyI-4sGYT7_mz47phSw/s0/Day21-21Nov21-Elevation_HighestPoints_IndianStatesUTs-Final.png" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" data-original-height="2048" data-original-width="1807" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiX9exBtkSFdfA4V7iK5jaOWtPDTZtkBYmammanxaGBJNIoqe7hz8WgB0PTOOX5Dhmykxe4zv0IrarHTUmUrtmn0sG7QdKD1gXYbb90OmnUw5d6lAUq0WwyyI-4sGYT7_mz47phSw/s0/Day21-21Nov21-Elevation_HighestPoints_IndianStatesUTs-Final.png"/></a></div>
<hr>
Day 22:Boundaries
<br>
Maritime Boundaries: Territorial Seas (12NM)
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Map generated using MapnikRasterizer in FME from Safe Software
<br>
<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjOTBd-01bDuS1xDzluuREk4Rfk0repQgPby_4KNiVSvKwvEOYYZVv2wgAUOfZs7y5ZAsZttjZtfkecHGLzUAv5JMmOMKrJT2nPdS5OgfLtI8AO7YMl4E1tanh7P_lXdJWOejAtGA/s0/Day22-22Nov21-Boundaries-12NM_MarineBoundaries-Final.png" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" data-original-height="1080" data-original-width="2048" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjOTBd-01bDuS1xDzluuREk4Rfk0repQgPby_4KNiVSvKwvEOYYZVv2wgAUOfZs7y5ZAsZttjZtfkecHGLzUAv5JMmOMKrJT2nPdS5OgfLtI8AO7YMl4E1tanh7P_lXdJWOejAtGA/s0/Day22-22Nov21-Boundaries-12NM_MarineBoundaries-Final.png"/></a></div>
<hr>
Day 23:Data Challenge 3: GHSL Global Human Settlement Layer
<br>
GHS Functional Urban Areas (GHS-FUA)
<br>
Map generated using MapnikRasterizer in FME from Safe Software
<br>
<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg-kIPrOg59ZylbGBXSnKz9H6aSaIGk0KKyvjz4t3R-4KZUWuMqsIr0juasQKF3zq0TY-cmgrueBQwhE-guffSuho2iYOQQJKRlzPVomVFum4XvG6lIbP6teLSTnFz8C17iznJq5A/s0/Day23-23Nov21-Challenge3-GHSL-FUA-Final.png" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" data-original-height="1080" data-original-width="2048" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg-kIPrOg59ZylbGBXSnKz9H6aSaIGk0KKyvjz4t3R-4KZUWuMqsIr0juasQKF3zq0TY-cmgrueBQwhE-guffSuho2iYOQQJKRlzPVomVFum4XvG6lIbP6teLSTnFz8C17iznJq5A/s0/Day23-23Nov21-Challenge3-GHSL-FUA-Final.png"/></a></div>
<hr>
Day 24:Historical
<br>
UNESCO World Heritages Sites in India 2021
<br>
Map generated using MapnikRasterizer in FME from Safe Software
<br>
<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhMFMlL3OG-0juwrKs4Q0lx0ne8mmuYj5U5hkz4fzpq96Ccwtf5KPPYYqixKJaxMZWZjRtCaHAQ6sCEi0_vkoalxIV_HzUdywHP9odeqko3PjamNqYmdctfyQorOU1RPIJYurNIlQ/s0/Day24-24Nov21-Historical_WorldHeritageSites-India-Final.png" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" data-original-height="2021" data-original-width="2048" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhMFMlL3OG-0juwrKs4Q0lx0ne8mmuYj5U5hkz4fzpq96Ccwtf5KPPYYqixKJaxMZWZjRtCaHAQ6sCEi0_vkoalxIV_HzUdywHP9odeqko3PjamNqYmdctfyQorOU1RPIJYurNIlQ/s0/Day24-24Nov21-Historical_WorldHeritageSites-India-Final.png"/></a></div>
<hr>
Day 25:Interactive
<br>
World Countries and Urban #Population 2018
<br>
GeoJSON for map generated using FME from Safe Software
<br>
Visualization using Unfolded Studio
<br>
<a href="https://studio.unfolded.ai/public/62a4d07d-4337-47f9-9f17-3d05f2bc42db" target="_blank">Click here for the interactive map</a>
<br>
<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiPn364uZ5QHnFr6uFOG3ji_Wu84Zb76ZgP_0ht392e7qJxUAOsQnhHEz5ZK43DChVrF3gMf7SXu3q6FDo_f1n1JbmJINWPA65XYQffY77TfCXfXiUzaauKuGoflm9ELKrif-ms2w/s0/Day25-25Nov21-Interactive-Unfolded_Interactive_UrbanPopulation2018.png" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" data-original-height="1080" data-original-width="1920" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiPn364uZ5QHnFr6uFOG3ji_Wu84Zb76ZgP_0ht392e7qJxUAOsQnhHEz5ZK43DChVrF3gMf7SXu3q6FDo_f1n1JbmJINWPA65XYQffY77TfCXfXiUzaauKuGoflm9ELKrif-ms2w/s0/Day25-25Nov21-Interactive-Unfolded_Interactive_UrbanPopulation2018.png"/></a></div>
<hr>
Day 26:Choropleth
<br>
Worldwide Estimated Cancer Deaths (2020)
<br>
Map generated using MapnikRasterizer in FME from Safe Software
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<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjZgSLniB6CwE97AdVahb7NqlWKOzKyztpuwVdN7eQN-yjw93pi4hk_lxd9o2pgS3fC4AzpV8jzlmFFmUE0DgJhMpFgm1qk4iAkM2Y_v-RF3vIPFFoe_J96W12V8nc2RKjbZ7NjuQ/s0/Day26-26Nov21-Choropleth-EstimatedCancerDeaths2020-Final.png" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" data-original-height="1080" data-original-width="2048" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjZgSLniB6CwE97AdVahb7NqlWKOzKyztpuwVdN7eQN-yjw93pi4hk_lxd9o2pgS3fC4AzpV8jzlmFFmUE0DgJhMpFgm1qk4iAkM2Y_v-RF3vIPFFoe_J96W12V8nc2RKjbZ7NjuQ/s0/Day26-26Nov21-Choropleth-EstimatedCancerDeaths2020-Final.png"/></a></div>
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Day 27:Heatmap
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Annual Mean Temperature °C (1991-2020)
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Map generated using MapnikRasterizer in FME from Safe Software
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The heatmap effect has been achieved using GradedColorizer transformer in FME
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<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi2iuRXJ0JYSca6E5q7tOe2v3J858hKVf4Za8IDnb5r4PmeqyjupZ0_OogSZIVDVNK6KXBHmITEP48xA3bjm6UtSrGtYOEJrE0nS96FFZ-Pq8bletQuARAz38tpjLQHQFJmhA7I2g/s0/Day27-27Nov21-HeatMap-AnnualMeanTemperature1991-2020-Final.png" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" data-original-height="1080" data-original-width="2048" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi2iuRXJ0JYSca6E5q7tOe2v3J858hKVf4Za8IDnb5r4PmeqyjupZ0_OogSZIVDVNK6KXBHmITEP48xA3bjm6UtSrGtYOEJrE0nS96FFZ-Pq8bletQuARAz38tpjLQHQFJmhA7I2g/s0/Day27-27Nov21-HeatMap-AnnualMeanTemperature1991-2020-Final.png"/></a></div>
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Day 28: Earth is not Flat
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Earth is not flat and that is why we have this completely FME (from Safe Software) generated 3D Globe
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Original workspace of <a href="https://twitter.com/dmitriatsafe" target="_blank">Dmitri Bagh</a> of Safe Software adapted with changes
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And for those interested in juggling around with the actual 3D PDF in Adobe Reader, <a href="https://drive.google.com/file/d/1jts-VsHa3E4qZag-TZOVkbHqdxVNKr15/view" target="_blank">click here</a>
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<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhjvAb5NOdJPzjd92kPaxJBEtVmGwzXqqg01HWW0iGCCo_ChHVYXZvoMZZQrDsYe9t8DKFu-D6eULK52NjlEko_QuczhF2ZEl2YgVMc72Clk-KCCqEbbZx8U6_u-wQRV7DpEn8Ahg/s0/Day28-Earth-is-not-flat-FME-3d-Globe.png" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" data-original-height="1564" data-original-width="2008" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhjvAb5NOdJPzjd92kPaxJBEtVmGwzXqqg01HWW0iGCCo_ChHVYXZvoMZZQrDsYe9t8DKFu-D6eULK52NjlEko_QuczhF2ZEl2YgVMc72Clk-KCCqEbbZx8U6_u-wQRV7DpEn8Ahg/s0/Day28-Earth-is-not-flat-FME-3d-Globe.png"/></a></div>
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Day 29:Null
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World Map in Null generated using MapnikRasterizer in FME from Safe Software
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<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiAtKeYE4Zd1pH7OKZ3ksHr1AWylz3yCnzfiQgZYOaXTodRCd-885Op_4U-TIC19nQVuoAz3DiTtQyPiOej3K-jNDi_eUCTRWAJhgXa9QKte0ENHofIEI92P_11hth9exlf0DglTQ/s0/Day29-29Nov21-Null-World-in-Null-Final.png" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" data-original-height="1080" data-original-width="2048" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiAtKeYE4Zd1pH7OKZ3ksHr1AWylz3yCnzfiQgZYOaXTodRCd-885Op_4U-TIC19nQVuoAz3DiTtQyPiOej3K-jNDi_eUCTRWAJhgXa9QKte0ENHofIEI92P_11hth9exlf0DglTQ/s0/Day29-29Nov21-Null-World-in-Null-Final.png"/></a></div>
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Day 30: Metamapping
That is why, this blog post!
