xarray.open_rasterio(filename, parse_coordinates=None, chunks=None, cache=None, lock=None, **kwargs)[source]#

Open a file with rasterio.

Deprecated since version 0.20.0: Deprecated in favor of rioxarray. For information about transitioning, see: https://corteva.github.io/rioxarray/stable/getting_started/getting_started.html

This should work with any file that rasterio can open (most often: geoTIFF). The x and y coordinates are generated automatically from the file’s geoinformation, shifted to the center of each pixel (see “PixelIsArea” Raster Space for more information).

  • filename (str, rasterio.DatasetReader, or rasterio.WarpedVRT) – Path to the file to open. Or already open rasterio dataset.

  • parse_coordinates (bool, optional) – Whether to parse the x and y coordinates out of the file’s transform attribute or not. The default is to automatically parse the coordinates only if they are rectilinear (1D). It can be useful to set parse_coordinates=False if your files are very large or if you don’t need the coordinates.

  • chunks (int, tuple or dict, optional) – Chunk sizes along each dimension, e.g., 5, (5, 5) or {'x': 5, 'y': 5}. If chunks is provided, it used to load the new DataArray into a dask array.

  • cache (bool, optional) – If True, cache data loaded from the underlying datastore in memory as NumPy arrays when accessed to avoid reading from the underlying data- store multiple times. Defaults to True unless you specify the chunks argument to use dask, in which case it defaults to False.

  • lock (False, True or threading.Lock, optional) – If chunks is provided, this argument is passed on to dask.array.from_array(). By default, a global lock is used to avoid issues with concurrent access to the same file when using dask’s multithreaded backend.


data (DataArray) – The newly created DataArray.