Spatio-Temporal Behaviour of Vegetation Dynamics over the Betwa Basin (2018–2023), India

Vegetation plays a critical role in the mitigation of climate change impacts. In this work we have used Google Earth Engine (GEE) to quantify vegetation dynamics by computing spectral indices for Betwa River Basin, India. Strong positive correlations are observed among vegetation greenness and burn-sensitive indices. NDVI exhibits a very high correlation with SAVI (r = 0.98) and a strong correlation with NBR (r = 0.92) and NDMI (r = 0.90), indicating that these indices respond similarly to variations in vegetation density and condition. Linear trend analysis of six vegetation and moisture indices (NDVI, EVI, NBR, SAVI, NDWI, and NDMI) for the study area during 2018– 2023. NDVI shows a weak negative trend (−0.0127 yr⁻¹, R² = 0.021, p = 0.227), indicating a slight decline in overall vegetation greenness, although the trend is statistically insignificant. Similarly, EVI exhibits a marginal decreasing trend (−0.0192 yr⁻¹, R² = 0.010, p = 0.406), suggesting relatively stable vegetation Vigor with no significant longterm change. Mann–Kendall non-parametric trend tests broadly corroborate the linear regression findings. Hence, the work is useful for conservation of vegetation and resource planning purpose.