SRAI: Towards Standardization of Geospatial AI
Machine Learning
2023-11-22 v2
Abstract
Spatial Representations for Artificial Intelligence (srai) is a Python library for working with geospatial data. The library can download geospatial data, split a given area into micro-regions using multiple algorithms and train an embedding model using various architectures. It includes baseline models as well as more complex methods from published works. Those capabilities make it possible to use srai in a complete pipeline for geospatial task solving. The proposed library is the first step to standardize the geospatial AI domain toolset. It is fully open-source and published under Apache 2.0 licence.
Keywords
Cite
@article{arxiv.2310.13098,
title = {SRAI: Towards Standardization of Geospatial AI},
author = {Piotr Gramacki and Kacper Leśniara and Kamil Raczycki and Szymon Woźniak and Marcin Przymus and Piotr Szymański},
journal= {arXiv preprint arXiv:2310.13098},
year = {2023}
}
Comments
Accepted for the 6th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery (GeoAI 2023)