Urban growth modeling of a rapidly urbanizing area using FMCCA model

Abstract

Rapid urbanization is a serious concern for most of the developing countries as well as for India. Rapid and dynamic urbanization requires continuous monitoring of the underlying process of urbanization. But some loopholes of the Census of India data restrict continuous monitoring of rapid urbanization as the Census of India is the only source of urbanization-related numerical data in India. Past land use pattern of the study area shows a rapid growth of urban areas from 38.70 km2 in 2009 to 54.92 km2 in 2017 at the expense of agricultural land, vegetation, and also wetland areas. Markov chain-derived transition matrix-based cellular automata modeling is used to predict the land use pattern for 2017 on the basis of past two land use for a rapidly urbanizing phase integrating fuzzy standardization and weighted linear combination based potential urban development surface. Predicted land use map is used to compare with the actual land use map of 2017 extracted from satellite image for assessing the applicability of this model for future land use change prediction. Validation result shows a 94.24% (in terms of areal extension) agreement between actual and predicted urban area map of 2017. Then, the final urban growth map for 2020 is predicted using 2014 and 2017 land use maps and the same urban development potential area map used for predicting the 2017 urban area map. The predicted map shows a rapid urbanization in the adjacent areas of Salt Lake City especially towards the Northern and Eastern direction of the Salt Lake area, which increases the conciseness of the urban planners.