Search for Open Geospatial Data

Depending on the location of your site, you will have to go the respective local authority website to obtain open geospatial data. Sometimes you can get open data globally from a single source such as OpenStreetMap and the Microsoft building footprint project.

Open 3D dataset around the world¶

• https://3d.bk.tudelft.nl/opendata/opencities/

Microsoft Building Footprint Project¶

1. Go to https://github.com/microsoft/GlobalMLBuildingFootprints to have a better understanding of the dataset.

2. Install the necessary Python library and run the code to get the dataset.

   pip install pandas geopandas shapely

3. Run the following python script to grab data from the server.

   import math
   import pathlib
   import pandas as pd
   import geopandas as gpd
   from shapely.geometry import shape
   #==========================================================================================================================================================
   # region: Parameters
   #==========================================================================================================================================================
   location = 'UnitedStates' # find all the location names in this csv https://minedbuildings.blob.core.windows.net/global-buildings/dataset-links.csv
   lat = 40.345680487096764
   lng = -74.65880323282136
   res_dir = '/result/dir'
   
   # endregion
   #==========================================================================================================================================================
   # region: Functions
   #==========================================================================================================================================================
   def get_quadkey(lat: float, lng: float, zoom_lvl: int = 9) -> str:
       # https://medium.com/@biz.soing/generating-quadkeys-83aa2b8018b7
       x = int((lng + 180) / 360 * (1 << zoom_lvl))
       y = int((1 - math.log(math.tan(math.radians(lat)) + 1 / math.cos(math.radians(lat))) / math.pi) / 2 * (1 << zoom_lvl))
       quadkey = ''
       for i in range(zoom_lvl, 0, -1):
           digit = 0
           mask = 1 << (i - 1)
           if (x & mask) != 0:
               digit += 1
           if (y & mask) != 0:
               digit += 2
           quadkey += str(digit)
       return quadkey
   
   def get_footprint(location: str, lat: float, lng: float, res_dir: str, zoom_lvl: int = 9):
       # this is the name of the geography you want to retrieve. update to meet your needs
       target_quadkey = get_quadkey(lat, lng, zoom_lvl=zoom_lvl)
       target_quadkey = int(target_quadkey)
       dataset_links = pd.read_csv("https://minedbuildings.blob.core.windows.net/global-buildings/dataset-links.csv")
       loc_links = dataset_links[dataset_links.Location == location]
       for cnt, row in loc_links.iterrows():
           quadkey = row.QuadKey
           if target_quadkey == quadkey:
               print('found', quadkey)
               df = pd.read_json(row.Url, lines=True)
               df['geometry'] = df['geometry'].apply(shape)
               gdf = gpd.GeoDataFrame(df, crs=4326)
               res_path = pathlib.PurePath(res_dir,str(row.QuadKey) + '.geojson')
               gdf.to_file(str(res_path), driver='GeoJSON')
   
   # endregion
   #==========================================================================================================================================================
   # region: Main
   #==========================================================================================================================================================
   if __name__ == "__main__":
       get_footprint(location, lat, lng, res_dir)
   # endregion

4. The script will download a geojson quad by specifying the lat, lng of the space of interest.