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The #30DayMapChallenge 2021 entries are also available on <a href="https://flic.kr/s/aHsmX9xCYF" target="_blank">Flickr</a>
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It may be 30 days of gruelling, brainstorming; putting all your learning and experience into practice or self test
To me, the whole idea of participating and contributing to #30DayMapChallenge 2021 is about promoting #GIS<br>
But then the satisfaction in having contributed to promotion of GIS outweighs everything else!
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<b>GIS Temper, Let us not lose it!</b>
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I take this opportunity to thank all those who contributed in some way or the other, to my career and to what I am today in the field of GIS!
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Thanks to Safe Software for such a wonderful product/platform "FME" that helped me to convert,transform,share and integrate data from multi-farious sources and types, not just for this #30DayMapChallenge 2021, but for the last 21 years of my career in GIS
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Last but not the least, special thanks to my family (my wife and son) for all the patience, understanding and support, while I meticulously worked on the submission every day!
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More information about Topi Tjukanov (#30DayMapChallenge conceptualizer)
https://medium.com/@tjukanov
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https://twitter.com/tjukanovSaint GIShttp://www.blogger.com/profile/03296153994051314633noreply@blogger.com0tag:blogger.com,1999:blog-7854142.post-82598455299830549032020-06-17T21:57:00.001-07:002020-06-17T21:58:38.848-07:00COVID-19: Lockdown-Unlockdown your Data - Insights Success<a href="https://www.insightssuccess.in/covid-19-lockdown-unlockdown-your-data/">COVID-19: Lockdown-Unlockdown your Data - Insights Success</a>: As a Mapophilic or a Mapophile, maps have always been my love, just like a rain to a pluviophile. Mica Trinidad lists seven strong signs of a pluviophile: You Find Comfort In The Rain You Enjoy Being Outside You Just Want To Bottle Up That “After Rain” Scent You Love The Darkness Of The Sky …Saint GIShttp://www.blogger.com/profile/03296153994051314633noreply@blogger.com0tag:blogger.com,1999:blog-7854142.post-24104000179237716552019-03-06T01:37:00.001-08:002019-03-06T01:37:31.222-08:00The Mapophobic to Mapophilic TransformationIf you had chanced to look into maps made in medieval times, the dragons, multi-headed serpents and other strange fictional creatures marking the distant and unexplored lands on the edges of maps must have surely scared you. Cartographers of medieval times used the inscription HIC SVNT LEONES (“Here are Lions”) and notation of strange or mythical creatures to invoke the harm that sailors feared to encounter when entering previously uncharted territories. Mathematics has been a bitter pill for many as kids. Nevertheless, geography and maps too have been a phobia to many as well. From spatially locating continents, countries, states, cities on a map to getting the capitals right, it has been a nightmare for many experiencing symptoms from racing hearts, sweating, dizziness, disorientation and panic when looking at maps.<br />
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<div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEinN-guIMdF-tH1NJJ-YNEF4lDAQCOhq4XtvigOyKpvHJRYYUyLwg73jfWNgodgMuHhz7GcWQ8RmVP9My-sJyj_Yb9lDDIIiCNatdxOVaBGiHAi7M2l4RRtzZYn1osgEP3V86B3-A/s1600/mapophobic2philic.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEinN-guIMdF-tH1NJJ-YNEF4lDAQCOhq4XtvigOyKpvHJRYYUyLwg73jfWNgodgMuHhz7GcWQ8RmVP9My-sJyj_Yb9lDDIIiCNatdxOVaBGiHAi7M2l4RRtzZYn1osgEP3V86B3-A/s400/mapophobic2philic.jpg" width="400" height="296" data-original-width="1160" data-original-height="859" /></a></div><br />
MapQuest founded in 1967 as a cartographic services division of R.R. Donnelley & Sons launched online maps, the web services version of present day in 1996. MapQuest is still one of the most widely used online mapping services. Google’s findings in 2004 that over 25% of its searches were of a geospatial character, including searches for maps and directions laid the foundation for its acquisition of Keyhole, the core technology behind Google Earth. Later in 2005, Google Maps was launched, which first started as a C++ program designed by two Danish brothers, Lars and Jens Eilstrup Rasmussen.<br />
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<b>Where are we? </b><br />
Thanks to web & mobile based global online map services such as Google Maps, MapQuest, Open Street Maps and Bing Maps to name a few, for having revolutionized the reach of maps. We live in interesting times, where maps are the order of the day. From daily commute to work, holiday planning to exotic places, shortest routing for emergency response, catastrophic natural disaster preparedness & relief, strategic planning to global warming, maps are used everywhere. There is a lot more awareness about importance of location intelligence and Geographical Information System (GIS). People are no more phobic to maps but philic. Maps, location intelligence and GIS are becoming part of our everyday lives sometimes even without us being aware!<br />
The power of location intelligence is of more importance than ever for businesses of this age. Location intelligence is the main stay of several disruptive innovations of today and continues its key position in futuristic disruptive technologies such as Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), Unmanned Aerial Vehicle (UAV), Augmented Reality (AR), Spatial Augmented Reality (SAR), Virtual Reality (VR), Autonomous Vehicles (AV), Computer Vision (CV) etc.<br />
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<b>The Challenges </b><br />
With mobile/connected devices becoming ubiquitous today, the amount of location data generated is enormous. Ever growing location intelligence based disruptive innovations and platforms together with disruptive technologies are proving to be the key differentiator to businesses to improve customer experience, drive revenue and increase operational efficiency. Disruptive technologies like IoT, AV, CV, UAVs etc. are delivering information that has never been possible before, creating entirely new avenues for geospatial data collection, while posing challenges for geospatial data storage, retrieval and analysis. Location-based analytics and platforms that can process and detect trends and provide intelligence are becoming more popular. This has resulted in greater adoption of cloud-based platforms for enterprise GIS deployment involving big data. <br />
Gartner, Inc. had forecast that 8.4 billion connected things to be in use worldwide in 2017, 110 percent of the world population estimated at 7.6 billion as of April 2018, up 31 percent from 2016, and predicted to reach 20.4 billion by 2020. <br />
Big data is all about the notorious five Vs: Volume, Variety, Velocity and Veracity. With disruptive technologies based location intelligence innovations and platforms growing day-by-day, the big data and cloud computing industry are faced with the challenge of geospatial big data capture, storage, analytics, visualization and reporting (dissemination). Besides the typical challenges posed by the five Vs of big data, geospatial industry continues to be trapped in the ever growing matrix of not just GIS data formats and data types but also of non-geospatial nature.<br />
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<b>Every Cloud has a Silver Lining</b><br />
Disruptive innovations and platforms that generate and or consume geospatial big data, quickly reach criticality, where there is so much of (big) data that they are either unable to handle or do not know what to do with them. In this context ETL (Extract-Transform-Load) platforms and specifically Spatial ETL platforms have been the silver lining to the dark data format and data type clouds shrouding the geospatial (big) data industry. Incompatible systems are a thing of the past with Spatial ETL platforms, providing native support for location data, including the complexity of GIS, Computer Aided Drafting (CAD), Building Information Model (BIM) and latest big data eco-systems such as Hadoop. Spatial ETL platforms such as Feature Manipulation Engine (FME) from Safe Software provides the much needed geospatial (big) data conversion-transformation-share-integration along with geospatial analytical capabilities. Such Spatial ETL platforms are already available on the cloud such as Amazon AWS. <br />
History of Big Data traces its first explosion to 1940s; the earliest documented use of the term “information explosion”, nevertheless geospatial data has always been Big Data. Despite challenges posed by Big (Geospatial) Data, it has the potential to improve operations and make quicker and intelligent decisions. Big (Geospatial) Data when converted, transformed, shared and or integrated appropriately using cloud based Spatial ETL platforms, can help organisations gain useful insight to increase revenues, better manage their assets and improve operations geospatially, in a BIG way!<br />
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This article was originally written by this author for Insights Success Magazine October 2018<br />
<a href="http://insightssuccessdigital.in/2018/The-10-Best-Oracle-Partners-To-Watch-In-2018-October2018/#page=44"></a><br />
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Saint GIShttp://www.blogger.com/profile/03296153994051314633noreply@blogger.com0tag:blogger.com,1999:blog-7854142.post-25686582559308249392016-03-30T01:34:00.000-07:002016-03-30T01:34:07.524-07:00Small Things of Big (Geospatial) Data<div dir="ltr" style="text-align: left;" trbidi="on">Be it clicks or likes; the networked world today is generating vast amounts of data at a significantly increasing rate. This together with exponentially increasing internal data is resulting in data explosion, popularly called “Big Data”.<br />
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The history of Big Data traces its origin to 1940s; the earliest documented use of the term “information explosion” and today we have Big Data explosion in geography (geospatial data).<br />
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Big data is a broad term for data sets so large or complex that traditional data processing applications are inadequate (Wikipedia). Paleolithic petroglyphs to modern data centers, the human race has always dealt with information. With technology innovation, Moore’s law is becoming irrelevant and Parkinson's Law of Data; “Data expands to fill the space available for storage” is resulting in information overflow or so called Big Data. <br />
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The world of Big Data is unfolding dramatically right before us from the amount of data being generated to the way in which it is structured and used. Despite the ever growing interest on “Big Data”, we surprisingly hear little about “Big Geospatial Data.” Nevertheless geospatial data has always been “Big Data”. Thanks to the advancements in geospatial data collection or acquisition such as satellite, remote sensing, global navigation satellite systems, aerial surveys using photographic / digital cameras, sensor networks, LiDAR and now Internet of Things (IoTs), is leading to exponential growth in volume of geospatial data. Big (Geospatial) Data exceeding capacity of current computing systems, presents its own set of opportunities and challenges. Examples of Big (Geospatial) Data include, but not limited to earth observation data, sensor data, location information, spatio-temporal data; which are key inputs for real time monitoring and management class of geospatial applications.<br />
