Analyzing the Seasonal Relationship between Vegetation Variation and Land Surface Temperature Dynamics in Eastern Maharashtra 10.32526/ennrj/24/20250231
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Abstract
Understanding land surface temperature (LST) change trend is very important in Eastern part of Maharashtra state, India as this region is undergoing rapid land-use change. Vegetation plays a critical role in regulating land surface temperature in such region. The main objective of this study is to analyze the vegetation change trend and investigate the seasonal relationship between vegetation variation and land surface temperature fluctuation from the years 2014 to 2022. Using Landsat 8 satellite imagery, the Normalized Difference Vegetation Index (NDVI) is derived to monitor vegetation variation and thermal infrared (TIR) bands is used to calculate LST. The methodology is divided into data collection, preprocessing, NDVI and LST calculation. Based on NDVI and adaptive vegetation classification, land use (LU) classification is carried out and finally correlation analysis between the various classes of LU, NDVI value with LST is calculated. The results suggest a clear seasonal pattern where the post-monsoon period has higher average NDVI values and lower average LST values as compared to the pre-monsoon periods. There was a declining trend of overall vegetation health throughout the study period, although 2022 showed a slight recovery in pre-season NDVI and improved vegetative health in post-monsoon dense vegetation classes. Correlation analyses consistently indicated a moderate-strong negative association (~ -0.2 to -0.5) of LST with vegetation cover (vegetation cooling effect) and a positive association (~ 0.1 to 0.5) with built-up areas (urban heat island effect). It highlights the importance of vegetation cover for local temperature management and has significant implications for the assessment of recent changes in the local environment.
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