Multi-index analysis for wildfire severity and vegetation dieback assessment in semi-arid forest ecosystems

Wildfires are among the most serious disturbances affecting semi-arid Mediterranean forest ecosystems, where abrupt fire-induced damage may coexist with gradual vegetation dieback driven by drought, soil degradation, and other environmental stressors. This study assessed wildfire impacts and vegetation decline in the Ouled Yagoub State Forest (Khenchela Province, northeastern Algeria) using a multi-index remote sensing approach. Cloud-free Landsat 8 OLI and Sentinel-2 images acquired between 2019 and 2022 were processed in Google Earth Engine to analyze vegetation dynamics before, during, and after the major 2021 wildfire event. Ten spectral indices related to greenness, burn severity, canopy water status, pigment stress, and soil background effects were derived and interpreted within three complementary themes: vegetation dynamics, burned-area severity, and forest dieback. The results showed that, according to the NDVI-based classification, 38.04% of the massif fell within high to very high wildfire-risk classes, 40.62% within the moderate class, and 20.33% within low to very low classes. Burn severity analysis based on dNBR for 2020–2021 indicated that 30.98% of the study area was affected by high to very high severity, 42.74% by moderate severity, and 26.28% by low to very low severity. The 2021–2022 dNBR comparison further showed that 75.23% of the area remained within high to very high disturbance classes, whereas only 3.01% fell into low to very low classes, confirming limited short-term recovery after the fire. NBR and dNBR were the most effective indices for delineating burned areas and severity gradients, while SAVI, MSAVI, and OSAVI improved the identification of vegetation loss and soil exposure in sparsely vegetated zones. In contrast, GNDVI, SIPI, and NDWI provided useful information on gradual physiological stress and dieback beyond the most severely burned sectors. Overall, the combined use of fire-sensitive, soil-adjusted, and stress-related indices provided a more robust interpretation of post-disturbance forest dynamics than any single index alone, offering a practical tool for post-fire assessment, ecological monitoring, and restoration planning in semi-arid Mediterranean forests.

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