<p>Natural hazards cause substantial environmental impacts, including vegetation destruction, landscape alteration and reduced ecosystem function. Understanding vegetation regrowth dynamics is crucial for evaluating post-disturbance recovery processes, and assessing ecosystem stability and resilience. The satellite-based spatial vegetation recovery model, inspired by Newton’s law of cooling, is proposed and validated in this study with the assumption that the rate of vegetation recovery following a landslide is directly proportional to the difference between the disturbed and non-disturbed NDVI through time. Employing NDVI time series data from the Landsat mission and Sentinel-2 covering distinct geographic regions, this study examines the resilience and restoration of vegetation triggered by landslides. Our analysis focused on the temporal dynamics of vegetation restoration at multiple landslide locations across Asia and Italy, triggered by earthquakes, typhoons, or extreme rainfall events. The results demonstrate a strong fit to the proposed model, with high R² values ranging from 0.81 to 0.98 across different sites, confirming that vegetation recovery rates are significantly influenced by the original NDVI. The study also differentiates recovery trends across landslide types and zones, revealing distinct resilience patterns based on the triggering mechanism and landslide zones. Results reveal that rainfall-induced landslides (RiLs) exhibit strong resilience compared to earthquake-induced landslides (EiLs). Further, within the EiLs, source zones consistently demonstrate slower recovery relative to runout zones, whereas RiLs show no significant difference between zones, possibly due to their shallow nature and uniform depositional characteristics. These findings contribute to a mechanistic understanding of vegetation regrowth processes and offer a remote sensing-based model for effectively quantifying the recovery component of ecosystem resilience.</p>