As a Geospatial data scientist, 2019 brought some new tools that made my life easier. In this post, I am sharing the best of these new additions in the Python ecosystem and some resources to get you started.
You will find tools that accelerate your Geospatial data science pipelines using GPU, advanced Geospatial Visualization tools and some simple, useful Geoprocessing tools. I hope you will find one or two from the list that can help you. 1. cuSpatial: GPU-Accelerated Spatial and Trajectory Data Management and Analytics Library It is part of open-sourced libraries with GPU accelerated data science pipelines entirely carried out in the GPU.