Assessing Local Climate Change by Spatiotemporal Seasonal LST and Six Land Indices, and Their Interrelationships with SUHI and Hot–Spot Dynamics: A Case Study of Prayagraj City, India (1987–2018)

LST has been fluctuating more quickly, resulting in the degradation of climate and human life on a local–global scale. The main aim this study is to examine SUHI formation hotspot identification over Prayagraj city India using seasonal Landsat imageries 1987–2018. interrelationship between six land indices (NDBI, EBBI, NDMI, NDVI, NDWI, SAVI) (using mono-window algorithm) was investigated by analyzing correlation coefficients directional profiling. NDVI dynamics showed that forested area observed lower 2.25–4.8 °C than rest landscape. NDBI built-up kept higher 1.8–3.9 landscape (except sand/bare soils). intensified center rural/suburban sites 0.398–4.016 summer 0.45–2.24 winter. Getis–Ord Gi* statistics indicated remarkable loss areal coverage very cold, cool classes MODIS night-time data strong at night This expected assist unfolding composition for mitigating thermal anomalies restoring environmental viability.