10. Case Study 2: Simulating Future Urban Growth Using Cellular Automata-Markov Chain Models

Developing nations are facing a serious threat of urbanization. India is one out of them. Keeping this concept on mind we tried to quantify the urban area expansion by using advanced geospatial technologies in this case study. Bangalore city was selected as our target study area. Here we assessed the urban area expansion from 2001 to 2025 in future. For that purpose, data for the years 2001, 2011 and 2016 was downloaded from Landsat Thematic Mapper (TM) and Operational Land Imager (OLI). ERDAS Imagine was used for land use-land cover (LULC) map classification for the years 2001, 2011 and 2016. LULC map was classified into five LULC classes, viz. urban, forest, vegetation, fellow land and water body. Cellular Automata-Markov (CA-Markov) Chain Modelling was used through IDRISI Selva software for the prediction of future land cover. Land Transition Probability matrix was also created using Markov model for the time period 2001–2025. 2016 LULC map was used for the validation of CA–Markov Model. Result revealed that urban area will be increased to 33% in 2001 to 55% in 2025. Nearly forest cover will become half from 30% in 2001 to 15% in 2025. Vegetation will also reduce from 33% in 2001 to 24% in 2025. This case study revealed the fact that rapid rate of the urban area expansion is being observed in the region. But this is happening at the cost of forest and vegetation loss. Result showed that these two land use classes will decrease substantially till 2025. Considering this result, it is the responsibility of the concerned authorities and government stakeholders to prepare a wholistic plan in such a way that proper urbanization could be managed at the least cost of green cover in the region.