crop
crop#
- crop(xds: typing.Union[str, xarray.core.dataarray.DataArray, xarray.core.dataset.Dataset, rasterio.io.DatasetReader], shapes: typing.Union[geopandas.geodataframe.GeoDataFrame, shapely.geometry.polygon.Polygon, list], nodata: typing.Optional[int] = None, **kwargs) -> (<class 'numpy.ma.core.MaskedArray'>, <class 'dict'>)[source]#
Cropping a dataset: setting nodata outside of the given shapes AND cropping the raster to the shapes extent.
Overload of rioxarray.clip function in order to create a masked_array.
>>> raster_path = "path/to/raster.tif" >>> shape_path = "path/to/shapes.geojson" # Any vector that geopandas can read >>> shapes = gpd.read_file(shape_path) >>> xds2 = crop(raster_path, shapes) >>> # or >>> with rasterio.open(raster_path) as dst: >>> xds2 = crop(dst, shapes) >>> xds1 == xds2 True
- Parameters
xds (PATH_XARR_DS) – Path to the raster or a rasterio dataset or a xarray
shapes (Union[gpd.GeoDataFrame, Polygon, list]) – Shapes with the same CRS as the dataset (except if a
GeoDataFrame
is passed, in which case it will automatically be converted)nodata (int) – Nodata value. If not set, uses the ds.nodata. If doesnt exist, set to 0.
**kwargs – Other rioxarray.clip options
- Returns
Cropped array as a xarray
- Return type
XDS_TYPE