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GIS-Based Community Risk Assessment - Tools for wildfire prediction and mitigation

March 25, 2013

Introduction:

Wildfire is a disastrous force, responsible for significant forest and property loss. Wildfire hazards are one of the most notoriously destructive and devastating natural hazards in the United States. The high cost and severe damage that forest fires cause is blamed, in part, on the difficulty in predicting and responding to fire in a timely manner. Planners and policy makers are in need of tools that enable them to make decisions about where to locate particular land uses and community assets to avoid wildfire hazards in communities that are most susceptible to such natural and manmade disasters. GIS can provide these effective planning tools and insights to plan for natural and manmade disasters, so that we can be prepared to confront these disasters before they happen and mitigate their impact on the community after they occur. This way, both policy makers and the community at large can plan for both pre- and post-disaster response and mitigation.

There are numerous wildfire methodologies that primarily focus on predicting where the fire is most likely to occur based on historic data and spatial characteristics of the environment. What’s missing is knowledge of the impact of wildfire on vulnerable populations and critical infrastructure. To that end, predicting fire hazards by modeling areas that are most vulnerable to fire and measuring the impact on the community’s assets and human and physical resources is both important and warranted to mitigate wildfire hazards and associated costs and fatalities. Intensifying and improving emergency response in areas most susceptible to the frequency of fire occurrence, based on data interpolation and prior delineation of these areas, can help save lives and precious resources. Cognizant of the importance of forest-urban interface fire predication and mitigation, this paper focuses on conducting a community risk assessment from a planning point of view and further proposes a GIS-based multiple-criteria evaluation (MCE) framework for analyzing, predicting, and ultimately mitigating the impact of wildfires.

 

Purpose of the Study and Target Area:

On the whole, the purpose of this study is to develop a systematic methodology for assessment of wildfire impact on community’s critical assets, including human capital and infrastructure assets. In particular, this study is interested in conducting spatial modeling and representation of wildfire hazard analysis; spatio-temporal interpolation of communities at risk; developing a standardized planning support system (PSS) for methodology of GIS-based regional molding of Wildfire Susceptibility Index (WFSI) for planning and policy making; identifying areas at risk (hotspots) and vulnerable communities; and providing better assessment tools and capabilities for future land use planning policymaking.

The target area is Travis County, Texas, which houses nearly a million people and includes the cities of Austin, Jonestown, and Round Rock. The county includes major population, business, and educational hubs such as the University of Texas at Austin.

 

Geospatial Methods and Analyses:

This analysis is composed of three key indicators. These include temporal, spatial, and human indicators, representing the potential for ignition, potential for fire combustibility and propagation (or how fast the fire spreads), and potential ramification on the community respectively. This way, the analysis captures not only the risk and probability of wildfires, but also the magnitude of impact on the community.

  • The potential for ignition: this is measured by the temporal indicators including current and historical climate data about precipitation, drought events, lightning strikes, wind speed and direction; current and historical fire occurrence data; and current and historical emergency calls data.

  • The potential for fire combustibility and propagation: this is measured by a set of spatial indicators including existing fuel and topographic data (such as fuel types, slope, elevation, and aspect); and fire suppression capability (such as initial dispatch locations and spatial morphology data about emergency response time, fire containment, and dry hydrants).

  • The potential ramification on the community: this is measured by existing data on population centers, urban interface, critical infrastructure, and evacuation potential.

A community survey was conducted and several meetings with the local community were held to collaboratively determine the importance of each of these indicators in the analysis, which is represented by the weights assigned to them.

 

This analysis trilogy translates into the following conceptual diagram that includes risk analysis, hazard analysis, and potential ramification to create fire propensity index, fire behavior/spatial diffusion index, and sensitive areas contingency valuation index. Each of these three pillars is inclusive of several factors and layers.

 

A Recipe for Disaster:

Wildfire can cause a blazing inferno with a potential of speed ranging from 30-40 miles per hour which causes the fire to spread fast, creating firenado potential. Three main ingredients can contribute to this; weather conditions, surface fuel, and topography, among other factors.

            1- Weather conditions:

  • Severe drought pattern: the area has been experiencing a drought condition  for the past 10 years

  • Low precipitation: the area is currently receiving only 50-60% of normal precipitation

            2- Surface Fuel:

  • High forest density and canopy cover

  • Crown fire potential

  • Dry vegetation: because of the severe drought, west Austin is densely covered with highly flammable trees and brush

            3- Topography:

  • Steep slope in west Austin's hills and canyons

  • High wind speed and direction

  • High elevation

            4- Other factors:

  • High fire ignition risk related to transportation and historic wildfire occurrences

  • High population density

  • Poor access related to transportation network and urban morphology

  • Low fire suppression capacity in terms of locations and levels of coverage of nearby fire departments

 

Each of the factors listed in the conceptual diagram was represented by a separate layer that was created, extracted, or derived from other data sources or a combination thereof. Figure below shows these layers used for the analysis.

 

Analysis Results:

GIS is used to create and extract data layers to represent each factor listed in the conceptual diagram and conduct spatial analysis to derive density, propensity, and proximity maps. These maps were consolidated and combined into the six category maps which are juxtaposed and overplayed (after assigning weights reflecting the community’s priorities) to produce the final map representing the Wildfire Susceptibility Index (WFSI).

 

The final map shows that areas in red and orange are locations threatened by extreme and very high potential for wildfire breakouts respectively. Areas, such as north Travis County and west Austin, are identified as high risk areas because of the current drought conditions, high forest density and canopy cover, flammable vegetation, steep slopes, in addition to the concentration of population and critical infrastructure located in these areas, combined with the relative lack of resources and fire suppression capacity. The three-dimensional diagram shows very high and extreme to better understand the level of risk and magnitude of impact on these communities affected by potential wildfire.

 

Conclusion:

This article provided a methodology for conducting community risk assessment for wildfire hazard on a regional scale, and provided evidence of the value of using GIS in data management, and organization and planning analysis. This analysis is imperative for emergency respondents, on one hand, and planners and policy makers, on the other. GIS is used to help model areas that are most vulnerable to wildfire so that we can predict where the fire is most likely to happen and be able to respond in a timely manner to mitigate its impact. By knowing the population at risk, communities will be able to determine where to allocate future resources most effectively. Planners can also use this analysis to inform future land use polices and visions and guide their decisions regarding future growth areas. The results can also be disseminated to inform future land use suitability analysis and conflict maps to avoid future expansion in those areas identified as high risk areas for wildfire hazard. Therefore, this spatial knowledge is critical for land use policy and decision making.

In a nutshell, GIS is an invaluable tool to conduct this analysis and produce actionable knowledge and intelligence. By integrating data, geo-processing tools, model builder and visualization tools, we can evaluate the impact of human activities on the natural and built environment. Both state-of-the-art GIS visualization and analytical tools help in understanding and analyzing the spatial and temporal characteristics of wildfire, which is a spatial phenomenon in nature. In addition, GIS modeling capabilities, allows us to apply cutting edge technology to make informed decision about future growth and effective resource allocation to save money and precious human lives. Knowing where wildfire is most likely to occur and identifying vulnerable communities gives us the advantage to plan our cities today to confront inevitable disasters tomorrow.

 

Original post: GIS-Based Community Risk Assessment - Tools for wildfire prediction and mitigation

 

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