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Proceedings Paper

Use of empirically based land use dynamics model with climate and socio-economic parameters in a rain-fed agricultural area
Author(s): Vidhya R.; Manonmani R.
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Paper Abstract

The changes in the agricultural patterns and the forest land are one important indicators of serious socio economic and environmental management implications. The main challenge for the agriculture sector from the rainfed areas is to sustain present livelihood conditions and to secure future demands and typically they are more fragile to the changing climates and demands. Remote Sensing and Geographical Information System coupled with empirical modeling is recognized as a powerful and effective tool in detecting land use change and predict future changes. In this study, modeling and prediction of agricultural land use change across space and time using Logistic Regression and Geographically Weighted Regression in dry land region is attempted as the land use and land cover change is the function of interacting factors which are known as drivers, agents and determinants. The land use pertaining to 1985,1995 and 2005 for the study area were generated to study and model the land use dynamics. The drivers for land us change based on the factors such as climatological data and socio economics data were identified and a model for changes land use using geographically weighted regression and binary logistic regression methods . The models were validated with the help of land use map generated with remote sensing data.

Paper Details

Date Published: 24 October 2013
PDF: 9 pages
Proc. SPIE 8893, Earth Resources and Environmental Remote Sensing/GIS Applications IV, 889311 (24 October 2013); doi: 10.1117/12.2028715
Show Author Affiliations
Vidhya R., Anna Univ. Chennai (India)
Manonmani R., Anna Univ. Chennai (India)


Published in SPIE Proceedings Vol. 8893:
Earth Resources and Environmental Remote Sensing/GIS Applications IV
Ulrich Michel; Daniel L. Civco; Karsten Schulz; Manfred Ehlers; Konstantinos G. Nikolakopoulos, Editor(s)

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