Vegetation dynamics are important indicators of environmental conditions, ecosystem health, and climatic variability. The study investigated the spatio-temporal variation of vegetation in the Mahaweli River Basin, Sri Lanka from 2016 to 2025. Normalized Difference Vegetation Index (NDVI) derived from satellite imagery is the core of the study. Seasonal NDVI analysis was conducted for both wet and dry seasons to evaluate vegetation conditions and long-term trends within the basin. The results revealed noticeable seasonal variations in vegetation cover, with the wet season recording slightly higher mean NDVI values compared to the dry season. Mean NDVI values ranged from 0.545 to 0.698 during the wet season and from 0.513 to 0.680 during the dry season. Statistical analysis showed that the dry season exhibited greater variability in vegetation conditions compared to the wet season. Trend analysis using linear regression, Theil–Sen slope estimation, and Mann–Kendall testing indicated positive NDVI trends during both seasons over the study period. The findings suggest gradual improvement in vegetation health and density within the Mahaweli River Basin from 2016 to 2025. Annual anomaly analysis also demonstrated temporal fluctuations associated with climatic and environmental variability while maintaining an overall increasing trend. The study highlights the effectiveness of remote sensing and GIS techniques for long-term vegetation monitoring and environmental assessment. The findings provide valuable information for watershed management, environmental monitoring, and sustainable land resource planning in Sri Lanka.

The study assessed the spatio-temporal dynamics of vegetation in the Mahaweli River Basin from 2016 to 2025 using NDVI analysis derived from satellite imagery. The results revealed that vegetation conditions varied seasonally, with the wet season showing slightly higher NDVI values than the dry season.The trend analysis indicated an overall increase in NDVI values during both wet and dry seasons throughout the study period. The finding suggests gradual improvement in vegetation cover and health within the basin. The dry season exhibited comparatively higher variability, indicating greater sensitivity of vegetation to climatic conditions and water availability. The statistical and trend analyses confirmed positive long-term vegetation trends across the basin. The anomaly analysis also showed yearly fluctuations in vegetation conditions while maintaining an overall increasing trend. Thestudy demonstrates that remote sensing-based NDVI analysis is an effective approach for monitoring long-term vegetation dynamics and seasonal environmental changes in the Mahaweli River Basin. The findings can support environmental management, agricultural planning, and sustainable watershed management activities in Sri Lanka.

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