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    DEVLOPING A USER-FRIENDLY TOOL FOR DETERMINING AND MAPPING THE DIFFERENCED NORMALIZED BURN RATIO

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    MS-GIST_2023_Hacker.pdf
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    Description:
    MS-GIST Report
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    Author
    Hacker, Chloe
    Issue Date
    2023-05
    Keywords
    wildfire
    python
    burn ratio
    automate
    Advisor
    Mason, Jennifer
    
    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
    When it comes to wildfire recovery efforts, time is of the essence. Analyses to plan restoration efforts need to be conducted within seven days of wildfire containment. This window ensures that the data collected is most reflective of postfire conditions. It is necessary for the satellite images to capture the near infrared and shortwave infrared reflectance values from the ground before vegetation begins to grow back. This project aims to create a user-friendly tool for analyzing burn severity of wildfires. The goal is to be able to automate these analyses so they can be used for post wildfire land rehabilitation. The difference between pre-fire and post-fire normalized burn ratio provides information regarding where the land was most and least damaged from a wildfire, helpful for informing land managers with post fire recovery efforts, if necessary. A tool developed in this project uses Landsat imagery from before and after the wildfire and runs it through a python script to automatically calculate the difference between pre-fire and post-fire normalized burn ratio and map it. From here, the tool can be applied to any wildfire that has imagery available from before it started and shortly after its containment. The results of this project are a python script to automate mapping the differenced normalized burn ratio that is customizable to be run on any computer with any data saved.
    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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