Spatiotemporal Dynamics of Ecological Health in Punjab (2001–2023): Integrated Remote Sensing Approach for Sustainable Paddy Cultivation

Monitoring ecological health at regional scales is crucial for guiding sustainable agricultural practices under increasing climatic and anthropogenic pressures. This study employs the Remote Sensing Ecological Index (RSEI), integrating NDVI, Land Surface Temperature (LST), Normalized Difference Built-up and Soil Index (NDBSI), and wetness, to assess ecological condition during the Kharif season from 2001 to 2023 using MODIS imagery across Punjab. Each indicator was normalized (0–1) and processed through Principal Component Analysis (PCA), with PCA1 utilized to construct the composite RSEI. Spatiotemporal analyses reveal a predominance of moderate ecological quality (37–45%), while the “Good” category declined from 19.11% in 2001 to 14.40% in 2023, reflecting ecological stagnation under urbanization and thermal stress. Vegetation (NDVI) contributed most strongly to RSEI (0.72-0.81), followed by wetness (0.12-0.18), whereas NDBSI and LST, though lower in weight, strongly influenced localized ecological degradation. Temporal fluctuations highlight stress years (2020 with elevated LST and reduced NDVI) and partial recovery in 2023. Rainfall analysis underscores the dominance of monsoon variability, with July–September contributing >70% of annual totals, directly shaping vegetation health and wetness. Correlation analysis demonstrates that RSEI negatively associates with NDVI (–0.74), wetness (–0.84), and paddy yield (–0.23), while positively linking with NDBSI (0.715), confirming the ecological and agronomic costs of built-up expansion and climate stress. These findings underscore the utility of RSEI as a robust, spatially explicit indicator of ecosystem quality, offering actionable insights for precision agriculture and sustainable land-use planning in water-intensive crop regions.