@@ -198,19 +238,7 @@ export default function Results(props) {
Demographics of the impacted area:
-
-
Population by race
-
-
- {populations.map(([group, count]) => (
-
- | {group} |
- {count} |
-
- ))}
-
-
-
+ {populationTable}
{/*
*/}
{povertyPar}
diff --git a/scripts/get_building_footprints.py b/scripts/get_building_footprints.py
new file mode 100644
index 0000000..9b963c2
--- /dev/null
+++ b/scripts/get_building_footprints.py
@@ -0,0 +1,55 @@
+"""
+Based on https://planetarycomputer.microsoft.com/dataset/ms-buildings#Example-Notebook
+The resulting GPKG is hosted on GCS natcap-urban-online-datasets
+"""
+
+import subprocess
+
+import dask_geopandas
+import deltalake
+import mercantile
+import pystac_client
+import planetary_computer
+import pygeoprocessing
+import shapely
+
+from osgeo import osr
+
+catalog = pystac_client.Client.open(
+ "https://planetarycomputer.microsoft.com/api/stac/v1",
+ modifier=planetary_computer.sign_inplace,
+)
+collection = catalog.get_collection("ms-buildings")
+
+srs = osr.SpatialReference()
+srs.ImportFromEPSG(4326)
+target_proj_wkt = srs.ExportToWkt()
+base_info = pygeoprocessing.get_raster_info('../appdata/lulc_overlay_3857.tif')
+bbox = pygeoprocessing.transform_bounding_box(
+ base_info['bounding_box'],
+ base_info['projection_wkt'],
+ target_proj_wkt
+)
+print(bbox)
+
+asset = collection.assets['delta']
+storage_options = {
+ "account_name": asset.extra_fields["table:storage_options"]["account_name"],
+ "sas_token": asset.extra_fields["table:storage_options"]["credential"],
+}
+table = deltalake.DeltaTable(asset.href, storage_options=storage_options)
+
+quadkeys = [
+ int(mercantile.quadkey(tile))
+ for tile in mercantile.tiles(*bbox, zooms=9)
+]
+uris = table.file_uris([("quadkey", "in", quadkeys)])
+
+df = dask_geopandas.read_parquet(uris, storage_options=storage_options)
+mask = df.intersects(shapely.geometry.box(*bbox))
+data = df[mask]
+data.to_parquet('buildings.parquet')
+
+# parquet driver requires libgdal-arrow-parquet, which is only supported in gdal>=3.8
+subprocess.run(
+ ['ogr2ogr', '-f', 'GPKG', 'buildings_san_antonio.gpkg', 'buildings.parquet'])