Spatiotemporal dynamics of land surface temperature and vegetation cover in Thanjavur district Tamil Nadu India using remote sensing and GIS

Land Surface Temperature (LST) and vegetation dynamics are widely recognized as reliable indicators of environmental change, urbanization, and climate variability. Understanding their spatial and temporal interactions is essential for sustainable environmental planning, particularly in agriculturally intensive regions experiencing rapid land-use transformation. This study investigates the spatio-temporal variations of LST and the Normalized Difference Vegetation Index (NDVI) in Thanjavur District, Tamil Nadu, India, using multi-temporal Landsat imagery acquired during 2011 and 2021. Satellite images were processed using standard remote sensing techniques to derive LST and NDVI, while Geographic Information System (GIS)-based spatial analysis was employed to evaluate block-level variations. A simple linear trend analysis was employed to project potential environmental conditions for 2031 based on observed temporal changes. The results indicate considerable spatial heterogeneity in both thermal conditions and vegetation cover across the district. During 2011, the highest LST (46 °C) was recorded in Ammapettai Block, whereas Thiruvonam exhibited the highest NDVI (0.7128), reflecting dense vegetation supported by the Cauvery Delta irrigation system. In 2021, Thanjavur Block emerged as the principal thermal hotspot (43 °C), while vegetation cover declined in several urban and peri-urban areas. The projected 2031 scenario suggests a continued increase in thermal intensity in rapidly developing regions together with a gradual reduction in vegetation density. Regression analysis showed a weak and statistically insignificant relationship between LST and NDVI (R² = 0.043; p = 0.477), indicating that surface temperature is influenced not only by vegetation but also by urban expansion, irrigation practices, land-use characteristics, and local environmental conditions. The study demonstrates the usefulness of integrating remote sensing and GIS techniques for long-term environmental monitoring and provides baseline information for sustainable land-use planning, urban greening, climate adaptation, and environmental management in the Cauvery Delta region.