An Analytical study of relation between Land surface temperature and Land Use/Land Cover using spectral indices: A case study of Chandigarh
DOI:
https://doi.org/10.58825/jog.2023.17.2.65Keywords:
LST, LULC, spectral indices, change detection, correlation, regression, mono-window algorithmAbstract
Rapid urbanization is the major cause for Land Use and Land Cover changes globally. The urbanization alters the land surface dynamics and affects the surface temperature, which gives rise to urban heat island effect. In the present study, spatial correlation analysis has been done between Land Surface Temperature (LST) and Land Use and Land Cover (LULC) for the city of Chandigarh. The LST is retrieved from Landsat-8 thermal band using Mono-Window algorithm and shows 2.5°C increase of temperature from 2016 to 2022. The LULC has been derived using Maximum Likelihood Classifier (MLC) which shows an increase in built-up of 7.56% and decrease in forest cover by 32%. Spectral indices belonging to major LULC classes have been derived using Sentinel-2 optical bands and spatially correlated with LST using linear regression analysis. The results show a strong positive correlation (r=0.988) between built-up and LST and a negative correlation (r=-0.625) between urban vegetation cover and LST. The mean correlation coefficient for LST-NDVI for vegetation and forest cover, LST-NDWI for water bodies, LST-NDBI for built-up and LST-NBLI for bare land is -0.3, 0.116, 0.51 and 0.392 respectively. The results indicate that vegetation and water bodies mitigate the rise of LST, whereas built-up areas and bare lands sustain in the rise of LST. The statistical analysis will be helpful for policy makers and urban planners for prevention of further degradation of urban environment and surface dynamics.
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