Characterizing urban growth and land surface temperature in the western himalayan cities of India using remote sensing and spatial metrics - Gupta, Rajman; Sharma, Mani; Singh, Garima; Joshi, Rajendra Kr (Frontiers in Environmental Science, 2023)
Urban heat islands (UHI) are developing due to increasing urbanization and loss of vegetation in major cities in India. Increased urbanization modifies the urban microclimate that leads to significant land-use changes resulting in surface conversion and heat release, which poses serious risks to human health, environment and the ecosystem of the Himalayan ecosystem. Hence, mitigating UHI becomes important and requires a better understanding of underlying associated biophysical processes. In the study an attempt has been made to demonstrate the impact of urbanization on land surface temperature (LST) in Shimla and Dehradun, capitals of the Western Himalayan states, India using satellite data and spatial metrics. The process was analyzed using urban coverage patterns obtained from Landsat 5, 7, and 8 and corresponding sensors from TM, ETM+, and OLI. The Built-up and Non-Built-up areas were extracted and the biophysical parameters NDVI, NDBI, NDWI and LST were calculated to capture different features of urban growth. The result indicated, that the built-up area increased from 32.19 km2 (2000) to 68.37 km2 (2016) in Dehradun and from 12.38 km2 (2000) to 29.47 km2 (2016) in Shimla during the study period, resulting in an increase in NDBI and LST and Reduction and NDVI and NDWI. Results showed that temperature hotspots were largest in urban areas, followed by vegetation and water bodies. A significant correlation (P < 0.05) was observed between LST and biophysical parameters -NDVI, NDBI, NDWI. Spatial metrics at the class and landscape levels show that increased urban growth from 2000 to 2016 has made the landscape fragmented and more heterogeneous. The Identified trends and changes in landscape patterns and their impact on heterogeneous urban areas suggest that the study is feasible to estimate LST, NDVI, NDBI and NDWI with reasonable accuracy that will likely have influence on policy interventions.