The growing frequency and intensity of wildfires pose serious threats to communities in wildland-urban interface regions. Understanding evacuation behavior is critical for effective emergency planning. This study analyzes evacuation during the 2025 Palisades and Eaton Fires using high-resolution Facebook data. We propose a comprehensive framework to derive wildfire evacuation-related metrics, including compliance rate, departure timing, delay, origin-destination flows, travel distance, and destination types. A new metric, Damage-Evacuation Disparity Index (DEDI), identifies areas with severe structural damage but low evacuation compliance. Results reveal spatiotemporal heterogeneity: residents closer to the fire evacuated earlier, whereas late or nighttime orders led to lower compliance and longer delays. Contrasting patterns between East and West Altadena further illustrate this disparity. DEDI-identified communities exhibited higher social vulnerability and fire risk. Most evacuations concluded in residential areas, while longer trips concentrated in hotels and public facilities. These findings showcase the Facebook data's potential for data-driven wildfire evacuation planning.

翻译：日益频发且剧烈的野火对城乡交界区域的社区构成严重威胁。理解疏散行为对有效的应急规划至关重要。本研究利用高分辨率Facebook数据分析了2025年帕利塞兹与伊顿火灾期间的疏散情况。我们提出了一个综合框架以推导野火疏散相关指标，包括遵从率、出发时间、延迟、起讫点流、出行距离及目的地类型。新指标“损毁-疏散差异指数”（DEDI）用于识别建筑损毁严重但疏散遵从率低的区域。结果揭示了时空异质性：靠近火场的居民疏散更早，而夜间或延迟发布的疏散指令导致更低的遵从率与更长的延误。东阿尔塔迪纳与西阿尔塔迪纳之间的对比模式进一步阐释了这种差异。DEDI识别出的社区表现出更高的社会脆弱性与火灾风险。多数疏散以居民区为终点，而较长距离的出行则集中于酒店与公共设施。这些发现展示了Facebook数据在数据驱动的野火疏散规划中的应用潜力。