SRAI (Spatial Representations for AI) - Python library simplifying Geospatial Machine Learning

What is it about?

Geospatial Machine Learning is a growing domain of research that combines geospatial data and machine learning to draw insights from the surrounding world. The publication introduces a new, fully open-source Python package called Spatial Representations for AI (SRAI in short). The library simplifies access to open-source geospatial data and integrates many geo-related algorithms with a unified API. It includes tools for downloading geospatial data split a given area into micro-regions using multiple algorithms and train an embedding model using various architectures Our main goal in developing such a library is to make geospatial data processing, especially Geospatial Machine Learning, easier and more accessible for machine learning practitioners and GIS experts. We believe that by making it easy to use and share geospatial data and models, we can encourage more people to utilize geospatial data in their solutions and improve the maturity of the GeoAI domain.

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Photo by NASA on Unsplash

Photo by NASA on Unsplash