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GRASS with R: An Introductory Tutorial to Open Source GIS & Statistical Computing Software for Geospatial Analysis
http://wgbis.ces.iisc.ernet.in/energy/
Anindita Dasgupta1          Uttam Kumar1,2,3          Chiranjit Mukhopadhyay2           T.V. Ramachandra1,3,4,*
1Energy and Wetlands Research Group, Centre for Ecological Sciences [CES], 2Department of Management Studies, 3Centre for Sustainable Technologies (astra),
4Centre for infrastructure, Sustainable Transportation and Urban Planning [CiSTUP], Indian Institute of Science, Bangalore – 560012, India.
*Corresponding author:
cestvr@ces.iisc.ernet.in

ABSTRACT

GRASS (Geographic Resources Analysis Support System) is a free Geographic Information System (GIS) software used for geospatial data management and analysis, image processing, graphics/maps production, spatial modelling, and visualization. GRASS is being used in academic, research and development, governmental agencies and also for commercial purposes around the world. GRASS is an official project of the Open Source Geospatial (OSGeo) Foundation. OSGeo was created to support the collaborative development of open source geospatial software and promote its widespread use.

For many advanced geo-spatial statistical analysis, GRASS has an interface to the most powerful statistical package – R. R is a language and environment for statistical computing and graphics. R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, etc.) and graphical techniques, and is highly extensible. R is available as Free Software under the Free Software Foundation's GNU General Public License in source code form. Both GRASS and R compile and run on a wide variety of UNIX platforms and similar systems (including FreeBSD and Linux), Windows and MacOS.

In this communication, an introductory material for GRASS and R is presented for novice users in the form of a tutorial. It is aimed to provide basic knowledge of both these Open Source Packages, their robustness and their strengths with examples. Finally GRASS–R interface is presented to start R from within GRASS environment.

Keywords- foss; GRASS; R statistical Software; geo-statistics; open source

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Citation : Anindita Dasgupta, Uttam Kumar, Chiranjit Mukhopadhyay and Ramachandra. T.V., 2012, GRASS with R: An Introductory Tutorial to Open Source GIS & Statistical Computing Software for Geospatial Analysis, Proceedings of the OSGEO-India: FOSS4G 2012- First National Conference "OPEN SOURCE GEOSPATIAL RESOURCES TO SPEARHEAD DEVELOPMENT AND GROWTH”, 25-27th October 2012, @ IIIT Hyderabad , pp. 1-6.
* Corresponding Author :
Dr. T.V. Ramachandra
Energy & Wetlands Research Group, Centre for Ecological Sciences, Indian Institute of Science, Bangalore – 560 012, India.
Tel : +91-80-2293 3099/2293 3503-extn 107,      Fax : 91-80-23601428 / 23600085 / 23600683 [CES-TVR]
E-mail : cestvr@ces.iisc.ernet.in, energy@ces.iisc.ernet.in,     Web : http://wgbis.ces.iisc.ernet.in/energy, http://ces.iisc.ernet.in/grass
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