Urban growth dynamics of an Indian metropolitan using CA Markov and Logistic Regression

Abstract

The inescapable phenomenon of growth due to urbanization is witnessed by urban centres. The rate of growth of an urban area can be attributed to a number of factors that play a pivotal role in depicting the land use dynamics. The need to identify, quantify and analyse the drivers of growth is essential to understand the phenomenon of urban growth in a fast growing agglomeration like Lucknow, capital of the most populous state, Uttar Pradesh in India. In this study the urban growth within the planning area was analysed for the year 1993, 2003 and 2013 using certain bio-physical and proximity factors affecting the growth pattern of the city. Factors maps were generated for the various years and the growth was predicted for the year 2023 using integrated Logistic Regression based CA-Markov analysis embedded in the LULC Dynamics Modelling Platform v1.0 developed under the ISRO Geosphere Biosphere Programme at IIRS, ISRO, Dehradun. The predictions show that the city is expected to grow manifolds to 441.2 sq. km in 2023 from mere 53.6 sq. km in 1993. Results show that the model was successful in depicting the infill growth but could not completely predict the expansion phenomenon. The results indicate that integration of remote sensing, GIS and growth models provide important information related to the process of urban expansion useful for planners preparing vision documents for cities. Keywords: Urbanization, Urban growth, Drivers of growth, Logistic Regression