To be able to use spatial data and make decisions based on it, we need to be able to visualize it (statically, interactively, through web etc).
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R has increasing functionality for analyzing spatial data, but so has GRASS GIS, QGIS and/or SAGA GIS. This course explains how to use GIS software from within R for statistical geocomputing.
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Several R packages exists that allows loading spatial and spatiotemporal data and which provide structures, validity control and functions. One of the packages with the highest number of dependencies is the sp package.
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Machine Learning Algorithms are increasingly interesting for analyzing spatial data, especially to derive spatial predictions / for spatial interpolation and to detect spatial patterns
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GRASS GIS is a general purpose Free and Open Source geographic information system (GIS) that offers raster, 3D raster and vector data processing support
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