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Quantifying intertidal habitat relative coverage in a Florida Estuary Using UAS imagery and GEOBIA

Espriella Michael C., Lecours Vincent, C. Frederick Peter, V. Camp Edward et Wilkinson Benjamin. (2020). Quantifying intertidal habitat relative coverage in a Florida Estuary Using UAS imagery and GEOBIA. Remote Sensing, 12, (4), e677.

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Intertidal habitats like oyster reefs and salt marshes provide vital ecosystem services including shoreline erosion control, habitat provision, and water filtration. However, these systems face significant global change as a result of a combination of anthropogenic stressors like coastal development and environmental stressors such as sea-level rise and disease. Traditional intertidal habitat monitoring techniques are cost and time-intensive, thus limiting how frequently resources are mapped in a way that is often insufficient to make informed management decisions. Unoccupied aircraft systems (UASs) have demonstrated the potential to mitigate these costs as they provide a platform to rapidly, safely, and inexpensively collect data in coastal areas. In this study, a UAS was used to survey intertidal habitats along the Gulf of Mexico coastline in Florida, USA. The structure from motion photogrammetry techniques were used to generate an orthomosaic and a digital surface model from the UAS imagery. These products were used in a geographic object-based image analysis (GEOBIA) workflow to classify mudflat, salt marsh, and oyster reef habitats. GEOBIA allows for a more informed classification than traditional techniques by providing textural and geometric context to habitat covers. We developed a ruleset to allow for a repeatable workflow, further decreasing the temporal cost of monitoring. The classification produced an overall accuracy of 79% in classifying habitats in a coastal environment with little spectral and textural separability, indicating that GEOBIA can differentiate intertidal habitats. This method allows for effective monitoring that can inform management and restoration efforts.

Type de document:Article publié dans une revue avec comité d'évaluation
Version évaluée par les pairs:Oui
Date:19 Février 2020
Nombre de pages:1
Identifiant unique:10.3390/rs12040677
Sujets:Sciences naturelles et génie > Sciences appliquées > Océanographie
Sciences naturelles et génie > Sciences naturelles > Sciences de la terre (géologie, géographie)
Département, module, service et unité de recherche:Départements et modules > Département des sciences fondamentales
Unités de recherche > Centre de recherche sur la Boréalie (CREB)
Mots-clés:geographic object-based image analysis, eastern oyster, unoccupied aircraft system, UAS, drone, Florida, coastal habitat, habitat mapping, eCognition, UAV
Déposé le:30 oct. 2023 19:01
Dernière modification:30 oct. 2023 19:01
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Creative Commons LicenseSauf indication contraire, les documents archivés dans Constellation sont rendus disponibles selon les termes de la licence Creative Commons "Paternité, pas d'utilisation commerciale, pas de modification" 2.5 Canada.

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