Friday is map day! Were you waiting for new maps/visualizations of Philippine population? Well, you're in luck because here's #anotherone (or four really).
This time they are maps of population per latitude (and longitude) in the Philippines. As usual, all the processing and map-making was done in QGIS.
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#GIS #QGIS #Geospatial #Philippines #Maps #Cartography #MakeBetterMaps #Population #WorldPop #gischat #DataViz #DataVisualization
The data used are a population raster (30 second/1km grid) from WorldPop and Philippine admin boundary map from GADM.
The first map visualizes the population per 30 second of latitude (or longitude) using color while the second visualizes the population as a bar/column chart.
The process was once again fairly straightforward.
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#GIS #QGIS #Geospatial #Philippines #Maps #Cartography #MakeBetterMaps #Population #WorldPop #gischat
1. Used QGIS' "Create grid" algorithm to generate a grid of 30 second (or longitudes) covering the extent of the Philippines.
2. Used the "Zonal Statistics" algorithm to compute for the sum of population (pop_sum) for each latitude (or longitude) using the WorldPop population data.
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#GIS #QGIS #Geospatial #Philippines #Maps #Cartography #MakeBetterMaps #Population #WorldPop #gischat
3a. For the first visualization:
- Apply a graduated symbology or "data-defined" symbology using the pop_sum field.
3b. For the second visualization:
- Use geometry generators and the "scale" expression with pop_sum and max(pop_sum) to create the bar/column graph.
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#GIS #QGIS #Geospatial #Philippines #Maps #Cartography #MakeBetterMaps #Population #WorldPop #gischat #DataViz #DataVisualization
BNHR.XYZ 
Donald R Noble