The AiTLAS toolbox (Artificial Intelligence Toolbox for Earth Observation) includes state-of-the-art machine learning methods for exploratory and predictive analysis of satellite imagery as well as repository of AI-ready Earth Observation (EO) datasets. It can be easily applied for a variety of Earth Observation tasks, such as land use and cover classification, crop type prediction, localization of specific objects (semantic segmentation), etc. The main goal of AiTLAS is to facilitate better usability and adoption of novel AI methods (and models) by EO experts, while offering easy access and standardized format of EO datasets to AI experts which allows benchmarking of various existing and novel AI methods tailored for EO data.

Getting started

AiTLAS Introduction https://youtu.be/-3Son1NhdDg

AiTLAS Software Architecture: https://youtu.be/cLfEZFQQiXc

AiTLAS in a nutshell: https://www.youtube.com/watch?v=lhDjiZg7RwU

AiTLAS examples:

• Land use classification with multi-class classification with AiTLAS: https://youtu.be/JcJXrMch0Rc
• Land use classification with multi-label classification: https://youtu.be/yzHkEMbDW7s
• Maya archeological sites segmentation: https://youtu.be/LBFY4pCfzOU
• Visualization of learning performance: https://youtu.be/wjMfstcWBSs

Installation

The best way to install aitlas, is if you create a virtual environment and install the requirements with pip. Here are the steps:

• Go to the folder where you cloned the repo.
• Create a virtual environment

conda create -n aitlas python=3.8

• Use the virtual environment

conda activate aitlas

• Before installing aitlas on Windows it is recommended to install the following packages from Unofficial Windows wheels repository:

pip install GDAL-3.4.1-cp38-cp38-win_amd64.whl 
pip install Fiona-1.8.20-cp38-cp38-win_amd64.whl
pip install rasterio-1.2.10-cp38-cp38-win_amd64.whl

• Install the requirements

pip install -r requirements.txt

And, that's it, you can start using aitlas!

python -m aitlas.run configs/example_config.json

Citation

For attribution in academic contexts, please cite this work as

@article{dimitrovski2022aitlas,
      title={AiTLAS: Artificial Intelligence Toolbox for Earth Observation}, 
      author={Ivica Dimitrovski and Ivan Kitanovski and Panče Panov and Nikola Simidjievski and Dragi Kocev},
      year={2022},
      journal={arXiv preprint arXiv:2201.08789},
}