Data Science, Machine Learning, GIS, Python, R, Remote Sensing, land and water science, and others
Spatial Data Science integrates Geographic Information System (GIS) and Data Science. This article briefly describes Geospatial or Spatial Data Science in my point of view in simple way. Of course there are may other perspectives of Spatial Data Science. GIS contains 3 steps. They are data input, processing, and visualization/output.
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Working with GIS is fun. Preparing, analysing, visualizing, and concluding geospatial data are interesting for those have passion in it. But, doing repeated and monotonous technical jobs can be boring or even frustrating, especially if the huge load of work must be completed in a short time. Some human errors can happen. However, if the work is repeated, it can be automated using Model Builder, Batch Files, or Python. In this article, geospatial data processing is the focus of the discussion.
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Data Science and GIS 