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Organisations that generate and or consume geospatial data, suddenly find themselves swimming in so much data that they don't know what to do with them, besides faced with challenges such as capture, query, analysis, visualization, and dissemination of this data.<br />
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Contrary to the notion that Big (Geospatial) Data is just about handling lot more data (both structured and un-structured) requiring sophisticated data storage systems, organisations embracing Big (Geospatial) Data fail to take note that, it is also about handling<br />
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Volume: unprecedented growth in data volumes<br />
Velocity: rapid increase in the velocity or speed of data creation (generation)<br />
Variety: extension in the variety of data types to be handled<br />
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Big (Geospatial) Data is more specifically concerned with the advancing speed in which new information, from an increasing number of diverse data sources and types, confront organisations trying to embrace Big (Geospatial) Data. <br />
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As with any Big Data, the three V’s: Volume, Velocity and Variety are the critical challenges with Big (Geospatial) Data as well. With efficient handling of these three V’s or “Small Things of Big (Geospatial) Data”, organisations embracing Big (Geospatial) Data is sure to reap the full benefits.<br />
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With FME (Feature Manipulation Engine), the industry standard in spatial data transformation technology, from Safe Software Inc., Canada you are in “Safe” hands for a reliable handshake with the ever growing Big (Geospatial) Data universe.<br />
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Volume: With support for several Big Data applications, FME eases the process of migration of voluminous (Volume) legacy or existing data of different types and models from/ to Big Data services or solutions.<br />
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Velocity: There is so much of geospatial and non-geospatial data today available for use immediately or in real time as soon as it is collected. In order for such real time data to be of any use, it requires suitable systems in place, to handle the advancing speed in which new information floods the system, from an increasing number of diverse data sources and types. FME’s real-time processing functionality has the ability to immediately respond to events and trigger different FME actions to ensure real-time data is delivered exactly how it's needed in actual real-time.<br />
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Variety: FME’s exceptional data conversion, transformation, integration, validation and migration capabilities together with support for 345+ data sources such as BIM/ CAD/ Database/ GIS/ LiDAR/ Raster/ Vector/ Web/ XML/ Sensor file formats and data model barriers; can help organisations solve Big (Geospatial) Data challenges with ease. <br />
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With one powerful integration engine and three ways to deploy: FME Desktop, FME Server and FME Cloud, keep ahead of evolving Big (Geospatial) Data, while addressing the three critical V’s or “Small Things of Big (Geospatial) Data”. While FME Desktop lets you connect and transform data in limitless ways, FME Server provides enterprise-level access to FME's powerful capabilities. FME Cloud is the hosted version of FME Server with no hardware required.<br />
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Despite several challenges posed by Big (Geospatial) Data, it has the potential to improve operations and make quicker and intelligent decisions. Big (Geospatial) Data when converted, transformed, shared and or integrated appropriately using a platform like FME, can help organisations gain useful insight to increase revenues, better manage its assets and improve operations geospatially, not just in a BIG way but also in a “Safe” way!<br />
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</div>Saint GIShttp://www.blogger.com/profile/03296153994051314633noreply@blogger.com0tag:blogger.com,1999:blog-7854142.post-71674391089203490962016-03-23T03:13:00.000-07:002016-03-23T03:13:36.053-07:00Geospatial Intelligence: The “Safe” WayThe intelligence, defence and law enforcement communities increasingly rely on geospatial intelligence in today’s world of evolving terror threats, theatres of war, natural disasters and civil unrest.<br />
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The ability of GIS to add spatial perspective to any data being analysed or monitored is the key to geo-intelligence. “Data is Power” and a key component that drives any geo-intelligence solution. Thanks to sensors and IoT (Internet of Things), big data is now a reality: the volume, variety and velocity of data coming into any geo-intelligence system continue to reach unprecedented levels.<br />
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Geo-intelligence is about timely collection, exploitation and analysis of geospatial data, including sensor data, imagery etc to maximise operational capabilities, assess risk and informed decision-making. “Right Information” at the “Right Time” in the “Right Form”<br />
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Many a time, at the critical hour, when the need is for a common operational picture the intelligence agencies end up with GIS interoperability issues not just against GIS file formats but also against real time information from sensors and IoTs. GIS interoperability is the ability to integrate or exchange information between different components of any geospatial (intelligence) solution, even though different agencies are on different GIS platforms and therefore file formats and data models. <br />
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GIS interoperability has long been a burning issue in the geo-intelligence community. For years geo-intelligence users and decision makers continue to maintain data locked up in some proprietary format until the gloomy cloud of interoperability issue suddenly snuck out from nowhere and its dark shadow descends over when the nation is under threat or a disaster strikes. A nightmare scenario, but for this digital alchemy: FME from Safe Software Inc., Canada, the industry standard in spatial data transformation technology.<br />
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Geo-intelligence community is an always connected world and FME’s data conversion, transformation, integration, validation and migration capabilities can not only empower this community to overcome 325+ CAD/GIS/Database/Web/Sensor file formats and data model barriers but also solve day-to-day data interoperability challenges. <br />
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With FME Desktop, FME Server and FME Cloud, keep ahead of evolving sensors or IoT technology and the ever increasing quantity of disparate data types to integrate and instantly make use of urgent intelligence. Increase operational efficiency by removing data integration problems. Build situational awareness by collecting, filtering, and analyzing information from vast data volumes to effectively identify threats and share critical knowledge. Make sense of your sensor data with FME to derive useful, actionable information from sensors with FME's ability to read and process sensor messages, analyze them and identify significant events, then execute appropriate responses to these events, all automatically and in real or near real-time.<br />
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FME Server is a complete sensor data processing solution that enables users to productively overcome all of the complications associated with utilizing sensor data. FME technology supports data transformation and integration between JSON, XML and CSV- the most common formats for raw sensor messages - and hundreds of other data types and applications, enabling you to use sensor data effectively with other data and in any system you need. Accomplish complex analysis with sensor networks, alert people and systems of sensor events in real-time, connect to sensor data management platforms and maximize the value of sensor data with FME.<br />
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With sensors in your own pockets, no matter whatever be the sensor data or GIS file formats that you handle, the only time GIS interoperability could be fun, is when you make peace with GIS file formats and sensor data using FME!<br />
Saint GIShttp://www.blogger.com/profile/03296153994051314633noreply@blogger.com0tag:blogger.com,1999:blog-7854142.post-6397942138937335522015-02-26T02:11:00.001-08:002015-05-11T01:44:34.166-07:00<html><br />
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<title>Writing to CartoDB using FME: My first CartoDB visualization</title><br />
<h1>Writing to CartoDB using FME: My first CartoDB visualization<br />
</h1>Availability of schooling facilities in habitations at primary level as on 30th September 2009 using data from data.gov.in<br />
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Inspired by the new Writer for CartoDB in FME 2015 from Safe Software (www.safe.com), here is my first CartoDB visualization based on data from data from data.gov.in portal of Government of India under NDSP on availability of schooling facilities in habitations at primary and upper primary stages as on 30th September 2009<br />
<p><iframe allowfullscreen="" frameborder="0" height="520" mozallowfullscreen="" msallowfullscreen="" oallowfullscreen="" src="https://saintgis.cartodb.com/viz/3faedf72-f7b9-11e4-92f9-0e4fddd5de28/embed_map" webkitallowfullscreen="" width="100%"></iframe><br />
</p><b><a href="http://www.safe.com/solutions/cartodb/">Click here for more information on CartoDB support in FME</a></b><br />
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</html>Saint GIShttp://www.blogger.com/profile/03296153994051314633noreply@blogger.com0tag:blogger.com,1999:blog-7854142.post-45138726053087727422014-09-08T03:02:00.001-07:002014-09-08T05:50:26.737-07:00Mr M.Krishnan's-Thirumullaivoyal house in Google Earth 3D<div dir="ltr" style="text-align: left;" trbidi="on"><div style="color: #222222; font-family: 'Open Sans', 'Helvetica Neue', Helvetica, Arial, sans-serif; font-size: 14px; line-height: 23.7999992370605px; margin-bottom: 0.825em;">Well the intention of this blog as it states is to talk about Geographical Information Systems (GIS) and my (<span style="line-height: 23.7999992370605px;">Saint GIS) </span><span style="line-height: 23.7999992370605px;">favourite Spatial ETL tool FME (Feature Manipulation Engine),but this is an exceptional post for my well wisher.</span></div><div style="color: #222222; font-family: 'Open Sans', 'Helvetica Neue', Helvetica, Arial, sans-serif; font-size: 14px; line-height: 23.7999992370605px; margin-bottom: 0.825em;">It is said, one of the biggest commitments anybody will make in one’s life, both financially and emotionally, is buying or building a house. Though it is interesting for a few, the experience of most of the buyers is fraught with frustration, exhaustion and poor satisfaction. A significant feature is that the location of a project plays a predominant role in the decision making process. This is a 3D model of a residential house being constructed and modeled in 3D in Google Earth kml format for visualizing the proposed residential development along with its environs. This is a regular practice in many countries to ensure that any new urban development is in harmony with its neighbourhood.</div><div style="color: #222222; font-family: 'Open Sans', 'Helvetica Neue', Helvetica, Arial, sans-serif; font-size: 14px; line-height: 23.7999992370605px; margin-bottom: 0.825em;">So why not consider this as a first model(step) for Chennai!</div><br />
