microsoft / GlobalMLBuildingFootprints

Worldwide building footprints derived from satellite imagery
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Issue retreiving building footprints west of amsterdam around Schipol #109

Open virgilxw opened 1 month ago

virgilxw commented 1 month ago

I tried to run the following with a Microsoft planetary computer to get building footprints, but apparently the buildings West of Amsterdam are not showing up?

catalog = pystac_client.Client.open(
"https://planetarycomputer.microsoft.com/api/stac/v1",
modifier=planetary_computer.sign_inplace,
)
collection = catalog.get_collection("ms-buildings")

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(*buffer[0].bounds, zooms=9)
]
quadkeys

uris = table.file_uris([("quadkey", "in", quadkeys)])
uris

df = dgd.read_parquet(uris, storage_options=storage_options)

where buffer is a circle around (52.372778, 4.893611)

Get bounds

minx, miny, maxx, maxy = area_of_interest.total_bounds
min_dist = min([abs(minx-latlng[0]), abs(miny-latlng[1]), abs(maxx-latlng[0]), abs(maxy-latlng[1])])

# Create a GeoDataFrame with the specified point
gdf = gpd.GeoDataFrame(geometry=[Point(latlng[1], latlng[0])], crs=crs)

# The UTM zone number can be calculated from the lnggitude
utm_zone = int((latlng[1] + 180) / 6) + 1
# Determine the hemisphere and assign the appropriate UTM CRS
if latlng[0] >= 0:  # Northern Hemisphere
    local_utm_crs = f'EPSG:326{utm_zone:02d}'
else:  # Southern Hemisphere
    local_utm_crs = f'EPSG:327{utm_zone:02d}'

# Reproject to a local UTM CRS
gdf_utm = gdf.to_crs(local_utm_crs)

# Create a 50 km buffer around the point
buffer_circle = gdf_utm.buffer((radius) * 1000)  # Convert km to meters

buffer = buffer_circle