five

Eaton Fire Burn Area, in Infrastructure Resilience and Impact Study for Wildfire-affected Infrastructure in Los Angeles

收藏
DataCite Commons2026-03-23 更新2026-04-25 收录
下载链接:
https://www.designsafe-ci.org/data/browser/public/designsafe.storage.published/PRJ-5815/#detail-5a77ce86-fe4a-4394-b0c4-d12362e3885d/?version=3
下载链接
链接失效反馈
官方服务:
资源简介:
In January 2025, two major wildfires devastated the Los Angeles region: the Palisades Fire and the Eaton Fire. Both fires ignited on January 7, 2025, and were fully contained by January 31, 2025. Together, they burned over 15,000 hectares (approximately 60 square miles), destroyed more than 16,000 structures, and caused an estimated economic loss exceeding $75 billion. The Palisades Fire primarily affected the Pacific Palisades and Malibu communities, while the Eaton Fire impacted Altadena and Pasadena. This dataset is part of the "RAPID: Infrastructure Resilience and Impact Study for Wildfire-affected Infrastructure in Los Angeles (IRIS-Wildfire)" project (NSF Award #2524950). The project's primary goal is to understand how wildfires impact infrastructure in communities where developed areas meet wildlands—known as the wildland-urban interface (WUI). Data was collected in February/March 2025, and again in September 2025 to capture change. The datasets are unique because of their high level of detail and specific focus on infrastructure performance in densely populated areas adjacent to wildfire-prone wildlands, offering crucial insights into the immediate effects of wildfires on civil infrastructure. The key objectives of this research project are to gather detailed aerial and ground-based information on buildings, roads, utilities, and communities affected by the fires; examine how fires spread from structure to structure and identify factors that influence damage extent within communities; assess the effectiveness of firebreaks and other fire prevention methods; and improve fire spread prediction models using real-world data collected from these events. Data collection was carried out by the research team associated with NSF Award #2524950 and supported by the NHERI RAPID Facility. The methods included high-resolution aerial imaging and street view imagery (SVI). Uncrewed Aerial Systems (UAS), also known as drones, piloted by the NHERI Natural Hazards and Disaster Reconnaissance (RAPID) Facility, surveyed areas impacted by both fires. This aerial imaging produced approximately 30 square kilometers of high-resolution images, geo-referenced orthomosaics, 3D point cloud models, and digital surface models, all of which are provided in this dataset. Street view imagery captured 640 kilometers of detailed, ground-level visuals of the affected areas. Due to personally identifiable information in the raw street view images, these are not publicly available—please contact the Principal Investigator for access requests. Privacy-protected imagery is viewable on the Mapillary web platform: https://www.mapillary.com/app/?lat=34.0931&lng=-118.3476&z=10.2841&username%5B%5D=uwrapid The Palisades and Eaton Fire data can be easily viewed in the cloud using the project's associated Hazmapper application, which provides a user-friendly interface for exploring the information without requiring specialized software (see "Hazmapper Maps" link above). This web-based resource is ideal for community members, local officials, and general users who want to understand the fire impacts in their areas. For detailed analysis purposes, please download the complete, full-resolution dataset from the project. This information serves a wide range of users, from community members and local officials seeking to understand fire impacts in their neighborhoods to researchers studying general wildfire impacts and experts in infrastructure resilience, fire spread modeling, and public health. The data supports diverse applications including community awareness, policy development, in-depth case studies, regional-scale assessments, and computer model calibration and verification. Detailed information about these datasets is provided in the associated data reports.
提供机构:
Designsafe-CI
创建时间:
2025-08-28
二维码
社区交流群
二维码
科研交流群
商业服务