<iframe src="http://www.nearby.org.uk/google/fake-kmlgadget.html?up_kml_url=https://sites.google.com/site/krishnanhouse3d/krishnanhousekmzfile/KrishnanHouse3d_3551-08Sep14.kmz?attredirects=0&d=1&up_view_mode=earth&up_lat=&up_lng=&up_zoom=&up_earth_2d_fallback=0&up_earth_fly_from_space=1&up_earth_show_nav_controls=1&up_earth_show_buildings=1&up_earth_show_terrain=1&up_earth_show_roads=1&up_earth_show_borders=1&up_earth_sphere=earth&up_maps_streetview=0&up_maps_zoom_out=0&up_maps_default_type=hybrid" height="600" width="600"></iframe><br />
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</div>Saint GIShttp://www.blogger.com/profile/03296153994051314633noreply@blogger.com1tag:blogger.com,1999:blog-7854142.post-51100539456380233832013-06-25T00:24:00.002-07:002013-06-25T00:27:12.540-07:00Himalayan Tsunami 2013-Uttarakhand Flood Calamity 2013,India<hr>
<h1>Google Earth tour of some flood ravaged areas</h1>
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<h1>This Google Earth project is dedicated to those pilgrims and tourists whose lives were lost in the recent floods (June 2013) in the State of Uttarakhand, India</h1>
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<h3>This is a tour of some flood ravaged areas.</h3>
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<h3>More information on Uttarakhand:</h3>
http://en.wikipedia.org/wiki/Uttarakhand
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http://www.uk.gov.in
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<h3>RESCUE & RELIEF OPERATIONS WEBSITE </h3>
http://164.100.150.41/rescuenrelief
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<h3>Google Person Finder-2013 Uttrakhand Floods </h3>
http://google.org/personfinder/2013-uttrakhand-floods/
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Saint GIShttp://www.blogger.com/profile/03296153994051314633noreply@blogger.com0tag:blogger.com,1999:blog-7854142.post-61675997090803799492011-09-05T03:37:00.000-07:002011-09-05T03:37:55.019-07:00Web GIS for Public Health<div dir="ltr" style="text-align: left;" trbidi="on">
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Heraclitus, a Greek philosopher known for his doctrine of change being central to the universe rightly said that change is <span class="googqs-tidbitgoogqs-tidbit-0"><span lang="EN" style="mso-ansi-language: EN;">the only constant in this universe. No reason why this change should not be constant in the noble life saving field of medical sciences.</span></span></div>
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<span lang="EN" style="mso-ansi-language: EN;">Public health is "the science and art of preventing disease, prolonging life and promoting health through the organized efforts and informed choices of society, organizations, public and private, communities and individuals" (1920, C.E.A. Winslow). It is concerned with threats to the overall health of a community based on population health analysis. The population in question can be as small as a handful of people or as large as all the inhabitants of several continents (for instance, in the case of a pandemic). Public health is typically divided into epidemiology, biostatistics and health services. Environmental, social, behavioral, and occupational health are other important subfields </span>(Wikipedia). The underlying commonality in many of the above aspects of public health research is the spatial component of the factors being analysed or monitored.</div>
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Medical geography aka health geography, is an area of medical research that incorporates geographic techniques into the study of health around the world and the spread of diseases. It also includes studies on the impact of climate and location on an individual's health as well as the distribution of health services. Medical geography is an important field because it aims to provide an understanding of health problems and improve the health of people worldwide based on the various geographic factors influencing them. Health geography is the application of geographical information, perspectives, and methods to the study of health, disease, and health care (Wikipedia).</div>
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<span lang="EN" style="mso-ansi-language: EN;">Thanks to the Greek doctor Hippocrates (5th-4th centuries BCE) for having studied the effect of location on one’s health thus laying the foundation for the beginning of medical geography. But for Dr John Snow, a </span>doctor in London<span style="mso-ansi-language: EN;"> </span>who plotted the distribution of cholera deaths throughout London on a map and found a cluster of unusually high deaths near a water pump on Broad Street, <span lang="EN" style="mso-ansi-language: EN;">when the cholera epidemic gripped London medical geography would not have gained significance. </span>Since then geographic techniques have found their place in several other areas of public health research.</div>
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<span lang="EN" style="mso-ansi-language: EN;">The ability of a GIS to add spatial perspective to any data being analysed or monitored is the key to its application in public health research. GIS has always proved to be very useful to epidemiologists across the globe in elucidating patterns and relationships between the person, place, and time components of epidemiologist data. In addition, GIS technology has been an important tool for understanding and displaying disease or disease risk that are related directly to environmental exposure. </span></div>
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<span lang="EN" style="mso-ansi-language: EN;">Medical geography has an increasing number of applications due to advancements in ICT and GIS. Besides, the spatial distribution of disease is still a large matter of importance, with GIS based maps playing a significant role in this field. </span>Much recent attention has focused on developing GIS functionality in the Internet, Worldwide Web, and private intranets and is termed Web GIS. Web GIS is a Geographic Information System distributed across a networked computer environment to integrate, disseminate, and communicate geographic information visually on the World Wide Web over the Internet” [Gillavry, 2000]. Web GIS is also popularly called as Internet GIS. Web GIS holds the potential to make distributed geographic information (DGI) available to a very large worldwide GIS audience. On similar lines, <span lang="EN" style="mso-ansi-language: EN;">Google Maps in the recent years has revolutionized the way in which information on several epidemics/ pandemics like swine flu, flu (Google Flu Trends) is delivered to general public with the latest addition being Google Insights for Search.</span></div>
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The objective is to focus on the following aspects:</div>
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<li class="MsoNormal" style="margin: 0in 0in 0pt; mso-list: l0 level1 lfo1; tab-stops: list .5in; text-align: justify;">Importance of public health research,</li>
<li class="MsoNormal" style="margin: 0in 0in 0pt; mso-list: l0 level1 lfo1; tab-stops: list .5in; text-align: justify;">Current trends in the field of GIS, especially Web GIS</li>
<li class="MsoNormal" style="margin: 0in 0in 0pt; mso-list: l0 level1 lfo1; tab-stops: list .5in; text-align: justify;">GIS Applications in Medical Geography – Tools & Technologies,</li>
<li class="MsoNormal" style="margin: 0in 0in 0pt; mso-list: l0 level1 lfo1; tab-stops: list .5in; text-align: justify;">Spatial Epidemiology: Current Trends and Future Challenges </li>
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It can be easily demonstrated how the convergence of advancements in ICT and Medical Geography or Health GIS could play a major role in public health research in taking it to the next level.</div>
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The Future of Human Life Expectancy: Have We Reached the Ceiling or is the Sky the Limit? Although human ability to take command of the course of life and death is controversial, after remaining fairly constant for most of human history, life expectancy has nearly doubled in the past century. However the trend towards longer life has also raised concerns about the quality of life at older ages. </div>
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GIS together with the advancements in ICT, if applied in the right manner, at the right time, for sure can help address the problems confronting the epidemiologist and the medical community in saving the human race, if not solve them completely.</div>
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No matter whether human life expectancy has reached the ceiling or sky is the limit: Let us explore ways to apply GIS to make our lives better!</div>
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~ SRG</div>
Saint GIShttp://www.blogger.com/profile/03296153994051314633noreply@blogger.com0tag:blogger.com,1999:blog-7854142.post-68122289047034549432010-12-18T01:37:00.000-08:002010-12-18T01:39:35.749-08:00GIS based Donor Information System<div align="center"><span style="font-size:180%;">GIS based Donor Information System</span></div><span style="font-size:180%;"></span><div align="justify"><br />Phone calls to friends and relatives with a great deal of anxiety are quite common during medical emergencies arising out of accidents or illness or other such medical conditions. Any help from unknown quarters comes as a big relief. But one is often caught scrambling during such critical times for much-needed information, the information regarding donors.<br /><br />It is needless to emphasize the plight of those looking out for blood donors especially of rare blood groups during such medical emergencies. If such is the situation with information on blood donors, imagine the nightmare of those looking for information on donors of other types such as bone marrow, kidney, liver, lungs, eyes etc not getting the required information at the appropriate time. Everyday thousands of lives are lost for want of such critical information at the appropriate time. When lives are at stake, every second counts and words cannot describe the plight of the near and dear ones, running from pillar to post in locating the donors.<br /><br />Geography or GIS for that matter has never been so closer offering a helping hand in our day-today life. Web based and even GIS based blood bank/ blood donor information systems are already the order of the day. But for some reason the concept has not extended beyond blood banks and blood donors into other types of medical donors like eye, kidney, bone marrow, lung, liver donors etc. and corresponding donor banks/ facility.