Prediction of Land use Dynamics in the Rapidly Urbanising Landscape using Land Change Modeller

Landscape transformations in the rapidly urbanizing landscape are the most dynamic process altering the local ecology, hydrology and environment. This necessitates understanding of spatial patterns of the growth for an effective urban planning. Remote sensing data acquired at regular intervals through satellite borne sensors enables the synoptic monitoring and visualization of urban growth patterns and dynamics. Focus of this communication is to model the land use dynamics in a rapidly urbanizing landscape with 10 km buffer considering all agents. Due to the unplanned urbanization, Bangalore a Silicon Valley of India has been facing numerous challenges of loss of green space, mobility constraints, higher pollution levels, flooding, indiscriminate disposal of solid and liquid waste, etc. Land Change Modeller (LCM) with Markov Cellular Automata was used to predict likely land use in 2020 with the knowledge of land use changes during 2006-2012 with the constraint of no-change in land use of water category. The results suggest an urban expansion of 108% (from 59103.9 in 2012 to 123061.6 hectares in 2020), with the decline of green space to 7% from 33.68% (2012). The visualised urban growth provide vital insights for better planning of urban space to ensure Bangalore regain the status of liveable and sustainable city.