Using Deep Learning to Detect Land Cover Change and Correlate with Water Quality for the New River 2011-2021

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dc.contributor.authorFoy, Andrewen
dc.coverage.countryUnited Statesen
dc.coverage.stateVirginiaen
dc.date.accessioned2024-08-15T14:32:14Zen
dc.date.available2024-08-15T14:32:14Zen
dc.date.issued2024-04-12en
dc.description.abstractThe land cover composition of a watershed is a critical multivariant factor that affects the water quality of river systems. There have been numerous studies on land cover change in the New River Basin, but most use low resolution satellite imagery, are not recent, and don’t directly correlate to changes in water quality. This research investigates land cover change in the New River-Peak Creek HUC10 (0505000115), which encompasses Claytor Lake in Virginia, from 2010-2022, using high resolution orthophotography and deep learning. Advancements in artificial intelligence have led to expansive growth in the applications of deep learning for remote sensing. There are new deep learning models, which are excellent at learning and characterizing complex land cover semantics, producing high-quality land cover data. This paper reviews the observed benefits of using deep learning methods and demonstrates the applications for assessing land cover effects on water quality. The land cover change in the watershed and the riparian buffer zone of HUC10-0505000115 were statistically analyzed to detect/predict changes in water quality data. There were noticeable benefits to using deep learning to analyze land cover change, but challenges remain in correlating those multivariant changes to statistically significant differences in water quality.en
dc.identifier.urihttps://hdl.handle.net/10919/120937en
dc.language.isoenen
dc.publisherNew River Symposiumen
dc.relation.ispartofNew River Symposium 2024en
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectLand coveren
dc.subjectWater qualityen
dc.subjectDeep learningen
dc.subjectNew Riveren
dc.subjectClaytor Lakeen
dc.subject.lcshNew River (N.C.-W. Va.)en
dc.titleUsing Deep Learning to Detect Land Cover Change and Correlate with Water Quality for the New River 2011-2021en
dc.typePresentationen
dc.typeConference proceedingen
dc.type.dcmitypeTexten
dc.type.dcmitypeStillImageen

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