<br /><br />“Brain death” something hitting the headlines these days refers to the irreversible end of all brain activity (including involuntary activity necessary to sustain life) due to total necrosis of the cerebral neurons following loss of blood flow and oxygenation. Brain stem death (not whole brain death) is taken to be the significant indicator of death. Brain death may result in legal death, but still with the heart beating, and with mechanical ventilation all other vital organs may be kept completely alive and functional, providing optimal opportunities for organ transplantation. Most organ donation for organ transplantation is done in the setting of brain death. In some nations (for instance, Belgium, Poland, Portugal and France) everyone is automatically an organ donor, although some jurisdictions (such as Singapore, France, or New Zealand) allow opting out of the system. Elsewhere, consent from family members or next-of-kin is required for organ donation. (Source: <a href="http://en.wikipedia.org/wiki/Brain_death">http://en.wikipedia.org/wiki/Brain_death</a>).<br /><br />With the success of organ transplantation as an effective modality of treating end stage disease of various organs, increasing numbers of organ transplants are being performed all over the world. However, this procedure requires a “donor” pool of either “living” or “cadaveric” donors. Since this pool is limited, the gap between “demand” and supply is widening, which is further hampered with the non-availability of information regarding this limited donor pool at the right time. In the context of organ donation “cadaveric” donation has largely meant “brain dead” or “heart beating” donors. Such cadaver organ donation no doubt requires a robust IT/GIS based operational support system as its backbone to effectively utilize such cadaver donors.<br /><br />A final thought: For a moment let us close our eyes and imagine the plight of the near and dear ones scrambling for information on donors, during medical emergencies. How thoughtful it would be if a donor registered for eye donation breathes his last and a SMS with the donor ID to a centralised server with details regarding the place, date and time of death etc is dispatched by the kith and kin of the deceased. This SMS then triggers of a set of GIS analysis on the server based on parameters such as the list of recipients registered in the vicinity of the donor considering medical factors for organ donation along with the spatial separation between the donor, recipient and the transplantation facility. The end result is an alert to either to the recipient/ care taker/ medical facility with location details of the donor.<br /><br />A new concept such as this GIS based donor information system definitely needs inputs and support from all quarters and needs to be experimented, given a deep thought to put in practice.<br /><br />The donors may be living or cadaver, their hearts beating or not beating, but let our hearts beat as one for a GIS based Donor Information System!<br /> </div>Saint GIShttp://www.blogger.com/profile/03296153994051314633noreply@blogger.com0tag:blogger.com,1999:blog-7854142.post-29635751867932095192010-12-18T01:33:00.000-08:002016-03-23T03:35:34.437-07:00Can GIS Save Lives?<div dir="ltr" style="text-align: left;" trbidi="on"><div align="center"><span style="font-size: 180%;">Can GIS save lives?</span></div><br />
<span style="font-size: xx-normal;">Medical geography aka health geography, is an area of medical research that incorporates geographic techniques into the study of health around the world and the spread of diseases. It also includes studies on the impact of climate and location on an individual's health as well as the distribution of health services. Medical geography is an important field because it aims to provide an understanding of health problems and improve the health of people worldwide based on the various geographic factors influencing them. Health geography is the application of geographical information, perspectives, and methods to the study of health, disease, and health care (Wikipedia)</span><br />
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<span style="font-size: xx-normal;">During the times of the Greek doctor Hippocrates (5th-4th centuries BCE), people have studied the effect of location on one’s health. For example, early medicine studied the differences in diseases experienced by people living at high versus low elevation. It was easily understood that those at living low elevations near waterways would be more prone to malaria than those at higher elevations or in drier, less humid areas (geography.about.com). Though the reasons for these variations were not fully understood at the time, the study of this spatial distribution of disease for sure was the beginning of medical geography. It was not until middle of 18th century when the cholera epidemic gripped London that medical geography gained significance.</span><br />
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<span style="font-size: xx-normal;">During the last three decades, a powerful technology has quietly changed the way people view and live in their neighborhoods, towns, and cities. Most people remain unaware of GIS and its impact-an impact that is as far-ranging as it is useful-despite GIS having grown immensely in the last 15 years, despite hundreds of thousands of people now using the technology, and despite it affecting the daily lives of millions (ESRI).</span><br />
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<span style="font-size: xx-normal;">Be it the pandemic killer swine flu or AIDS of the 20th century, the super power of GIS is its ability to add a spatial perspective to any data being analysed. This has always proved to be very useful to epidemiologists across the globe in elucidating patterns and relationships between the person, place, and time components of epidemiologist data. In addition, GIS technology has been an important tool for understanding and displaying disease or disease risk that are related directly to environmental exposure.</span><br />
<span style="font-size: xx-normal;"></span><br />
<span style="font-size: xx-normal;">Today, medical geography has a number of applications as well. Since the spatial distribution of disease is still a large matter of importance, with GIS based maps playing a significant role in this field. Google Maps in the recent years has revolutionized the way in which information on several epidemics/ pandemics like swine flu, flu (Google Flu Trends) is delivered to general public.</span><br />
<span style="font-size: xx-normal;"></span><br />
<span style="font-size: xx-normal;">The Center for Disease Control and Prevention (CDC) in the United States for instance uses what they call the Atlas of United States Mortality to look at a wide range of health factors across the U.S. Data ranges from the spatial distribution of people at different ages to places with the best and worst air quality. The World Health Organization (WHO) features health data for the world with its Global Health Atlas. In India NATMO (National Atlas and Thematic Mapping Organisation) prepares Health and Diseases Atlas for India besides other organisations.</span><br />
<div align="justify"><span style="font-size: xx-normal;">Though GIS has been playing a significant role in the field of medical geography, there are quite a few stumbling blocks/ limitations as well. They could be anything from accurately tracking the first incidence of a disease, the accuracy of data collected to confidentiality laws that can complicate the reporting of a disease.</span><br />
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<span style="font-size: xx-normal;">A final thought: For a moment let us close our eyes and imagine the plight of our human race threatened with a plethora of heath related issues in this 21st century. Of what use could be any technology if it cannot reach and benefit the common public suffering in the veritable concrete jungles, the so-called cities and the remote villages of India? It is a pity that technologies such as GIS and many such applications do not see the light of the day, for one reason or the other. Let us explore ways to apply GIS to make our lives better!</span><br />
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<span style="font-size: xx-normal;">Now, Can GIS save lives? The answer is: on the lighter vein, GIS has been my bread winner for several years now. GIS may not be the paragon of all virtues but it could be important as one of several measures for addressing the problems confronting the epidemiologist and the medical community in saving the human race, if applied in the right manner, at the right time.</span></div></div>Saint GIShttp://www.blogger.com/profile/03296153994051314633noreply@blogger.com0tag:blogger.com,1999:blog-7854142.post-1153112090484630392006-07-16T21:50:00.000-07:002006-07-16T21:54:50.506-07:00Broadening the CAD-GIS horizons<div align="justify">INTRODUCTION<br />Broadband is the marriage of telecommunications and cable technologies. As it is rightly said, “Necessity is the mother of invention”, the last decade saw tremendous advancements in the arena of digital and fiber optic technologies: key elements empowering the broadband technology. Broadband technology has not only given a new meaning for information exchange, but has also been the building blocks for the so-called “Information Superhighway”. Besides fostering a new class of consumer and business related services such as IP based telephone and video conferencing services, Video On Demand (VOD), home networking etc., it has also resulted in increased cable modem penetration and deployment of cable telephony services, making cities digitally intelligent.<br /><br />Broadband technology besides being looked upon as an innovative technology, as a tool to make the city residents digitally literate, competent and proficient, it is also being looked upon as an “always-open gateway” to a new world of telecommunications and cable technologies and as the buildings blocks for the so called “Information Superhighway”, expected to dictate the economic development of the cities of the third world.<br /><br /><br />NEED FOR GIS IN BROADBAND INDUSTRY<br />As with most utilities, cable companies traditionally create and maintain detailed paper maps of their systems (network and equipments). In the last decade these paper maps became increasingly generated and stored using CAD and rarely did these MSO’s employ the software for tasks beyond simple drafting. In other words the CAD technology was merely used to create an image for the purpose of engineering documentation, whilst maintaining key data in disparate spreadsheets and other databases to manage their key assets.<br /><br />With the tremendous pace at which the broadband infrastructure is being deployed and given the ever-growing consumer needs, the cable and broadband companies are at crossroads. Moreover these systems expand geographically and functionally every day. The realities of this new paradigm have made obsolete, the manual, non-integrated approach to asset management, network monitoring and customer care that characterized the cable industry’s simpler past. In the absence of a comprehensive out-of-box solution in place and faced with the competitive realities, the cable companies are finding it difficult to not only manage the increasing volume of CAD documents associated with such network systems, but their real assets on the field as well. The engineering departments rely on system maps painstakingly drawn by drafters and residing in legacy CAD/Database combination files, paper maps, disparate spread sheets and other such formats, thereby making their enterprise wide usage redundant. By virtue of the manner in which such critical cable plant network data is maintained and managed, quicker and accurate decisions are next to impossible.