Journal of Remote Sensing & GIS

Abstract

Interfacing Grass-GIS and R: Road Descriptive Statistical Representation based on Slope

Kumari Pritee and Rahul Dev Garg

As lots of GIS (Geographic Information systems) applications for statistical purposes are available in the market but still there is lots of demand of integration of GRASS-GIS i.e., Geographic Resources Analysis support GIS with the R statistical package. Many researchers always want to explore, analyse, complex analysis of spatial data with statistical problems and dealing with large areas in less amount of time and memory within individual software but this is not possible without integration. However, the integration of GRASS-GIS and R statistical package play a very important role to fulfil all needs related to computation, analyse, retrieve, image processing, graphics production and query spatial data. GRASS is open source software freely available, used for data management, analysis of geospatial data, spatial modelling with visualization whereas R (Open Source Package) enables all statistical environments with better quality plots providing linear or non-linear modelling, time series analysis with classification and clustering. In this paper, GRASS-GIS i.e., GIS subsystem act as a simple interface for R i.e., statistical computing subsystem for both raster and vector spatial data which provides commands to GRASS program via R system () function. Integration also enables all R plotting and analytical functions i.e., kriging prediction; kernel density pattern estimation etc. and proves very beneficial with the perception of research and educational purposes. It is also capable to provide introductory knowledge of both open software’s packages with their flexibility, robustness capability. This paper also introduces an example of classification of roads on the basis of slope via box plot representation by interfacing R in GRASS Environment.