RISING FROM THE FLAMES: TRACKING NATURE'S RESILIENCE AFTER THE BLUE CUT FIRE

Post-fire recovery assessment is critical for wildland-urban interface management and climate adaptation planning, yet quantitative relationships between environmental controls and regeneration success remain poorly understood in Mediterranean ecosystems. This research addresses the fundamental problem of predicting recovery patterns through comprehensive dual-index analysis combining Normalized Difference Vegetation Index and Normalized Burn Ratio assessments of vegetation regeneration following the 2016 Blue Cut Fire across 37,020 acres in San Bernardino County, California. Six time periods of Landsat 8/9 imagery spanning 2016-2025 were processed using automated workflows, integrated with comprehensive topographic analysis quantifying slope gradient and aspect orientation effects through advanced statistical modeling. The dual-index approach provided unprecedented cross-validation of recovery patterns, with NDVI analysis achieving 98% successful natural regeneration averaging 129.0% of pre-fire conditions while NBR analysis confirmed 80% significant improvement from immediate post-fire conditions. Results revealed counter-intuitive patterns challenging conventional ecological theory: moderate slopes achieved 132.6% recovery compared to flat slopes at 124.6%, contradicting erosion control predictions. Quadratic regression modeling provided exceptional validation with R² = 0.9573, mathematically proving optimal recovery occurs at 26.5° slope gradient. Circular regression explained 87.3% of aspect-related recovery variation, with north-facing slopes achieving superior recovery across both indices. The convergence of findings across independent analytical approaches demonstrates that environmental controls explain greater than 85% of recovery variation, providing robust quantitative frameworks for predicting post-fire regeneration success. Results suggest Mediterranean fire-adapted ecosystems possess exceptional natural recovery potential, enabling resource managers to prioritize limited restoration funds toward other ecosystem priorities rather than widespread intervention following similar fire events.