<br /><br />It is in this context that GIS finds importance in not only giving asset management a new dimension with the ability to handle geospatial data but also in revolutionizing the way in which such key assets are managed. In the recent years the trend has been to integrate geospatial and asset management systems to provide the most natural and effective links in utility information management and this synergy has been quite evident. Awakened by the shortcomings of the CAD/Database combination approach of the existing legacy systems to maintain key network element information and faced with the competitive realities, it seems quite logical to apply geospatial technology for a solution to this crisis.<br /><br />GIS BASED BROADBAND AM/FM UTILITY GIS – WHAT IS IT?<br />PIXEL has been serving the Broadband/ Cable industry for the past 12 years and this rich experience along with its skilled in-house GIS team has gone into developing this GIS based Broadband Information System to address the key issues confronting such systems like: Network monitoring & Optimized Efficiency in Service, Ability to take Quicker and Accurate Decisions, Better Asset Management etc. A web based GIS for cable TV operators and other utility companies is a linkage of databases and maps, thereby creating a searchable interface that includes the simplest functionalities like zooming and panning to the sophisticated ones like printable reports and completely searchable and locatable network elements. Applying GIS for the Broadband industry will not only help the industry migrate their cable plant data from their existing obsolete legacy CAD/ Database systems to a web based GIS system but also derive enterprise wide benefits, effectively manage their assets, avoid intelligence redundancy and have the information about their assets at their finger tips. PIXEL though this article shares its years of rich international and domestic experience in the HFC/ Broadband industry both in the design and GIS creation.<br /><br />THE CATV HFC WORKFLOW<br />A typical CATV (Cable TV) network map starts with a field walkout collecting the addresses to be served and verifying them. This is followed by what is called a STRAND MAPPING. Strand Mapping is a graphical representation of Broad Band network routing. Data collected through field walk is drafted on CAD software, which forms the base for Broad Band network design. This is followed by a Node layout based on the HFC architecture deciding the number of homes passed. Then the actual RF Network design and or Fiber design is done. There are several combinations in this Broadband architecture depending on the actual devices and systems used. In places like Manhattan in New York, there are FTH connections or what is called as Fiber to Home.<br /><br />MIGRATING CAD DATA TO GIS<br />Intelligent graphics and data binding between the graphical elements on a map and its corresponding information in a database is the essence of any GIS system. Deploying GIS for the Broadband industry is with the intention to enable the Broadband, Coaxial, Fiber and other network element information data of cable companies residing in legacy CAD/Database systems accessible to its users enterprise wide via corporate intranet or the World Wide Web. The first and the most challenging step for PIXEL was to perform spatial & attribute data mining and migration from the traditional CAD/Database format combinations to a user friendly, cost effective and easy to use GIS format.<br /><br />To avoid GIGO (Garbage In Garbage Out), before the process of mining the data from the traditional systems, PIXEL does what is known as data scrubbing and validation. In this process the key information based on the nature of the queries and reports required for a MSO, is filtered out. The inaccuracy and inconsistency of the data is brought to the attention of the MSO and appropriate action taken before taking it up for data migration. The input data for migration to any standard GIS or more complicated systems like GE Smallworldâ is run through several processes checking for the database integrity, signal levels, engineering design consistency, design and drafting errors etc. before the files are sent for migration to GIS. This is necessary and a critical process in the life cycle of the project, due to the inconsistencies that creep in during the drafting and design processes of these files that are carried out not by one contractor but by several of them. In some instances due to technological limitations at the time of data migration many of the system maps are unintelligent. These are made intelligent by a skilled in-house team either by manual or semi-manual drafting and design processes. Another obstacle in the path of CAD-GIS migration was the multiplicity of CAD formats like Bentleyâ’s MicroStation, AutoCADâ etc. and databases like Oracle, dBase etc. in which the spatial and attribute data respectively to be migrated resided. Thanks to FMEâ(Feature Manipulation Engine), powerful spatial data translation and transformation software from Safe Software, Canada. With the aid of custom-made mapping files designed in house, the data mining is done at various levels to migrate the unintelligent or relatively less intelligent data into a more intelligent piece of geospatial data. This is essential to enable the network elements to be completely searchable in a web based GIS environment satisfied by virtue of the carefully designed data model and layer structure.<br /><br />FMEâ, the spatial ETL (Extract, Transform and Load) tool from Safe Software, is a Swiss Army knife in terms of cutting across the CAD-GIS migration barriers and in handling multitude of CAD/GIS file formats in the industry. It is the neutral CAD/GIS environment of FME that adds power and giving it an unique edge in the interoperability industry. Over 170 plus CAD/GIS formats as on date are interoperable through FME. PIXEL’s experience in the CAD/GIS industry suggests that many a time the network and landbase data in popular CAD formats are prone to simple design and drafting errors to more complex ones like database integrity, inconsistent signal levels between network elements/ equipments, engineering design inconsistency etc. There have been always these issues of the landbase over which the Broadband network elements are drafted and designed getting outdated or requiring a datum shift from say NAD27 to NAD83 systems in a typical United States system. Most of the data though available in CAD formats, either are not suitable for a direct GIS migration by virtue of the file formats or prone with drafting errors like overshoots, undershoots, snapping errors. All of these require a thorough data scrubbing. PIXEL’s in-house team does most of these through its custom in-house data scrubbing tools or using FME.<br /><br />The next task was to make this intelligent piece of network information available for enterprise wide use and to provide the end users at various levels with the appropriate tools and interface for querying, report generation and other such routine tasks relating to the cable industry. Along with the appropriate development tools, based on our experience with some of our most prestigious cable MSO’s and understanding of the key end user requirements, an appropriate web GIS interface has been developed to make the most out of GIS.<br /><br />Broadband AM/FM Utility GIS<br />Beyond making intelligent network maps available for enterprise wide use, GIS as evident has other features that can be used for network operations, field engineering, marketing & sales and engineering purposes. To quote a few:<br /><br />The Network Operations Center (NOC) could use GIS for trouble ticket dispatch at a quicker pace with no more rummaging through cumbersome paper maps or Run a trace to locate the fiber cut for service restoration or Quickly highlight the consumers who will be affected from an outage, so that the alternative measures could be planned.<br /><br />The Engineering department can plan before they dig up, as the network plant data is made available overlaid with appropriate GIS landbase layers in GIS. The engineers can locate any piece of network element like amplifiers, power supply, cables etc. The customer addresses can be clicked to get information like what type of cables run to it? Where is the feeding amplifier? Which node is it connected to? How many houses are wired to the same network? Where are they? and so on. Quickly generate engineering inventory reports like the total cable footage, house counts, count of specified pole types within a given service area and so on.<br /><br />The Accounting department for the inventory report on its valuable assets out in the field could simply pick the fields on which they wish to generate the reports or do franchise fee calculations, weekly or monthly field inventory statements etc.<br /><br />The Marketing and Sales department could locate their “Best Customers” based on specific criteria and this could be for their proposed service area or could be within the existing ones. This could also be to identify the “Best Business” location or to identify areas suitable for reference or direct advertisement.<br /><br />GIS for Broadband also offers a wide range of scope to integrate GIS system with other existing Work Management Systems (WMS) at various levels.<br /><br />INTEGRATING WITH WORK MANAGEMENT SYSTEMS<br />Integrating GIS with other systems increases its value proposition and gone are the days of a standalone GIS system. By integrating such GIS based systems with other work management systems, one can get a wider range of benefits. Work management systems could be anything from a market analysis system to an outage management system or a bandwidth management system. By using powerful Geocoding tools the non-geospatial data associated with such systems can be tied to an appropriate spatial entity in the existing geospatial network data in GIS. This not only allows for an opportunity to visualize the non-geospatial data associated with such systems, but to also display the output from such systems on an intelligent GIS map. As an example the output from an outage management system could be used to display the trouble ticket location at the appropriate zoom level with other GIS layers on a GIS map. In most cases the existing outage management systems or any other work management systems for that matter lack such an interface leaving the decision makers with no choice other than a rugged display of the output from such system. There can be no doubt on the ability of GIS to discover existing dormant relationships between various entities. Moreover in the case of existing work management systems, they are discrete and this makes it impossible to bring valuable information in a timely manner. The role of any AM/FM GIS system for that matter would be to tightly integrate these systems and provide the users with the ability to view all the critical components of their operations processes at the click of a button.<br /><br />Of all creatures, humans are the only ones who can ponder over and understand a situation and the only ones who can think up ways of doing something about a problem in a rational and logical way. GIS may not be the paragon of all virtues, but it could be important as a tool for addressing key problems and rudimentary processes of the Broadband industry. Building the “Information Superhighway” with the Broadband technology to improve economic development, make city residents digitally literate and the cities intelligent is a mammoth task and with GIS, “Broadband bandwidth that is used to access such GIS is not the limit” but "Sky is the true limit!”