Spatiotemporal monitoring and assessment of green oak leaf-roller outbreaks in Zagros forests using Sentinel-2 data and the BFAST algorithm

The decline of oak forests in the Zagros Mountains poses a major threat to the ecological stability and long-term resilience of these ecosystems. This study quantified the effects of green oak leaf-roller (Tortrix viridana L.) outbreaks on canopy dynamics by integrating Sentinel-2 imagery, vegetation indices (NDVI, EVI, NDWI), and the BFAST time-series algorithm. Canopy deterioration was most pronounced at mid-elevations (1200-1800 m) and on moderately sloped terrain (15-30%). The most severe defoliation occurred in 2019 (~ 4253 ha), coinciding with the peak infestation period, followed by partial stabilization in 2021 (~ 1362 ha) and 2022 (~ 1380 ha). Vegetation indices revealed marked physiological stress in affected stands, with NDVI declining to ~ 0.38, EVI to ~ 0.23, and NDWI to ~ 0.1, indicating reductions in photosynthetic activity, canopy density, and crown moisture. Although partial recovery was observed in 2023-2024, persistent biotic pressure limited full canopy regeneration. Time-series modeling showed that spatial and temporal variation in impacted stands was jointly shaped by topography, distance to roads and rivers, drought intensity, and pest activity. The combined use of high-resolution satellite data and BFAST provided an effective framework for detecting subtle canopy degradation and supports more accurate monitoring and adaptive management of pest-induced forest decline.