Assessment of Post-Fire Regeneration in the Mesguina Forest (Morocco) Using Remote Sensing and GIS - Aziz El Badri; Mohamed El Qryefy; Mohamed Benbrahim; Fouad Khiri (European Scientific Journal, ESJ, 2026)
This study aims to quantify the area affected by the 2013 wildfire in the Mesguina Forest in Morocco and monitor vegetation regeneration over six years (2013–2019) using remote sensing and GIS. A spatio-temporal database was created using Landsat-8 and Sentinel-2 imagery, which was supplemented by field observations. Two spectral indices were employed: the Normalised Difference Vegetation Index (NDVI) to evaluate vegetation coverage and density, and the Normalised Burn Ratio (NBR) to precisely delineate burnt areas. Satellite images acquired before and after the fire were processed using ArcGIS, ENVI, SNAP and QGIS software. The NDVI and NBR results were then classified in order to quantify changes in vegetation cover. The NDVI and NBR analyses revealed that 49.3 % (958 ha) to 54.85 % (1,066 ha) of the forest was burnt in July 2013. The most severe degradation occurred by 2015, leaving extensive areas of bare and degraded soil. Thereafter, gradual regeneration was observed, mainly on northern slopes and near river systems, dominated by regrowth of the species Tetraclinis articulata. By 2019, the regeneration rate had reached 58.48 % (560 ha of the burnt area). However, the analysis relies on medium-resolution satellite imagery, which may overlook fine-scale regeneration patterns. Furthermore, the study is limited to six years post-fire and does not assess long-term successional dynamics. Nevertheless, this study provides the first quantitative evidence of post-fire regeneration dynamics in a semi-arid Mediterranean forest in Morocco. By combining NDVI and NBR, it demonstrates the spatial heterogeneity of recovery and the strong influence of slope orientation and water proximity. These ecosystem-specific patterns, not previously documented in the Mesguina forest, differ markedly from those reported in temperate and boreal forests, offering valuable spatial data for post-fire management and monitoring.