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Details

24-2-06-7
2024
09/24/2024
Advanced Spatial Data Analytics for Parcel- and Neighborhood-Level Wildfire Damage and Risk Assessment
1. Problem Statement
In recent decades, growth in the frequency, scale and severity of catastrophic wildfires has caused increasing levels of devastation in the wildland-urban interface (WUI), particularly in residential neighborhoods. While significant research and technical guidance is available to understand the potential risks of wildfire threats in the built environment, it primarily focuses on detailed characterizations of the hazard, generally lacking significance, and component-level detail of structure vulnerabilities as well as limited incorporation of the interrelationship of parcel-, neighborhood- and community-characteristics on structure survivability. This study aims to build a more detailed, localized WUI database to conduct data-driven statistical analysis and machine learning to enhance existing frameworks, methods, and tools; to characterize WUI risk more comprehensively; and to better inform wildfire resiliency planning, preparedness, decision-making, damage estimates, and response strategies at localized scales.
2. Objectives
The purpose of the proposed research is to help advance industry knowledge and understanding of holistic parcel-, neighborhood- and community-level wildfire risk to better inform mitigation planning, policies, programs, and regulatory efforts in the WUI. The aim is to develop (1) results-oriented, multi-scale factor enhancements to existing parcel-level WUI scoring tool(s); (2) comprehensive, multi-scale neighborhood and community-scale WUI risk scoring tools; and (3) probabilistic structure damage-loss potential models that are substantiated by assessments of real-world performance. This will be achieved using a combination of quantitative methods (e.g., geospatial statistical analysis, machine learning), semi-quantitative methods (e.g., retrospective analysis, expert panel review), and field data collection to understand, evaluate and design improvements to current tools and methodologies.
3. Benefits
The outcomes of this research will increase industry knowledge and understanding of the spatio-statistical significance and damage potential of wildfire risk at various scales. This will benefit fire departments, fire safety professionals, individuals and communities, providing the ability to prioritize, monitor and evaluate mitigations efforts of higher risk parcels and neighborhoods more effectively, as well as inform incentive structures for neighborhood programs such as Firewise. The tools and associated data dashboards will enhance wildfire education and awareness programs for individuals, community organizations and the general public. Project results will be summarized in conference papers, journal articles, PhD dissertations/theses and training workshops for fire professionals (e.g., SFPE, NFPA). In addition, researchers will coordinate with the JFSP Fire Exchange Network contacts to provide region specific findings for distribution to the broader wildland fire community.
Alan T Murray
University of California-Santa Barbara
Department of Geography

Other Project Collaborators

Other Project Collaborators

Type

Name

Agency/Organization

Branch or Dept

Agreements Contact

Kelly Musselman

University of California-Santa Barbara

Research

Budget Contact

Alycia M Lewis

Co-Principal Investigator

Darlene T Rini

Jensen Hughes

Research, Development, Testing & Evaluation

Co-Principal Investigator

Max Moritz

University of California-Berkeley

Department of Environmental Sciences-Policy & Management

Project Locations

Project Locations

Fire Science Exchange Network

California


Level

State

Agency

Unit

STATE

CA

LOCAL

Local government lands

Final Report

Project Deliverables

Supporting Documents