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    Investigating Trends, Causes, and Patterns of Idaho Wildfires

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    Name:
    MS-GIST_2025_Henley.pdf
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    Description:
    MS-GIST Report
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    Author
    Henley, Ethan
    Issue Date
    2025
    Keywords
    fire ecology
    regression
    hot spots
    climate
    spatial statistics
    Advisor
    Korgaonkar, Yoga
    
    Metadata
    Show full item record
    Publisher
    The University of Arizona.
    Rights
    Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
    Collection Information
    This item is part of the MS-GIST Master's Reports collection. For more information about items in this collection, please contact the UA Campus Repository at repository@u.library.arizona.edu.
    Abstract
    Wildfires have become increasingly more common in much of the West, posing a large threat to both human and natural resources. This study uses a variety of spatial statistical methods to investigate the patterns, trends, and causes of wildfires across the state of Idaho. Leveraging tools such as the Global Moran’s I and Hot Spot Analysis to identify significant clusters and emerging trends of fire patterns, Standard Deviational Ellipses were also employed to show the dispersion and orientation of wildfire occurrences. Regression analysis, including ordinary least squares (OLS) and geographically weighted regression (GWR), was used to examine how fire management practices influence the spatial patterns of wildfire incident sizes. The results indicate that human and natural-caused fires exhibit reverse patterns: human-caused fires tend to be smaller but more costly, whereas natural-caused fires tend to be larger but less costly. Unsurprisingly, human fires tend to be concentrated around higher population densities, while natural fires tend to occur in more remote areas. These findings highlight the importance of more localized and data-driven approaches to wildfire management and policy decision-making.
    Type
    Electronic Report
    text
    Degree Name
    M.S.
    Degree Level
    masters
    Degree Program
    Geographic Information Systems Technology
    Degree Grantor
    University of Arizona
    Collections
    MS-GIST (Master's Reports)

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