Temporal impact of urban indicators of land surface cover on land surface temperature: Case study of an Indian metropolitan city

Land surface temperature (LST) is an important parameter for investigating surface urban heat islands (UHI) at different scales of urban development. Previous studies on UHI have been limited in quantifying the magnitude, and very few studies explored in-depth relations between built-up density classes and LST. This paper focuses on the land surface cover factors contributing to changes in urban LST. The impact of urban surface cover indicators such as land cover (LC) groups, built-up density classes, and pervious surface fraction (PSF) groups on LST was investigated in this study. Bengaluru metropolitan region was selected as the study area. Seasonal LSTs were calculated using the 2013–14, 2019, and 2023 Landsat 8 images and validated with MODIS LST images. LC for the three time periods were generated using supervised classification and related to respective LSTs. A 500 m × 500 m grid was considered a unit area to calculate the percentage of LC classes. One-way ANOVA tests revealed significant differences in seasonal mean LSTs among seven LC groups, six percentage built-up area (PBA) groups and nine PSF groups. The study has found a moderate negative relation between PBA groups and mean LSTs due to rapid urbanisation towards fringe areas in 2019 and 2023, which led to vacant lands with higher mean LST values converted into built-up areas with comparatively lesser mean LST. The mean LST of 2023 was lesser than in 2013 and 2019 due to an increment of vegetation cover by 16.8% during the last decade, which turned Bengaluru’s central area into a surface urban cool island (SUCI). However, the study has also found that the high-density built-up areas with no vegetation or waterbody located in the periphery of the outer ring road and the central commercial area of Bengaluru generated more urban hot spots in 2019 and 2023 than in 2013. This study, carried out at a local level of urban development, is more relevant to the urban planners’ formulation of guidelines for ameliorating surface UHI.