Merge branch 'main' of github.com:worldbank/GOSTurban into update-docs

docs/_toc.yml

@@ -7,7 +7,6 @@ parts:
   - caption: Documentation
     chapters:
       - file: api/GOSTurban.rst
-      - file: CONTRIBUTING
   - caption: Novel Urbanization
     chapters:
       - file: novel_context

docs/conf.py

@@ -24,6 +24,7 @@
     "sphinx_jupyterbook_latex",
     "sphinx.ext.napoleon",
     "sphinxcontrib.apidoc",
+    #"nbsphinx"
 ]
 external_toc_exclude_missing = True
 external_toc_path = "_toc.yml"

docs/notebooks

@@ -0,0 +1 @@
+../notebooks

notebooks/Replications/URB_NovelUrbanization.py

@@ -0,0 +1,56 @@
+import sys, os, shutil, requests
+import rasterio
+
+import pandas as pd
+import geopandas as gpd
+import numpy as np
+
+import GOSTurban.UrbanRaster as urban
+
+def download_pop_file(url, filename):
+    # Open the url
+    r = requests.get(url)
+    # Set decode_content value to True, otherwise the downloaded image file's size will be zero.
+    r.raw.decode_content = True
+    # Open a local file with wb ( write binary ) permission.
+    with open(filename,'wb') as f:
+        shutil.copyfileobj(r.raw, f)
+
+def main(iso3, out_folder):
+    # download the population data
+    wp_url = f'https://data.worldpop.org/GIS/Population/Global_2000_2020_1km/2020/{iso3.upper()}/{iso3.lower()}_ppp_2020_1km_Aggregated.tif'
+    print (wp_url)
+    if not os.path.exists(out_folder):
+        os.makedirs(out_folder)
+    out_file = os.path.join(out_folder, f'{iso3}_ppp_2020_1km_Aggregated.tif')
+    out_urban = os.path.join(out_folder, "urban_extents.geojson")
+    out_hd_urban = os.path.join(out_folder, "hd_urban_extents.geojson")
+
+    try:
+        if not os.path.exists(out_file):
+            download_pop_file(wp_url, out_file)
+    except:
+        print(f"Could not download national population data for {iso3} from {wp_url}")
+        print("If you can manually download to the defined out_folder, the script will run")
+    if os.path.exists(out_file):
+        inR = rasterio.open(out_file)   
+        urban_calculator = urban.urbanGriddedPop(inR)
+        urban_extents = urban_calculator.calculateUrban(
+            densVal=300, totalPopThresh=5000, smooth=False, queen=False
+        )
+
+        hd_urban_extents = urban_calculator.calculateUrban(
+            densVal=1500,
+            totalPopThresh=50000,
+            smooth=True,
+            queen=True,  # high density extents use queen's case contiguity, and are smoothed            
+        )
+
+        urban_extents.to_file(out_urban, driver="GeoJSON")
+        hd_urban_extents.to_file(out_hd_urban, driver="GeoJSON")
+
+if __name__ == "__main__":
+    iso3 = sys.argv[1]
+    out_folder = sys.argv[2]
+    main(iso3, out_folder)
+