Abstract:
The land _ use and land cover change (LULCC) plays an important role in global environmental change. Projections of future land use and land cover (LULC) patterns are needed to emulate the implications of human actions for the sustainable ecosystem. Models of land use and land cover changes have been developed by various researchers to address which, where and why land use and land cover changes occur.
This study aims at to predict future land use and land cover scenario in a developing region using empirical data and analysing their effects of different modeling parameters into the predicting results. The main objectives of this study are;. (i) Analysis of different satellite images on the basis of their land use and land cover classes (ii) Quantification of land use and land cover changes using change detection method and (iii) Simulation of land use and land cover changes using Cellular Automata Markov (CA Markov) chain based land use and land cover changes model for projecting the future land use and land cover scenario. To fulfil the above mentioned objectives, some research questions are posed, which include (i) What kind of changes occur in the study area? (ii) What types of transition are going, on within changes? (iii) What will be the future LULC? (iv) Do different sizes of neibourhood (3x3, 5x5, and 7 x 7 cellular automata) have an impact on CA Markov prediction results? (v) Which LULC parameter(s) have highest or lowest influence on predicted results? (vi) Are predicted results statistically independent or not? and (vii) Whether different time steps have any impact on CA Markov model predicted results?
To describe the above mentioned objectives and to answer the above mentioned questions, a study has been made to identify and review remote sensing GIS based LULCC models. Critical assessment and comparative analysis of identified reviewed models and background of remote sensing and GIS based LULCC modeling are described in this study. About 29 models are short-listed on the basis of their importance. It was also found that land use and land cover change is poorly understood and LULCC modeling for specific region, especially in developing regions, needs to be continuing.
