INTRODUCTION

GRASS (Geographic Resources Analysis Support System) is a Geographic Information System (GIS) used for data management, image processing, graphics production, spatial modelling, and visualization of many types of data. It is Free Software/Open Source released under GNU General Public License (GPL). GRASS GIS is official project of the Open Source Geospatial Foundation which was created to support the collaborative development of open source geospatial software, and promote its widespread use.

GRASS is a raster/vector GIS, image processing and graphics production system. GRASS contains over 350 programs and tools to render maps and images on monitor and paper; manipulate raster, vector, and sites data; process multi spectral image data; and create, manage, and store spatial data. GRASS uses both an intuitive windows interface as well as command line syntax for ease of operations. GRASS can interface with commercial printers, plotters, digitizers, and databases to develop new data as well as manage existing data.

GRASS supports workgroups through its Location/Mapset concept which can be set up to share data over NFS (Network File System). Keeping Locations with their underlying MAPSETs on a central server, a team can simultaneously work in the same project database. For raster data analysis, GRASS uses GDAL library and OGR library is used for vector analysis. The GRASS community maintains a Wiki page which contains getting started guides, tutorials, tips and tricks, FAQs, etc.

Many Geostatistical and GeoSpatial Data Analysis which are not supported in GRASS are possible in R. R is a language and environment for statistical computing and graphics and is a GNU project. R is an integrated suite of software facilities for data manipulation, calculation and graphical display. It includes an effective data handling and storage facility, a suite of operators for calculations on arrays, in particular matrices, a large, coherent, integrated collection of intermediate tools for data analysis, graphical facilities for data analysis and display either on-screen or on hardcopy, and a well-developed, simple and effective programming language which includes conditionals, loops, user-defined recursive functions and input and output facilities. R is flexible and powerful which performs statistical analysis along with graphics and provides scripting and interfacing that can do analysis of complex data.

R appeals differently to the different fields and is easy to use for data analysis because R has built-in commands for statistical procedures such as correlation, regression, ANOVA, various graphical procedures like histogram, box-plot, scatter plot and many more [1]. The main reason for R to be in FOSS is that its developers believe that collective and cooperative participatory approach is a proper way to fast and fair development. R software can be obtained from Comprehensive R Archive network (CRAN), which may be accessed from R project website at www.r-project.org. After the installation of R it can be initiated easily by entering R through command line. R is an interactive program that mainly works on a question and answer model. When R is ready for input then it prints “>” .To end the R session type (q) and this is why it is user friendly.

While R is a general data analysis environment, it has been extensively used for modelling and simulation. The R data analysis programming language and environment is an extensible system which can be connected directly to GRASS. R consists of a base package and extensions. R comprise packages for point pattern analysis, geostatistics, exploratory spatial data analysis and spatial econometrics. The R/GRASS interface substantially improves the geospatial analysis capabilities of GRASS.