If you wish to install RSGISLib, ARCSI and the other tools we make available using the conda Python package manager then this video provides a complete run through of the process. Note, the recommended options and versions have been updated from the video so take those from the following commands:

I would now recommend that you use the mamba command, rather than conda for the installation as it is quicker and easier. Mamba is a reimplmentation of conda using C++ rather than python. Therefore, all you need to do is to install mamba into your conda environment (command below) and then replace conda with mamba in all the commands you run.

conda install mamba -n base -c conda-forge

Commands for create an environment and installing RSGISLib, ARCSI etc.

# Create a New Environment
conda create -n osgeo-env-v1 python=3.10

# Change to the environment
source activate osgeo-env-v1

# Install RSGISLib and ARCSI
mamba install -c conda-forge rsgislib arcsi tuiview

# Install RSGISLib other useful packages:
mamba install -c conda-forge rsgislib h5py parallel scikit-learn scikit-image matplotlib pandas geopandas statsmodels scipy rasterio shapely networkx sqlalchemy pycurl seaborn numba pip rtree pygal jupyterlab pysal libpysal esda pyyaml netcdf4 xarray fiona psycopg2 ipywidgets contextily cvxopt feather-format pyod xlsxwriter openpyxl SALib tuiview

# Some extras only avilable via pip
pip install matplotlib_scalebar pysptools

Docker and Singularity

The easiest way to install our software is through Docker or Singularity, as shown below:

# Pull the docker image to your local system
docker pull petebunting/au-eoed

# Pull the docker image using singularity
singularity build au-eoed.sif docker://petebunting/au-eoed

Software We Maintain


The remote sensing and GIS software library, tools for processing image and vector datasets using Python.


A set of tools for the automated productions of Analysis Ready Optical Data (ARD). Supports Landsat and Sentinel-2.


Software for creating an EO based monitoring system.


HDF5 based image file format with GDAL driver.


HDF5 based file format for LiDAR data and tools for processing LiDAR datasets.


Python module for reading, writing and processing LiDAR datasets.


Lightweight Earth Observation (EO) image viewer.

Other Software

Accessing and Storing Data

Visualisating Data

Useful Python Modules

Machine Learning Python Modules