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A Docker image packaging Dr Pete Buntings Python Atmospheric and Radiometric Correction of Satellite Imagery (ARCSI) software (

This image is based on the official continuumio miniconda python 3.4 release, minimal optimisation and installation of arcsi + dependencies using the conda package manager. Paths and Debian libraries required for proper functioning of ARCSI are updated.

Warning - The resulting image is rather large


To set up a ARCSI Docker container on your system, first ensure you have Docker installed; follow the instructions at

To use the image, either pull the latest trusted build from by doing this:

docker pull epmorris/docker-arcsi

or build the image yourself like this:

docker build -t epmorris/docker-arcsi

Note: The 'build it yourself' option above will build from the develop branch wheras the trusted builds are against the master branch.


To run a container and get help on ARCSI commandline options do:

docker run -t epmorris/docker-arcsi -h

To mount a local volume with images, such as freely available USGS Landsat 8 images (available via, apply radiometric calibration and apply atmospheric correction, for example 'top-of-atmosphere' correction, do:

docker run -i -t \

-v <path_to_local_landsat_folder>:<path_to_local_landsat_folder> \

epmorris/docker-arcsi \ \
-s ls8 \
-f GTiff \
-p RAD TOA \
-i <path_to_local_landsat_folder><landsat_metadata_file>
-o <path_to_local_landsat_folder>

Flag -v tells Docker to mount the specified local volume (in the example this is simply cloned into the container). Replace <path_to_local_landsat_folder> with an absolute path on your filesystem. See Docker user guide, particularily how to add data volumes . The folder should contain the uncompressed landsat GeoTiff image files and metadata file. At present I did not work out how to include non-local media, such as USBsticks.

Including a command after the container tells Docker to run that command via Bash, here, which requires various options/flags to be defined (see -h). In the example -s defines the sensor, -f the output file format, -p the type of processing, -i the path to a metadata file, -o product output path (in this case the original folder). To try out the command remember to change <landsat_metadata_file> to the relative path of the landsat metadata file (i.e., LC82020352014224LGN00_MTL.txt).

See by Dan Clewley and Pete Bunting for a good tutorial on how to use ARCSI via the command line to do atmospheric correction of Landsat images. Support for ARCSI is available via and Finally, thanks to the arcsi and rsgislib authors for making their great code publically available.

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