# AiTLAS: Artificial Intelligence Toolbox for Earth Observation

Source: [AiTLAS: Artificial Intelligence Toolbox for Earth Observation](<https://www.sota2.com/research/paper/68fa6ba61e209131cea2f929>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T23:54:05.632Z

Authors: Ivica Dimitrovski, Ivan Kitanovski, Pan\\v{c}e Panov, Nikola Simidjievski, Dragi Kocev

Published: 2022-01-21T17:10:14.000Z

## Abstract

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 further allows benchmarking of various existing and novel AI methods tailored for EO data.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2201.08789>)

[PDF](<https://arxiv.org/pdf/2201.08789.pdf>)