converter.py 文件源码

def get_tile_geometry(path, origin_espg, tolerance=500):
    """ Calculate the data and tile geometry for sentinel-2 tiles """

    with rasterio.open(path) as src:

        # Get tile geometry
        b = src.bounds
        tile_shape = Polygon([(b[0], b[1]), (b[2], b[1]), (b[2], b[3]), (b[0], b[3]), (b[0], b[1])])
        tile_geojson = mapping(tile_shape)

        # read first band of the image
        image = src.read(1)

        # create a mask of zero values
        mask = image == 0.

        # generate shapes of the mask
        novalue_shape = shapes(image, mask=mask, transform=src.affine)

        # generate polygons using shapely
        novalue_shape = [Polygon(s['coordinates'][0]) for (s, v) in novalue_shape]

        if novalue_shape:

            # Make sure polygons are united
            # also simplify the resulting polygon
            union = cascaded_union(novalue_shape)

            # generates a geojson
            data_shape = tile_shape.difference(union)

            # If there are multipolygons, select the largest one
            if data_shape.geom_type == 'MultiPolygon':
                areas = {p.area: i for i, p in enumerate(data_shape)}
                largest = max(areas.keys())
                data_shape = data_shape[areas[largest]]

            # if the polygon has interior rings, remove them
            if list(data_shape.interiors):
                data_shape = Polygon(data_shape.exterior.coords)

            data_shape = data_shape.simplify(tolerance, preserve_topology=False)
            data_geojson = mapping(data_shape)

        else:
            data_geojson = tile_geojson

        # convert cooridnates to degrees
        return (to_latlon(tile_geojson, origin_espg), to_latlon(data_geojson, origin_espg))