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Mapping values at risk, assessing building loss and evaluating stakeholder expectations of wildfire mitigation in the wildland-urban interface

Date

2020

Authors

Caggiano, Michael, author
Hoffman, Chad, advisor
Amidon, Tim, committee member
Cheng, Antony S., committee member
Hawbaker, Todd, committee member

Journal Title

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Volume Title

Abstract

The Wildland-Urban Interface (WUI) is an area where residential development extends into undeveloped land. When WUI development occurs in hazard-prone fire-adapted ecosystems, wildfires can have detrimental impacts on human communities by destroying buildings and infrastructure. Wildfires that cause substantial building loss are known as WUI disasters because of their high social and economic costs. WUI disasters tend to occur when wildfires ignite under extreme burning conditions and threaten a large number of homes in hazardous conditions relative to firefighting resources. This combination of factors can lead to significant home loss. WUI disasters annually result in billions of dollars in fire suppression costs and destroy thousands of homes Governments, land managers, and effected stakeholders respond to this threat in numerous ways as they attempt to mitigate the impacts of wildfires and reduce losses in WUI communities. Although wildfire mitigation efforts emphasize the removal of nearby flammable vegetation and the use of nonflammable building materials, one of the critical steps involves developing a map of communities and buildings at risk in the WUI. Despite broad-scale mapping efforts, most WUI maps do not identify building locations at sufficiently fine scales to estimate fire exposure and inform wildfire planning. Defensible space is promoted as the most effective way to reduce home ignition; however, questions remain surrounding its interactions with fire response, and its efficacy under the wide range of potential fire behavior to which homes could be exposed. This dissertation sought to realize three goals: first, it examined the potential of new technologies to map the WUI and the buildings within it at fine scales; second, it evaluated how well existing WUI mapping efforts capture the pattern of building loss observed during WUI disasters; and third, it examined stakeholder perspectives on the efficacy and interactions of defensible space and fire response with regards to protecting homes from WUI disasters. Chapter two evaluates the ability of Object Based Image Analysis to extract WUI building locations from orthoimagery of the wildland-urban interface by testing accuracy and error at multiple scales. I found the approach can extract building locations with high rates of accuracy, and minimal user input. Extracting building locations using this approach can lead to comprehensive datasets of building locations in the WUI, which can be used to create more detailed maps of buildings exposed to wildfires. Such maps have utility for risk mapping, fuel treatment prioritization, and incident management, and can lead to a better understanding regarding the spatial patterns of home loss. Chapter three leverages building location data to quantify the impacts of WUI disasters and evaluate the accuracy of WUI maps. I compare how well existing polygon-based SILVIS WUI maps and point-based WUI maps capture the pattern of building loss and assess building loss in relation to the core components of the WUI definition. Findings can be used to improve existing WUI maps, create point-based WUI maps from building location datasets, identify which homes are most in need of defensible space, and refine risk mapping and identification of wildfire exposure zones. Finally, chapter four assesses stakeholder perspectives regarding the efficacy of defensible space and its interactions with fire response with regards to the stakeholders' ability to protect homes from WUI disasters. This is related to the prior mapping efforts because it speaks to the ways stakeholders co-manage wildfire risk with fire protection authorities, and the actions they take to protect threatened homes mapped using the methods evaluated in chapters one and two. These qualitative methods suggest a wide range in expectations of defensible space efficacy, both in theory and in practice. It is likely that numerous factors reduce the perceived and actual efficacy of defensible space.

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Subject

mapping
wildland urban interface
wildfire
GIS

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