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    Monitoring Harmful Algal Blooms in Small Inland Lakes Utilizing Sentinel-2 Multispectral Imagery

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    MS-GIST_2023_Mendoza.pdf
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    Description:
    MS-GIST Report
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    Author
    Mendoza, Crystal
    Issue Date
    2023
    Keywords
    Harmful algal bloom
    Remote Sensing
    Sentinel-2
    Normalized Difference Chlorophyll Index
    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
    Population growth and climate change continue to jeopardize food security. Modern agricultural practices adapt to these changes by increasing the use of chemicals and fertilizers which directly affects our water quality. Harmful Algal Blooms (HABs) is an overgrowth of blue-green algae, in some cases it contains toxic bacteria caused by excess nutrients in water sources. Local governments test water sources to ensure levels of algae remain safe for consumption and water activities, however the cost to test the water remains high. There is remotely sensed imagery currently that can identify and monitor HABs, however the spatial resolution is too low for small inland lakes and rivers to provide accurate data. This project uses Sentinel-2 multispectral imagery to identify HABs using a normalized difference chlorophyll index (NDCI). The results of the project revealed that the application successfully displayed the location and extent of possible algal blooms based on NDCI values and visual interpretations. The in-situ samples of excess chlorophyll did correlate with the increased chlorophyll of the index when there was in-situ sample data available. As a recommendation for use of NDCI, local testing facilities could focus their sample locations to the locations of where there is high chlorophyll content.
    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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