Spatio-Temporal Assessment of Forest Degradation Using Multi-Index Landsat Time Series for Restoration Prioritization in Bhutan

Forest degradation is difficult to detect because gradual changes in forest condition can occur without complete canopy loss. This study assessed Spatio-temporal forest degradation and restoration priorities in Bhutan from 2005 to 2024 using Landsat-derived NDVI, NDMI, NBR, and NDFI. Pixel-wise temporal trends were evaluated using ordinary least-squares regression (p < 0.05), and the four index-specific classifications were integrated using a ≥3 of 4 (75%) consensus criterion. Of 18,356.70 km² of analyzed persistent forest, 1.99% showed strong multi-index evidence of degradation, 64.03% were classified as stable/no significant trend, 12.97% improved, and 21.01% showed no consensus. Validation using 901 stratified random samples yielded an area-adjusted overall accuracy of 52.31%, indicating a trade-off between conservative multi-index agreement and sensitivity to subtle degradation. Restoration priority within mapped degraded forests was assessed by integrating erosion susceptibility, fire recurrence, human pressure, conservation importance, and forest-type restoration sensitivity using Simple Additive Weighting, with the resulting index classified into low, moderate, high, and critical priorities. The framework provides a spatially explicit approach for linking long-term forest degradation detection with targeted restoration prioritization in Bhutan, while explicitly accounting for uncertainty in forest-condition trajectories.