<br /> </div>Saint GIShttp://www.blogger.com/profile/03296153994051314633noreply@blogger.com0tag:blogger.com,1999:blog-7854142.post-1121771859264445362005-07-19T16:45:00.000-07:002005-07-19T04:25:29.686-07:00India: I Speak GIS<div align="justify">Geography or GIS for that matter has never been so closer to our lives. Citizens and Planners of our country have never had so much insight into the lives of the people: Where they live, How they live and What they do? Thanks to GIS for having opened their eyes to this new era of Geospatial Democracy. “Maps speak subtle and surprising truth”. But surprisingly in a country like India, the world’s largest democracy, maps have always been confined to geographers and planners. The hoi polloi, who constitute the basic tenets of democracy, have always been silently and safely ignored in most of our planning processes and kept away from accessing the geospatial data. Among the greatest shortcomings of Indian democracy is the citizens being denied the information they need to make meaningful choices.<br /><br />With the enactment of Freedom of Information Act, 2002: An Act to provide for freedom to every citizen to secure access to information under the control of public authorities, consistent with public interest, in order to promote openness, transparency and accountability in administration and in relation to matters connected therewith or incidental thereto.<br /><br />The people of our country now therefore have a right to their own views, to promote them in informed discussions, demand transparency in government, and to offer criticism without fear. The courts have repeatedly affirmed these, but the quest to realize them is far from over. The position pretty much clearly established in law, there is little doubt that information is not as free as scientists or other common citizens would like it to be. With reference to GIS, there are mounds of information to which the general public are still denied access. Maps of numerous areas are restricted beyond a particular scale. Given this situation, how do we expect the basic tenets of our democracy to put forward their views in the absence of GIS literacy and lack of geospatial democracy? Most government sector agencies do not understand the value of their data, and either do not release it or do not know how to price the data.<br /><br />The objective of this paper is:<br />To create awareness on the need to integrate GIS into our daily planning activity at various levels.<br />To show how GIS can effectively analyze different demographic and development indicators of India at state level and arrive at conclusions.<br />To show that “GIS holds the key to unlocking a nations potential” and Geospatial Democracy is the need of the hour.<br />Urban planning & GIS – an overview<br />Planning is a future-oriented activity that links "scientific and technical knowledge to actions in the public domain. It happens through a public discourse between all groups and individuals interested in and/or affected by urban development and management activities pursued by the public or private sector. Planning-related decisions are made daily through a complex, often politically charged process involving plurality of interests. Moreover, the implementation of those decisions makes a long-term imprint on the urban structure, functionality, and quality of life in urban environments. While most of urban and regional planning happens at the local level, national and state policies and legislation often influence planning activities.<br /><br />Role of GIS<br />The demographic and other development indicators for a planning area may be available in different forms such as paper maps, photograph, textual, graphical or tabular form to the planner. Integration of these multifarious data and their analysis is a tedious, time consuming and a real Herculean task for the planners. Moreover basic things like preparation of base maps by traditional methods take away the time and resources of planners, leaving little or no time for an elaborate analysis of the data collected in an effective manner.<br /><br />It is in this context that GIS find importance as a tool to enhance their analytical, problem-solving, and decision-making capability of the planners. From the late 1950s planners started to develop and use computerized models, Planning Support Systems (PSS), Planning Information Systems (PIS) and Decision Support Systems (DSS) to improve performance. Adoption of Geographic Information Systems (GIS) is a more recent manifestation of the same effort to incorporate new tools and technologies.<br /><br />India: the tiger speaks GIS<br />One who visits India for the first time is sure to be enthralled in its vivid kaleidoscope of landscapes, magnificent historical sites and royal cities, golden beaches, misty mountain retreats, colorful people, rich cultures and festivities. But for the hoi polloi, who else could say if the harsh realities, problems and paradoxical situations confronting them, have been hidden behind the tall skyscrapers and in the veritable concrete jungles of the cities of India.<br /><br />To understand the current state of affairs in various states of India and to demonstrate how GIS can be effectively used in planning, few demographic data and development indicators like:<br />Population<br />Population density<br />Sex Ratio<br />Literacy and<br />Urbanization<br />at state level have been taken up for analysis.<br /><br />Let us hear the fascinating story that the tiger country: India has to speak to us in the language of GIS.<br /><br />Population<br />The total population of India as at 0:00 hours of 1st March 2001 stood at 102,70,15,247 persons. In terms of population it became only the second country in the world after China to cross the one billion mark. At the state level, Uttar Pradesh tops the list with a total population of 16,60,52,859 persons, followed by Maharashtra. Interestingly a grid thematic analysis (Figure 1) of the population growth rate (1991-2001) using GIS throws more light on the fact that Nagaland which is in the twenty fifth place in terms of total population however comes first in terms of the growth rate, with Delhi in the fourth place. The red spots in indicate a population growth rate of over 50% between 1991-2001.<br /><br /></div><p><a href="http://photos1.blogger.com/blogger/3045/504/1600/mi04018.jpg"><img style="DISPLAY: block; MARGIN: 0px auto 10px; CURSOR: hand; TEXT-ALIGN: center" alt="" src="http://photos1.blogger.com/blogger/3045/504/320/mi04018.jpg" border="0" /></a><br /><br />Figure 1: Population growth rate (1991-01)<br /><br />Population Density<br />An important index of population concentration is its density measured as number of persons per square kilometer.<br /><br />According to world development report (2000-01) of World Bank, the world average is 46 persons per sq km and for low-income countries the average is 73. A thematic map (Figure 2) using GIS shows that Delhi tops with 9294 occupying one square kilometer area. Population density is a good indication for overcrowding especially in cities<br /><br /><br /><a href="http://photos1.blogger.com/blogger/3045/504/1600/mi04018a.jpg"><img style="DISPLAY: block; MARGIN: 0px auto 10px; CURSOR: hand; TEXT-ALIGN: center" alt="" src="http://photos1.blogger.com/blogger/3045/504/320/mi04018a.jpg" border="0" /></a><br /><br />Figure 2: Population Density (2001) Persons per Sq. Km<br /><br />A dot density thematic of population density growth factor between 1991 and 2001 (Figure 3) shows the drastic change in the density in Delhi and adjoining states where the growth factor is over 1.25 as evident from Figure 3. In Delhi about 3000 more people are occupying the same space in 2001 as compared to the year 1991. As the density of population increases the need for infrastructure increases. A case of expanding population and finite resources, calls for population stabilization so that undue pressure is not put on its natural resources to support the rising population.<br /><br /><a href="http://photos1.blogger.com/blogger/3045/504/1600/mi04018a.jpg"><img style="DISPLAY: block; MARGIN: 0px auto 10px; CURSOR: hand; TEXT-ALIGN: center" alt="" src="http://photos1.blogger.com/blogger/3045/504/320/mi04018a.jpg" border="0" /></a><br /><br />Figure 3: Population Density (1991-2001) Growth Factor<br /><br />Sex Ratio<br />Sex ratio is defined as the number of females per 1,000 males in the population. It is an important indicator to measure the extent of prevailing equity between males and females at a given point of time. It may be noted that India still has a low sex ratio of 933 females per 1000 males in 2001. In 1991, the sex ratio was 927. There has been a slight improvement, but compared to other countries the situation is disappointing. Important reasons to analyze sex ratio are to throw light on issues like neglect of the girl child; high maternal mortality; sex-selective female abortions and female infanticide. The tiger country is no exception but for Kerala and Pondicherry (shown in light green in Figure 4) where the sex ratio is just greater than unity (1058 and 1001 respectively).<br /><br /><br /><a href="http://photos1.blogger.com/blogger/3045/504/1600/mi04018c.jpg"><img style="DISPLAY: block; MARGIN: 0px auto 10px; CURSOR: hand; TEXT-ALIGN: center" alt="" src="http://photos1.blogger.com/blogger/3045/504/320/mi04018c.jpg" border="0" /></a><br /><br />Figure 4: Sex Ratio (2001)<br /><br />Delhi is in such a sorry state of affairs with a sex ratio of 821 females per thousand males. Who knows? The recent events in the capital city that have tarnished the pro women image of India in the international society could be an indication of this skewed sex ratio. Instead of merely blaming female foeticide, a host of social, health and environmental factors need to be brought under the microscope, if the skewed sex ratio has to be set right.<br /><br />Literacy<br />Literacy is an important indicator of social development. A person who can read and write with understanding in any language is treated as literate. A quick analysis of the states of India using GIS shows that Kerala tops with 90.92 percent (Figure 5). But an analysis of the female literacy rate shows that in some of the states female literacy is not even close to fifty percent. A classic example is Bihar whose history boasts of seat of knowledge like Nalanda University however has an overall literacy of only 47 percent with a female literacy rate of 33 percent.<br /><br /><a href="http://photos1.blogger.com/blogger/3045/504/1600/mi04018d.jpg"><img style="DISPLAY: block; MARGIN: 0px auto 10px; CURSOR: hand; TEXT-ALIGN: center" alt="" src="http://photos1.blogger.com/blogger/3045/504/320/mi04018d.jpg" border="0" /></a><br /><br />Figure 5: Literacy Rate (2001)<br /><br />A quick thematic analysis to see if atleast 50% of the females are literate shows that out of 35 only 28 pass the 50 percent mark (shown in light green-Figure 6) and in 7 states/ union territories (shown as red in Figure 6) less than 50 percent of the females are literate. It is necessary to increase the female literacy rate for several reasons including better population control, increased female life expectancy, better childcare etc.<br /><br /><br /><a href="http://photos1.blogger.com/blogger/3045/504/1600/mi04018e.jpg"><img style="DISPLAY: block; MARGIN: 0px auto 10px; CURSOR: hand; TEXT-ALIGN: center" alt="" src="http://photos1.blogger.com/blogger/3045/504/320/mi04018e.jpg" border="0" /></a><br /><br />Figure 6: Female Literacy Rate (2001)<br /><br />Urbanization<br />Urbanization is the increase in the proportion of people living in towns and cities. Urbanization occurs because people move from rural areas (countryside) to urban areas (towns and cities). Rural to urban migration is happening on a massive scale due to population pressure and lack of resources in rural areas. These are critical 'push' factors. The rapid pace of urbanization is inescapable and irreversible. It demands for increased utilization of the limited infrastructure in the cities. Failure to make note of this could lead to the break down of various infrastructure facilities, civic functions and depletion of natural resources like ground water in the cities. Delhi tops the list in terms of urbanization at 93.01percent. A grid thematic analysis clearly shows the urbanized areas by red spots (Figure 7).