Land-Use Land-Cover Classification and Its Change Detection Using Multi-Temporal Landsat Data

Shiv Raj¹, Surinder Deswal²

^1,2 Department of Civil Engineering, National Institute of Technology Kurukshetra, Kurukshetra, India.

Abstract

This study discusses the effect of land-use land-cover (LULC) change on the land surface temperature in the Gaya district of Bihar (India). Landsat data acquired from 1993 to 2023 were used for land cover classification as well as land surface temperature calculation. The predominant patterns of change in land cover are characterised by an increase in agricultural land area (+4.93%), built-up areas (+1.51%), and water bodies (+2.01%), accompanied by a decline in forest cover (4.23%) and barren terrains (4.23%). The findings of this study also suggest a strong inverse correlation between land surface temperature (LST) and normalised difference vegetation index (NDVI) and a strong positive correlation with normalised differences built-up index (NDBI). The actual temperature and temperature computed from the thermal band of Landsat images exhibited a strong correlation (0.979) with a low root mean square error (1.98). The average percentage decline of 5.42% showed that the computed land surface temperature was on the higher side of the actual measured temperature. The results of the study demonstrated a significant decline in vegetation cover in the study area due to increased population leading to urbanisation and infrastructure development, thus continuously changing the ecology of the region.

Keywords: Land-use land-cover (LULC); Land surface temperature (LST); Normalised difference vegetation index (NDVI); Normalised differences built-up index (NDBI); Kappa coefficient

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