Milan Janosov’s Post

#30𝐃𝐚𝐲𝐌𝐚𝐩𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞 - 𝐃𝐀𝐘26 - 𝐌𝐢𝐧𝐢𝐦𝐚𝐥 So now we are going minimal - and my minimalistic map is my all-time favourite, Budapest, especially its elevation contour lines collected from the Budapest Open Data Portal by ATLO The map clearly shows how the Danube split the city in half, how plain the Pest side is on the right (at around 100m above sea level), and how the Buda hills look down on it from a whopping height of 500m! 𝐂𝐨𝐝𝐞 𝐚𝐧𝐝 𝐨𝐭𝐡𝐞𝐫 𝐭𝐮𝐭𝐨𝐫𝐢𝐚𝐥𝐬: https://lnkd.in/dWmYyxhn 𝐃𝐚𝐭𝐚 𝐬𝐨𝐮𝐫𝐜𝐞: https://atlo.team/boda/ Data accessed: 2023 November 12 #gis #datascience #maps #geospatialdata #datavisualization #spatialanalytics #spatialdata #geospatial #data #ai

#30𝐃𝐚𝐲𝐌𝐚𝐩𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞 - 𝐃𝐀𝐘11 - 𝐑𝐞𝐭𝐫𝐨 Here, I am recapping a blast-from-the-past map from not so long ago, published by Towards Data Science, on the accessibility of publicly available defibrillator devices in Budapest and Vienna. The color encodes reachability time, from green (0 minutes) to red (10 minutes or more). 𝐑𝐞𝐚𝐝 𝐦𝐨𝐫𝐞: https://lnkd.in/dUkiUQWM 𝐂𝐨𝐝𝐞 𝐚𝐧𝐝 𝐨𝐭𝐡𝐞𝐫 𝐭𝐮𝐭𝐨𝐫𝐢𝐚𝐥𝐬: https://lnkd.in/dWmYyxhn #gis #datascience #maps #geospatialdata #datavisualization #spatialanalytics #spatialdata#geospatial #data #ai

#30𝐃𝐚𝐲𝐌𝐚𝐩𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞 - 𝐃𝐀𝐘27 - 𝐃𝐨𝐭 For my dot map, I again went for the Budapest Open Data Portal, which has a nice rasterised population map of Budapest (for more on population raster data, also check my tutorial on TDS)! Then, I turned each grid cell into the POI of its polygon and drew each POI with a marker with a size proportional to the number of inhabitants in the corresponding grid cell. Then, I coloured each dot red, blue, and white at random to give it this slightly old-school 3d vibe (I also have to admit, I became the biggest one of the neon red-blue colour palette this year, somewhat inspired by Star Wars). 𝐂𝐨𝐝𝐞 𝐚𝐧𝐝 𝐨𝐭𝐡𝐞𝐫 𝐭𝐮𝐭𝐨𝐫𝐢𝐚𝐥𝐬: https://lnkd.in/dWmYyxhn 𝐃𝐚𝐭𝐚 𝐬𝐨𝐮𝐫𝐜𝐞: https://atlo.team/boda/ Data accessed: 2023 November 11 #gis #datascience #maps #geospatialdata #datavisualization #spatialanalytics #spatialdata#geospatial #data #ai

The end-of-the-year countdown wouldn't be complete with one of my favourite ones ever - a road network visual of using OpenStreetMap data via the OSMNx package. Fun fact: this road network representation of Budapest has 115,539 nodes and 316,096 edges, while the length of all road segments measures 1,879 km! 𝐂𝐨𝐝𝐞 𝐚𝐧𝐝 𝐨𝐭𝐡𝐞𝐫 𝐭𝐮𝐭𝐨𝐫𝐢𝐚𝐥𝐬: https://lnkd.in/dWmYyxhn 𝐎𝐒𝐌𝐍𝐱 𝐬𝐨𝐮𝐫𝐜𝐞: https://lnkd.in/dcWjsNT3 #gis #datascience #maps #geospatialdata #datavisualization #spatialanalytics #spatialdata#geospatial #data #ai

Again a #30𝐃𝐚𝐲𝐌𝐚𝐩𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞 recap, in particular, 𝐃𝐀𝐘27 - 𝐃𝐨𝐭 For my dot map, I again went for the Budapest Open Data Portal which has a nice rasterized population map of Budapest (for more on population raster data, also check my tutorial on TDS)! Then, I turned each grid cell into the POI of its polygon, and drawed each POI with a marker with a size proprtional to the number of inhabitants in the corresponding grid cell. Then, I colored each color to red, blue, and white at random to give it this slightly old-school 3d vibe (I also have to admit, I became the biggest one of the neon red-blue color palette this year, somewhat inspired by Star Wars). 𝐂𝐨𝐝𝐞 𝐚𝐧𝐝 𝐨𝐭𝐡𝐞𝐫 𝐭𝐮𝐭𝐨𝐫𝐢𝐚𝐥𝐬: https://lnkd.in/dWmYyxhn 𝐃𝐚𝐭𝐚 𝐬𝐨𝐮𝐫𝐜𝐞: https://atlo.team/boda/ Data accessed: 2023 November 11 #gis #datascience #maps #geospatialdata #datavisualization #spatialanalytics #spatialdata#geospatial #data #ai

#30𝐃𝐚𝐲𝐌𝐚𝐩𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞 - 𝐃𝐀𝐘3 - 𝐏𝐨𝐥𝐲𝐠𝐨𝐧𝐬 This world map shows each country as a polygon based on Natural Earth data, where each country is coloured based on its distance from the equator. This rather unusual shape is because I used the Larrivee Projection here, which was developed by Léo Larrivée in 1988 for the Canadian International Development Agency. So far, I could only figure out that it was most likely used for remote sensing, so if you know more about the science behind this distinctive design, let us know! 𝐂𝐨𝐝𝐞 𝐚𝐧𝐝 𝐨𝐭𝐡𝐞𝐫 𝐭𝐮𝐭𝐨𝐫𝐢𝐚𝐥𝐬: https://lnkd.in/dWmYyxhn 𝐒𝐨𝐮𝐫𝐜𝐞: https://lnkd.in/dAjGDafk https://lnkd.in/dYRxGbwa https://lnkd.in/ddvKSTFf Data access: 2023 Sept 18 #gis #datascience #maps #geospatialdata #datavisualization #spatialanalytics #spatialdata#geospatial #data #ai

#30𝐃𝐚𝐲𝐌𝐚𝐩𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞 - 𝐃𝐀𝐘28 - 𝐈𝐬 𝐭𝐡𝐢𝐬 𝐚 𝐜𝐡𝐚𝐫𝐭 𝐨𝐫 𝐚 𝐦𝐚𝐩? For this map /?/ chart, I recreated one of my all-time favourite visualisations, originally by Geoff Boeing. This graph shows the directedness of each city based on its road network acquired from OpenStreetMap using OSMNx. Namely, each radar plot shows the total length of road segments (measured in e.g. kilometres) pointing in certain directions marked by the bars. As an example, I picked 48 large European cities. Have you visited any of them? 𝐂𝐨𝐝𝐞 𝐚𝐧𝐝 𝐨𝐭𝐡𝐞𝐫 𝐭𝐮𝐭𝐨𝐫𝐢𝐚𝐥𝐬: https://lnkd.in/dWmYyxhn 𝐈𝐧𝐬𝐩𝐢𝐫𝐚𝐭𝐢𝐨𝐧: https://lnkd.in/dmHPvUR3 Data accessed: 2023 November 24 #gis #datascience #maps #geospatialdata #datavisualization #spatialanalytics #spatialdata #geospatial #data #ai