Geospatial data is becoming increasingly used to solve numerous ‘real-life’ problems (check out some examples here.) In turn, R is becoming a powerful open-source solution to handle this type of data, currently providing an exceptional range of functions and tools for GIS and Remote Sensing data analysis. In particular, raster ...

Background In this post, the ninth of the geospatial processing series with raster data, I will focus on interpolating and modeling air surface temperature data recorded at weather stations. For this purpose I will explore regression-kriging (RK), a spatial prediction technique commonly used in geostatistics that combines a regression of ...