Benthic river algae mapping using hyperspectral imagery from unoccupied aerial vehicles

dc.contributor.authorLogan, Riley D.
dc.contributor.authorShaw, Joseph A.
dc.date.accessioned2024-07-25T19:51:39Z
dc.date.available2024-07-25T19:51:39Z
dc.date.issued2024-06
dc.description.abstractThe increasing prevalence of nuisance benthic algal blooms in freshwater systems has led to water quality monitoring programs based on the presence and abundance of algae. Large blooms of the nuisance filamentous algae, Cladophora glomerata, have become common in the waters of the Upper Clark Fork River in western Montana. To aid in the understanding of algal growth dynamics, unoccupied aerial vehicle (UAV)-based hyperspectral images were gathered at three field sites along the length of the river throughout the growing season of 2021. Select regions within images covering the spectral range of 400 to 850 nm were labeled based on a combination of professional judgment and spectral profiles and used to train a random forest classifier to identify benthic algal growth across several classes, including benthic growth dominated by Cladophora (Clado), benthic growth dominated by growth forms other than Cladophora (non-Clado), and areas below a visually detectable threshold of benthic growth (bare substrate). After classification, images were stitched together to produce spatial distribution maps of each river reach while also calculating the average percent cover for each reach, achieving an accuracy of approximately 99% relative to manually labeled images. Results of this analysis showed strong variability across each reach, both temporally (up to 40%) and spatially (up to 46%), indicating that UAV-based imaging with high-spatial resolution could augment and therefore improve traditional measurement techniques that are spatially limited, such as spot sampling.
dc.identifier.citationRiley D. Logan and Joseph A. Shaw "Benthic river algae mapping using hyperspectral imagery from unoccupied aerial vehicles," Journal of Applied Remote Sensing 18(2), 024513 (13 June 2024). https://doi.org/10.1117/1.JRS.18.024513
dc.identifier.issn1931-3195
dc.identifier.urihttps://scholarworks.montana.edu/handle/1/18697
dc.language.isoen_US
dc.publisherSPIE-Intl Soc Optical Eng
dc.rightscc-by
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectriver algae
dc.subjecthyperspectral imaging
dc.subjectunoccupied aerial vehicles
dc.subjectwater optics
dc.subjectwater quality
dc.titleBenthic river algae mapping using hyperspectral imagery from unoccupied aerial vehicles
dc.typeArticle
mus.citation.extentfirstpage1
mus.citation.extentlastpage13
mus.citation.issue2
mus.citation.journaltitleJournal of Applied Remote Sensing
mus.citation.volume18
mus.data.thumbpage5
mus.relation.collegeCollege of Engineering
mus.relation.departmentElectrical & Computer Engineering
mus.relation.universityMontana State University - Bozeman

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