CELLULAR AUTOMATA (CA) MARKOV MODELING OF LULC CHANGE AND SENSITIVITY ANALYSIS TO IDENTIFY SENSITIVE PARAMETER(S)
ISBN 978-85-88783-11-9
Authors
1Mondal, M.S.; 2Garg, P.K.; 3Sharma, N.; 4Kappas, M.
13DEPT. OF CIVIL (GEOMATIC) ENGINEERING, IIT, ROORKEE -247667 Email: msk.iit@gmail.com
2DEPT. OF CIVIL (GEOMATIC) ENGINEERING, INDIAN INSTITUTE OF Email: pkgiitr@gmail.com
3DEPT. OF W R D & M, INDIAN INSTITUTE OF TECHNOLOGY, ROORKEE Email: nayanfwt@gmail.com
41Dept. of Cartography, GIS & Remote Sensing, Institute of Ge Email: mkappas@uni-goettingen.de
Abstract
In this study, an attempt has been made to evaluate Cellular Automata (CA) Markov model to predict the future land use and land cover scenario in a Kamrup Metropolitan district of Assam State of India, using land use and land cover maps derived from multi-temporal satellite images. Land use and land cover maps derived from satellite images of 1987 and 1997 were used to predict future land use and land cover of 2007This spatio-temporal model provided not only the quantitative description of change in the past but also the direction and magnitude of change in the future. Sensitivity analysis has been also carried out to identify the parameter(s), which have the highest, lowest or intermediate influence on predicted results. The results shows that the land with or without scrub appeared to be most sensitive parameter as it has highest influences on predicted results of LULC of 2007. The second most sensitive parameter was lakes / reservoirs / ponds to predict LULC of 2007, followed by river, agricultural crop land, plantation, open land, marshy / swampy, sandy area, aquatic vegetation, built up land, dense forest, degraded forest, waterlogged area and agricultural fallow land. The least sensitive parameter is agricultural fallow land, which has minimum influence on predicted results of LULC of 2007.
Keywords
LULC Change; CA Markov Modeling; Sensitivity Analysis