Tutorial¶

This tutorial builds H3 cells for Rwanda and attaches WorldPop population to each cell. The result is a view.

The first run downloads the country's population raster into the data store. That can take a few minutes. Later runs read the stored files. WorldPop does not need an API key.

Build the view¶

from gigaspatial import H3ViewGenerator

zones = H3ViewGenerator(source="RWA", resolution=6)
view = zones.map_wp_pop(country="RWA")
print(view.head())

source is the country the cells cover. resolution=6 is the H3 size: about 36 km² per cell. map_wp_pop loads the WorldPop raster for that country and sums it onto the cells. view is a table of cells with a population column and a geometry.

S2ViewGenerator and MercatorViewGenerator follow the same pattern: construct them with a country, then call map_wp_pop.

What happened¶

A handler acquired the WorldPop files and stored them. The generator mapped that dataset onto zones. The view is those zones with population attached. That attachment is enrichment.

The next pages name those pieces, then show other uses:

• Datasets: handlers, fetchers, and cropping to a source
• Points and nearest buildings
• Processing a raster or a table, when you want the files themselves rather than a view