Spatio-temporal Variation of Building Morphology in Indian Cities from 2018 to 2023

By 2050, more than two-thirds of the world’s population is estimated to reside in urban areas, leading to a rapid increase in the consumption of resources in cities. Depending on factors such as urban sprawl and building morphology, this can lead to several adverse effects on the environment and public health, such as energy consumption and the Urban Heat Island effect. Rapidly developing countries like India have a great degree of unplanned expansion and building construction, with significant growth in urban infrastructure expected in the next 15 years. Therefore, it is critical to understand the evolution of building morphology in the process of urban development. This study examines the evolution of building morphology in 11 major Indian cities over two years: 2018 and 2023. Remote sensing data was coupled with a deep learning model, Simultaneous building Height And FootprinT extraction from Sentinel imagery (SHAFTS), for quantifying building height and footprint in these cities. A variability index was defined to quantify the spatial variability, demonstrating that height variabilities are more significant than footprint for 2018 and 2023. Chandigarh (0.0557 km-1) and Mumbai (0.0351 km-1) have the highest and the lowest footprint variability, while Bangalore (0.0739 km-1) and Mumbai (0.0441 km-1) have the highest and lowest height variability in 2023. Barring a few cities, the footprint variability decreased from 2018 to 2023, indicating that the newer buildings have similar footprints to existing ones. Contrarily, the increased height variability indicates height differences between the older and newly constructed buildings.