High versatility and potential of spatial data analysis with R programmin g

Abstract

R is a free programming language that has been widely used by statisticians and data miners for statistical software development and data analysis. The number of contributed packages for handling and analyzing spatial data has significantly increased over the last 15 years. This paper reviews the potential for spatial data analysis using R programming. The packages related mainly to geographic information system (GIS), such as sp, sf, rgdal, raster, ggmap, tmap, gstat, and RQGIS, are selected for specific tasks along with useful examples. By referring to these examples, new R users can examine how R handles spatial data and what types of problems it can be applied to. R provides several functions that can import, export, and manipulate vector and raster data. For spatial data analysis, R acts as a GIS tool because it can perform GIS procedures effectively from basic to advanced levels. For visualization and mapping, R can produce various 2D or 3D maps from spatial data using either customized or flexible approaches. A user community needs to be developed to enhance the benefits of R programming for the public and private sectors in Japan, particularly in the field of geoinformatics.