<br /><br /><br /><a href="http://photos1.blogger.com/blogger/3045/504/1600/mi04018f.jpg"><img style="DISPLAY: block; MARGIN: 0px auto 10px; CURSOR: hand; TEXT-ALIGN: center" alt="" src="http://photos1.blogger.com/blogger/3045/504/320/mi04018f.jpg" border="0" /></a><br /><br />Figure 7: Urbanization (2001)<br /><br />Conclusion<br />Well we did hear what India had to tell us in the language of GIS on its state of affairs. The list of such GIS analysis in planning is really endless. GIS could not only be the possible key to unlock the latent problems in our cities and in our planning techniques but also the “key to unlocking a nations potential”. GIS could be the mirror that could reflect the state of the people contained in the cities of India. How they live? Where they live? What they do? More importantly the quality of life in the cities. GIS may not be the paragon of all virtues but it could be important as one of several measures for addressing the problems confronting the urban planners of today.<br /><br />Of what use could be any technology if it cannot reach and benefit the common public suffering in the veritable concrete jungles, the so-called cities and the remote villages of India? It is a pity that it is not the people of the country who are starved but our planners and decision makers who are starved for want of information.<br /><br />Multiplicity of institutions and duplication of data at various levels have marred the desired results. Most of the time is spent in making one department or the other as the scapegoat when the plans fail to give the desired results. Let us not get mired in history and "throw out the baby (GIS) with the bathwater". Constructive and creative suggestions are the need of the hour. Let us work towards finding ways and means of applying GIS for urban problems in a rational and a logical way.<br /><br />Let the common man talk to our cities in the language of GIS. Let the common man understand what our cities, towns and villages have to say them. Let us empower them with Geospatial Democracy. Let them decide what the priorities are and let them make meaningful choices! A final thought: Let us empower the hoi polloi with the fundamental right to Geospatial Democracy before we hear the hoi polloi say: <strong>“Geospatial Democracy is my birth right and I shall have it !”</strong></p><p><strong>Thanks to Census of India for the data</strong></p>Saint GIShttp://www.blogger.com/profile/03296153994051314633noreply@blogger.com0tag:blogger.com,1999:blog-7854142.post-1114763308920627252005-04-29T01:25:00.000-07:002005-04-29T01:28:28.923-07:00GIS IS IN MY BLOOD<p><br />GIS IS IN MY BLOOD!<br />S.Raghavendran1<br /><br />1 GIS Analyst<br />Email: <a href="mailto:srg_gis@yahoo.com">srg_gis@yahoo.com</a></p><p><br />Give Me Blood! I Promise You Freedom!! This was the call by Netaji Subhash Chandra Bose at a rally of Indians in Burma, July 4, 1944 during India’s struggle for independence. Now we stand in an IT dominant era with tech savvy society, where most things happen at the click of a mouse. Phone calls to friends and relatives with a great deal of anxiety are quite common during medical emergencies arising out of accidents or illness or other such medical conditions. Any help from unknown quarters comes as a big relief. But one is often caught scrambling during such critical times for much-needed information, the information regarding blood donors. Those looking out for blood donors during such medical emergencies would understand the nightmare of not getting the required information at the appropriate time. Everyday thousands of lives are lost for want of blood at the appropriate time. When lives are at stake, every second counts and words cannot describe the plight of the near and dear ones, running from pillar to post in locating the blood donors. Geography or GIS for that matter has never been so closer offering a helping hand in our day-today life. Though GIS is being applied for logistics in transporting the accident victims to the appropriate hospital from the accident spot, evidences are not available regarding applying GIS for blood donors and receivers. In the recent past, help is available on the net: http://www.indianblooddonors.com a Nagpur-based website founded by Khusroo Poacha, that has information on blood donors across the country.<br /><br />This paper is a proof-of-concept for the City of Chennai, to show how GIS can be used to quickly locate the blood donors of the required blood group nearer to a given hospital location on a GIS based map of Chennai City. The proof-of-concept is a GIS map based interface, a linkage of database of the blood donors and the base map of Chennai City, thereby creating a searchable interface for those in search of blood donors. It also showcases how clustering techniques can be used along with GIS to reduce the precious time lost in prioritizing which blood donors to contact. Right information, at the Right time, in the Right form – GIS could be the possible way!<br />The objective here is:<br /><br />To create awareness on the need to integrate GIS into the daily lives of the hoi polloi at various levels. </p><p><br />To show how GIS can effectively be used in a myriad of ways to locate the blood donors quickly at the critical hour, thereby saving valuable human lives.<br /><br />Of what use could be any technology if it cannot reach and benefit the common public suffering in the veritable concrete jungles, the so-called cities and the remote villages of India? It is a pity that technologies such as GIS and many such applications do not see the light of the day!<br /><br />A final thought: With such a GIS application in place, I am sure to say “GIS is in my blood…Give me GIS and I promise you blood !”</p>Saint GIShttp://www.blogger.com/profile/03296153994051314633noreply@blogger.com0tag:blogger.com,1999:blog-7854142.post-1091606003735529702004-08-04T00:52:00.000-07:002004-08-04T00:55:47.100-07:00FME<div align="justify">Geography or GIS for that matter has never been so closer to our lives. Accurate geospatial data holds the key to several of the problems confronting our planners and decision makers today. The concept of Geospatial Data Infrastructure was first conceived in Canada in the early 1980s. There after other countries like USA, UK, Holland, Australia and Malaysia joined the race. Of late with the setting up of National Geospatial Data Infrastructure (NGDI) in India, the importance of geospatial data and the need to have a geospatial data infrastructure similar to any other infrastructure has increased manifold. In this cyber savvy era of rapid transition, government agencies and other organizations are required to provide quick response to natural disaster, environmental crises and other such issues. The information needed to make accurate decisions depend on the availability of accurate geospatial data. This underlines the critical need to have a Geospatial Data Infrastructure at the national level. This is easier to be said than realized. Yes, this is no less to a Herculean task. There are several hurdles in the way even before we even can see an iota of this being accomplished. Starting from the basic problems like the maps being not upto date, non availability of maps to the complicated ones like missing projection system, scale discrepancies etc. But this is not the end of all troubles. As it is rightly said “one size never fits all”. Blame it on the technology or blame it on the file formats, even if the geospatial data were readily available, they are in multitude file formats. But many a time this is a very serious bottleneck in the process of building a geospatial data infrastructure as evident from the experiences across the globe. Data Interoperability has long been a burning issue in the GIS community. For many years, sharing data between systems have always been difficult with many organizations having their data locked in proprietary formats. Thanks to FME (Feature Manipulation Engine): a Spatial ETL (Extract, Transform, and Load) technology from Safe Software, Inc., founded in 1993 in Canada. With FME “GIS file formats don’t matter”. Every GIS file format for that matter has its own advantages and limitations. With the OGC (Open GIS Consortium) gaining momentum in coming up with the standardization of GIS file format, we still have a long way to go. Solving the format problem alone however does not solve the GIS interoperability issue. The core technology of FME lies not only in its ability to break the format barrier, but also in its ability to perform a data model conversion at the same time. By virtue of the way in which data is represented varies greatly from system to system, a simple format A to format B translation is often not enough. What truly distinguishes FME from all others is its ability to perform data model transformations at the same time when performing the translation. FME provides a "thick pipe" connection between systems that allows for significant data model restructuring to be performed during the translation. FME offers two kinds of data model translations. The first is called generic, also called thin-pipe translation where the data is automatically moved from one GIS vendor product to another. This many a time adds little or no value to the data but provides a quick and easy way to get data from one system to the other. The second is called semantic, also called thick pipe, translation in which case users make use of our GUI-based FME Workbench translation and transformation development environment. Within this environment, users can restructure data, combine data from different data sources and formats all at once. Workbench is the environment that really makes FME be the ETL tool that it is. FME enables users to see their data models before and after the transformation, as well as the steps taken during the transformation, is critical in many situations. FME has seven different suites, each suite catering to the multifarious needs of its users. All of these 7 suites have three core components. FME Universal Translator: powerful data translation software with a drag-and-drop interface. Users can easily transfer and save data into as many as 100 different formats (including the OGC ones) with accuracy. When users need to customize the translation of their data, they rely upon FME Workbench: A point-and-click interface makes performing very sophisticated processing tasks a breeze. FME Universal Viewer: This useful utility allows quick viewing of data formats. Users can preview translation data (attributes and geometry), before performing translations using Workbench or Universal Translator. It is an ideal for previewing data. FME supports over 2000 coordinate systems based on a variety of projections, ellipsoids and datum. “SpatialDirect” another flagship product from SAFE is for users to retrieve data over the Internet/Intranet in the data format and projection of their choice.
<br />The subject matter of this paper in brevity is to demonstrate how FME can efficiently handle this burning issue of GIS interoperability, a major hurdle in building a geospatial data infrastructure and to drive home the point that in this “SAFE” route to GIS interoperability, “GIS file formats don’t matter!” </div>Saint GIShttp://www.blogger.com/profile/03296153994051314633noreply@blogger.com0