Use of Empirically based Land use dynamics model with Climate and Socio- Economic parameters in a rain-fed agriculture area

摘要

The changes in the land use and the pattern of the change are important indicators of socio economic and environmental management implications. The challenge is significant for for the agriculture sector from the rainfed areas as they are more fragile to the changing climates and increasing demands. Remote Sensing and Geographical Information System coupled with empirical modeling is 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. 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.