Urban sprawl modeling using cellular automata

Abstract

The population settlements in the fast-growing urban world need to be monitored in order to design a sustainable urban habitat. The remote sensing and GIS are considered as an effective monitoring and decision-support tool in urban planning. This study compiles the results of a study undertaken to measure the urban sprawl in Dehradun city, India through cellular automata CA-Markov model. CA-Markov model can effectively be used to study the urban dynamics in rapidly growing cities. Being an effective tool for encoding spatial structures, the information generated by it could be used to predict urban scenarios for sustainable growth. To achieve the goal, the temporal images of LISS IV were used to analyse the spatial pattern of land cover change in the area and the future growth was modeled by applying CA-Markov model. The results clearly suggest that major changes between the periods of 2004 and 2009 occurred in built up classes (about 27%) followed by agriculture (17.7%) and fallow land (10.2%). The projection as predicted using CA-Markov model suggested a value of kappa coefficient = 0.91 which indicates the validity of the model to predict future projections. Modeling suggested a clear trend of various land use classes’ transformation in the area of urban built up expansions. It is concluded that RS and GIS can be an effective decision support tool for policy makers to design sustainable urban habitats.

Keywords

• Urban sprawl
• CA-Markov
• GIS
• Urbanization