Sudhir Kumar Singh|Sk. Mustak|Prashant K. Srivastava|Szilárd Szabó|Tanvir Islam
Predicting Spatial and Decadal LULC Changes Through Cellular Automata Markov Chain Models Using Earth Observation Datasets and Geo-information
University of Allahabad|Pandit Ravishankar Shukla University|Goddard Space Flight Center|University of Debrecen|NOAA Center for Satellite Applications and Research|NOAA National Environmental Satellite Data and Information Service
remote sensing gis important tools studying land useland cover lulc change integrating associated driving factors deriving useful outputs study based utilization earth observation datasets highly urbanized allahabad district india allahabad district experienced intense change lulc last decades monitor changes advanced techniques remote sensing gis cellular automata camarkov chain model camcm used identify spatial temporal changes occurred lulc area two images 1990 2000 used calibration optimization markovian algorithm 2010 used validating predictions camarkov using ground based land cover image validating model plausible future lulc changes 2020 predicted using camcm analysis lulc pattern maps achieved classification multitemporal satellite datasets indicated socioeconomic biophysical factors greatly influenced growth agricultural lands settlements area two urbanization indicators calculated study viz land consumption ratio lcr land absorption coefficient lac also used indicated drastic change area terms urbanization predicted lulc scenario year 2020 provides useful inputs lulc planners effective pragmatic management district direction effective land use policy making suggestions effective policy making also provided used government officials protect important land resource