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dc.contributor.advisorKorgaonkar, Yoganand
dc.contributor.authorEdwards, Desiree
dc.date.accessioned2025-05-14T15:49:51Z
dc.date.available2025-05-14T15:49:51Z
dc.date.issued2025
dc.identifier.urihttp://hdl.handle.net/10150/677080
dc.description.abstractWildfires pose a significant threat to natural resources, communities, infrastructure like homes on the Fort Apache Indian Reservation. This project developed a GIS- based wildfire risk assessment model utilizing available data and analytical tools in ArcGIS Pro. The analysis incorporated key environmental variables including fuel models from LANDFIRE, topographic features derived from USGS Earth Explorer, and proximity to communities. A weighted overlay approach was applied to classify areas into no risk. low, moderate, high and extreme wildfire risk zones. By adapting methodologies like kriging and weighted overlay, this study has ensured a replicable and objective assessment and framework. The final wildfire risk maps are able to support land managers in prioritizing mitigation efforts and resource allocation for planning and emergency response efforts.en_US
dc.language.isoen_USen_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © 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.en_US
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en_US
dc.subjectWildfireen_US
dc.subjectcommunitiesen_US
dc.subjectFort Apache Indian Reservationen_US
dc.subjectWeighted Overlayen_US
dc.subjectrisk assessmenten_US
dc.titleWildland Fire Risk Analysis on the Fort Apache Indian Reservationen_US
dc.typeElectronic Reporten_US
dc.typetext
thesis.degree.grantorUniversity of Arizonaen_US
thesis.degree.levelmastersen_US
thesis.degree.disciplineGeographic Information Systems Technologyen_US
thesis.degree.nameM.S.en_US
dc.description.collectioninformationThis 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.en_US
refterms.dateFOA2025-05-14T15:49:54Z


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