Urban growth modeling using earth observation datasets, Cellular Automata-Markov Chain model and urban metrics to measure urban footprints

Humans have significantly transformed land due to increasing population, consumerism and urban functions. The urban areas are facing crisis of natural resources, changing micro climate and loss of green spaces which affects the goals of ecological sustainability. The urban metrics, multi-ring buffer, and zonal analysis were applied to understand better insight of urban and ecological footprints. Further, we have attempted a study to model and predict the plausible future urban growth using a Cellular-Automata and Markov Chain Model (CA-MCM) and we have also used three map validation procedure. The CA-MCM suggests the growth and direction of growth. The CA contiguity spatial filter of dimension (5 x 5 pixel) was applied to know the change in the year 2028. The CA-MCM and urban metrics results show the spatial configuration and temporal patterns of urban areas which have been largely affected by the socio-economic, biophysical, geopolitical drivers and urban functions. The urban metrics revealed the future scenario that the average annual urban expansion rate (AUER) is maximum (2.26%) for 6-7 km in the period of 2018-2028. The urban expansion intensity index (UEII) indicates maximum intensity (1.22%) for 6-7 km in the period of 2018-2028. The urban expansion differentiation index (UEDI) has highest value (2.37 ha) for 6-7 km in the period 2018-2028, it expresses fast growth. The metrics analyses suggest that there will be a high expansion and intensity of built-up area in the peripheral region in coming years because the city is to be developed as a smart city which is most considerable mission of Government of India. Therefore, it is under continuous pressure of urban growth.