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dask-rasterio provides some methods for reading and writing rasters in parallel using Rasterio and Dask arrays.


Read a multiband raster

>>> from dask_rasterio import read_raster

>>> array = read_raster('tests/data/RGB.byte.tif')
>>> array
dask.array<stack, shape=(3, 718, 791), dtype=uint8, chunksize=(1, 3, 791)>

>>> array.mean()
dask.array<mean_agg-aggregate, shape=(), dtype=float64, chunksize=()>
>>> array.mean().compute()

Read a single band from a raster

>>> from dask_rasterio import read_raster

>>> array = read_raster('tests/data/RGB.byte.tif', band=3)
>>> array
dask.array<raster, shape=(718, 791), dtype=uint8, chunksize=(3, 791)>

Write a singleband or multiband raster

>>> from dask_rasterio import read_raster, write_raster

>>> array = read_raster('tests/data/RGB.byte.tif')

>>> new_array = array & (array > 100)
>>> new_array
dask.array<and_, shape=(3, 718, 791), dtype=uint8, chunksize=(1, 3, 791)>

>>> prof = ... # reuse profile from tests/data/RGB.byte.tif...
>>> write_raster('processed_image.tif', new_array, **prof)

Chunk size

Both read_raster and write_raster accept a block_size argument that acts as a multiplier to the block size of rasters. The default value is 1, which means the dask array chunk size will be the same as the block size of the raster file. You will have to adjust this value depending on the specification of your machine (how much memory do you have, and the block size of the raster).


Install with pip:

pip install dask-rasterio


This project is managed by Poetry. If you do not have it installed, please refer to Poetry instructions.

Now, clone the repository and run poetry install. This will create a virtual environment and install all required packages there.

Run poetry run pytest to run all tests.

Run poetry build to build package on dist/.

Issue tracker

Please report any bugs and enhancement ideas using the GitHub issue tracker:

Feel free to also ask questions on our Gitter channel, or by email.

Help wanted

Any help in testing, development, documentation and other tasks is highly appreciated and useful to the project.

For more details, see the file


Source code is released under a BSD-2 license. Please refer to for more information.