Advancing disaster response with a comparative multisensor satellite imagery approach: The 2025 Palisades Fire in California

Wildfires pose severe threats to lives, critical infrastructure, and ecosystems, particularly in urban–wildland interface settings where rapid situational awareness is essential for response and early recovery. This study presents a comparative multisensor satellite workflow for rapid wildfire damage assessment, demonstrated using the 2025 Pacific Palisades Fire (California) as a case study. We integrate Sentinel-2 optical imagery with ALOS-2 (L-band) and Sentinel-1 (C-band) synthetic aperture radar (SAR) data to map burned areas and characterize structural impacts. Burned regions are delineated using optical spectral indices, while SAR coherence and texture features support urban damage characterization, including conditions where optical observations are hindered by smoke or clouds. Results indicate that ALOS-2 achieved higher classification performance (84.64% accuracy, Kappa = 0.73) compared with Sentinel-1 (78.31% accuracy, Kappa = 0.61), underscoring the added value of L-band SAR for post-fire impact mapping. The event affected 92.99 km², including 92.05 km² of forest and 0.94 km² of residential areas. Beyond technical performance, the comparison highlights operational trade-offs relevant to disaster response, where higher-accuracy products must be balanced against data accessibility and acquisition frequency. Overall, the proposed multisensor analysis supports rapid post-fire assessment and provides actionable information for emergency response and evidence-based recovery planning in fire-prone regions.