Assessment and monitoring of post-fire recovery using satellite imagery and the stability index in the north west of Algeria

Forest fires are a complex natural phenomenon, difficult to model because they depend many parameters, which vary in both time and space. It is therefore necessary to carry out research and prevention actions as part of the improvement and management of this risk. The severity of wildfires due to hotter and drier global climate conditions affects the ecological resilience and ecosystems at risk of deterioration following the failure of post-fire recovery. To properly prepare for wildfires, it is crucial to determine fire-sensitive areas, then locate fire suppression structures, and assess the spatial and temporal quantification of post-fire regeneration. The objectives of this study are, in the first stage, to introduce a new approach to fire detection using artificial intelligence, and in the second stage, to model the dynamics of regeneration and monitor the recovery of vegetation using satellite imagery and the post-fire stability index. This method is therefore based on the concept that the state of a disturbed system will be reflected by increasing or decreasing rates of change. While undisturbed or recovered system states are characterized by rates of change close to zero. This reflects the typical pattern of decreasing change rates in post-fire recovery trajectories. To do this, time series analyses of remote sensing images from Landsat and Alsat satellites between 2010 and 2023, both pre- and post-fire, were conducted in the Sidi Bel Abbés region, Algeria, to evaluate the post-fire stability index. Moreover, the rate of vegetation recovery after a fire was assessed using the normalized regeneration index. (NRI, RI). We therefore demonstrate the performance and relevance of the post-fire stability index compared to alternative approaches because this stability index provides a relatively simple and practical solution for consistent large-scale monitoring of post-fire recovery with satellite imagery, which, combined with standardized mapping of fire severity, thus offers numerous opportunities for further research on fires and landscape ecology.