Prediction of land use changes based on land change modeler (LCM) using remote sensing: A case study of Muzaffarpur (Bihar), India

Abstract

Land use change models are tools to support the analysis of the causes and consequences of land use dynamics. Land use and land cover change (LUCC) has been recognized as an important driver of environmental change on all spatial and temporal scales. The primary objective of this paper is to predict and analyze the present and future growth of Muzaffarpur city and its surrounding, Bihar (India) using the Landsat satellite images of 1988 and 2010. These data are used for change prediction and for preparation of prediction map of year 2025 and 2035. IDRISI, Land Change Modeler (LCM) was used to analyze the land use and land cover changes between various classes during the period 1988-2008. Erdas Imagine software (ver-9.3) were also used to prepare land use/cover classification using image processing supervised classification method in a multi-temporal approach. The prediction of land use land cover change was done on neural network built-in module in the Selva version of IDRISI. The accuracy was obtained as 72.28% for all the conversion types.

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