implement diff res of wp data downloads

_config.py

@@ -51,15 +51,15 @@
 # In the same units as the desired_crs (e.g. degrees for EPSG:4326)
 # Cannot be equal to or less than the original resolution of the downloaded
 # data
-res = 0.05
+res = 0.01
 
 # Desired coordinate reference system
 desired_crs = "EPSG:4326"
 
 # Input shapefile parameters - field_name needs to exist in both the input
 # shapefile and the input exposure CSV file. Directly replace field_name
 # with the field of interest
-adm_level = 1
+adm_level = 3
 field_name = f"ID_{adm_level}"
 
 # Threshold for checking that sampled asset counts match original input
@@ -97,7 +97,7 @@
 wp_directory = os.path.join("data", "worldpop")
 
 # File locations - inputs
-name = "Austria"
+name = "Portugal"
 shp_file = f"Adm{adm_level}_{name}.shp"
 
 # Directory locations - outputs

download_worldpop.py

@@ -4,15 +4,18 @@
 
 
 # Parse function with grid; FIXME: Support other resolutions from WP beyond 1km
-def download_worldpop(iso, year=2020, res=1):
+def download_worldpop(iso, year=2020, res="1km"):
     ''' This function downloads a raster file of population estimates from
     WorldPop. At the moment, this will download the 2020 population estimate
     at a 1km resolution for the desired country. This can be later expanded to
     download the 100m dataset, or (where possible) a direct estimate of the
     number of buildings.'''
 
-    # Arrange url
-    url = f'ftp://ftp.worldpop.org.uk/GIS/Population/Global_2000_{year}/{year}/{iso.upper()}/{iso.lower()}_ppp_{year}.tif'
+    # Arrange url; defeault  - 1km, UN adj
+    url = f'ftp://ftp.worldpop.org.uk/GIS/Population/Global_2000_2020_1km_UNadj/{year}/{iso.upper()}/{iso.lower()}_ppp_2020_1km_Aggregated_UNadj.tif'
+    if res == "100m":
+        # If requested, use 100m, UN adj
+        url = f'ftp://ftp.worldpop.org.uk/GIS/Population/Global_2000_2020/{year}/{iso.upper()}/{iso.lower()}_ppp_{year}_UNadj.tif'
 
     # Submit request
     r = urllib.request.urlopen(url)
@@ -37,7 +40,9 @@ def download_worldpop(iso, year=2020, res=1):
     # Parse arguments (group name)
     iso = sys.argv[1]
     year = 2020
-    res = 1
+    res = "1km"
+    if len(sys.argv) > 2:
+        res = sys.argv[2]
 
     # Call function
     download_worldpop(iso, year, res)

util/geo.py

@@ -52,9 +52,15 @@ def associate_grid_to_bounds(raster, adm_level, mapped_field,
         if type(geom) == shapely.geometry.polygon.Polygon:
             geom = [geom]
         # Perform mask on raster data
+        mask_error = False
         with rasterio.open(raster) as src:
-            out_image, out_transform = rasterio.mask.mask(src, geom, crop=True)
-            no_data = src.nodata
+            # Mask to boundary
+            try:
+                out_image, out_transform = rasterio.mask.mask(src, geom, crop=True)
+                no_data = src.nodata
+            except ValueError:
+                mask_error = True
+                print_yellow(f"Could not find raster data for {adm[mapped_field]}, will skip spatial disaggregation for that boundary")
         # Extract data from masked image
         data = out_image[0]  # get first (only) band
         # Remove nodata values