Spatio-Temporal Analysis of Vegetation Loss, Land Surface Temperature Changes, and Their Relationship with Vegetation Indices in Zhenjiang, China Using Satellite Imagery

The objectives of this study are to determine vegetation loss, changes in land surface temperature (LST) and their relation with vegetation indices (VIs) by utilizing multi-temporal satellite imagery over a thirty-year (1993–2023) period in Zhenjiang city located in Jiangsu province of China. For this purpose, a supervised classification technique was used to classify land use land cover (LULC) types based on maximum likelihood algorithm (MLC) approach. Our findings revealed that significant vegetation loss was observed (declines in greenery areas) alongside increases in urbanization and barren land, resulting in a notable rise in LST. Over the studied period (1993 to 2023), there was a significant drop of 16.69% in greenery areas, a moderate reduction of 1.44% in built-up areas, an increase of 2.64% in waterbodies, and a significant rise of 15.48% in other regions, such as barren, unoccupied, and non-agricultural land in studied region over three decades. Upon analysis, it was observed that normalized difference vegetation index (NDVI) decreased by 34% and the normalized difference moisture index (NDMI) decreased by 18%. In contrast, LST increased by 16.98%, the normalized difference built-up index (NDBI) increased by 18%, and the normalized difference water index (NDWI) increased by 16%. The study revealed that areas with greater NDVI values have lower LST, while region with more built-up areas (NDBI) showed a positive correlation with LST. Urban areas were hotter than rural areas, and atmospheric moisture helped lower LST. These findings highlight the need to monitor vegetation status in cities to maintain crop productivity and the benifts of remote sensing for agricultural management.