SRAI: Towards Standardization of Geospatial AI

• URL: http://arxiv.org/abs/2310.13098v2
• Date: Mon, 23 Oct 2023 15:03:50 GMT
• Title: SRAI: Towards Standardization of Geospatial AI
• Authors: Piotr Gramacki, Kacper Le\'sniara, Kamil Raczycki, Szymon Wo\'zniak, Marcin Przymus, Piotr Szyma\'nski
• Abstract summary: 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. Srai is fully open-source and published under Apache 2.0 licence.
• Score: 4.246621775040508
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• 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.

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