rasterio.mask module

Mask the area outside of the input shapes with no data.

rasterio.mask.mask(dataset, shapes, all_touched=False, invert=False, nodata=None, filled=True, crop=False, pad=False, pad_width=0.5, indexes=None)

Creates a masked or filled array using input shapes. Pixels are masked or set to nodata outside the input shapes, unless invert is True.

If shapes do not overlap the raster and crop=True, a ValueError is raised. Otherwise, a warning is raised.

Parameters:

  • dataset (a dataset object opened in 'r' mode) – Raster to which the mask will be applied.

  • shapes (iterable object) – The values must be a GeoJSON-like dict or an object that implements the Python geo interface protocol (such as a Shapely Polygon).

  • all_touched (bool (opt)) – Include a pixel in the mask if it touches any of the shapes. If False (default), include a pixel only if its center is within one of the shapes, or if it is selected by Bresenham’s line algorithm.

  • invert (bool (opt)) – If False (default) pixels outside shapes will be masked. If True, pixels inside shape will be masked.

  • nodata (int or float (opt)) – Value representing nodata within each raster band. If not set, defaults to the nodata value for the input raster. If there is no set nodata value for the raster, it defaults to 0.

  • filled (bool (opt)) – If True, the pixels outside the features will be set to nodata. If False, the output array will contain the original pixel data, and only the mask will be based on shapes. Defaults to True.

  • crop (bool (opt)) – Whether to crop the raster to the extent of the shapes. Defaults to False.

  • pad (bool (opt)) – If True, the features will be padded in each direction by one half of a pixel prior to cropping raster. Defaults to False.

  • indexes (list of ints or a single int (opt)) – If indexes is a list, the result is a 3D array, but is a 2D array if it is a band index number.

Returns:

Two elements:

maskednumpy.ndarray or numpy.ma.MaskedArray

Data contained in the raster after applying the mask. If filled is True and invert is False, the return will be an array where pixels outside shapes are set to the nodata value (or nodata inside shapes if invert is True).

If filled is False, the return will be a MaskedArray in which pixels outside shapes are True (or False if invert is True).

out_transformaffine.Affine()

Information for mapping pixel coordinates in masked to another coordinate system.

Return type:

tuple

rasterio.mask.raster_geometry_mask(dataset, shapes, all_touched=False, invert=False, crop=False, pad=False, pad_width=0.5)

Create a mask from shapes, transform, and optional window within original raster.

By default, mask is intended for use as a numpy mask, where pixels that overlap shapes are False.

If shapes do not overlap the raster and crop=True, a ValueError is raised. Otherwise, a warning is raised, and a completely True mask is returned (if invert is False).

Parameters:

  • dataset (a dataset object opened in 'r' mode) – Raster for which the mask will be created.

  • shapes (iterable object) – The values must be a GeoJSON-like dict or an object that implements the Python geo interface protocol (such as a Shapely Polygon).

  • all_touched (bool (opt)) – Include a pixel in the mask if it touches any of the shapes. If False (default), include a pixel only if its center is within one of the shapes, or if it is selected by Bresenham’s line algorithm.

  • invert (bool (opt)) – Determines whether to mask pixels outside or inside the shapes. The default (False) is to mask pixels outside shapes. When invert is used with crop, the area outside the cropping window is considered selected and should be processed accordingly by the user.

  • crop (bool (opt)) – Crop the dataset to the extent of the shapes. Useful for processing rasters where shapes cover only a relatively small area. Defaults to False.

  • pad (bool (opt)) – If True, the features will be padded in each direction by one half of a pixel prior to cropping dataset. Defaults to False.

  • pad_width (float (opt)) – If pad is set (to maintain back-compatibility), then this will be the pixel-size width of the padding around the mask.

Returns:

Three elements:

masknp.ndarray of type ‘bool’

Mask suitable for use in a MaskedArray where valid pixels are marked False and invalid pixels are marked True.

out_transformaffine.Affine()

Information for mapping pixel coordinates in masked to another coordinate system.

window: rasterio.windows.Window instance

Window within original raster covered by shapes. None if crop is False.

Return type:

tuple