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The Martin Fire, which ignited on July 5, 2018, in Nevada's Great Basin, burned over 177,750 hectares of shrubland, profoundly impacting rangeland ecosystems and wildlife habitats. This case study examines the methods and spatial datasets used to inform post-fire rehabilitation efforts, providing a framework for large-scale landscape restoration. Legacy grazing practices, compounded by an Aroga moth infestation, had degraded the herbaceous understory and increased fuel loads, further challenging recovery. Within the Bureau of Land Management's (BLM) 30-day Emergency Stabilization and Rehabilitation (ESR) planning window, tools were employed to evaluate pre-fire conditions, assess resilience, and prioritize rehabilitation needs. Key methods included the use of Disturbance Response Groups (DRGs) to classify plant communities by their response to disturbances and the integration of remote sensing and ground-based vegetation data to map plant functional group cover. Near-real-time annual grass mapping, validated against ground measurements, highlighted areas prone to invasive species dominance, while soil texture and precipitation data-informed microclimate resilience assessments. Historical wildfire data provided context for evaluating past rehabilitation outcomes, and guiding strategies for the current fire rehabilitation effort. Results revealed substantial variability in vegetation recovery, influenced by pre-disturbance conditions and environmental factors. Areas with resilient soils and adequate herbaceous cover recovered well, while those dominated by invasive annual grasses or dry fuels exhibited poor recovery. Herbicide treatments showed a notable reduction in bare ground and a temporary increase in annual vegetation, emphasizing the role of targeted interventions. This study demonstrates the utility of spatial datasets and collaborative planning in addressing large-scale disturbances. While implementation remains complex, the lessons learned from the Martin Fire provide valuable insights for improving future wildfire rehabilitation strategies, emphasizing the importance of integrating ecological data to support decision-making at the landscape scale.