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Object-based random forest wetland mapping in Conne River, Newfoundland, Canada

Par Conseil national de recherches du Canada

DOITrouver le DOI : https://doi.org/10.1117/1.JRS.15.038506
AuteurRechercher : ; Rechercher : ; Rechercher : 1; Rechercher : ; Rechercher : ; Rechercher : ; Rechercher :
Affiliation
  1. Conseil national de recherches du Canada. Génie océanique, côtier et fluvial
FormatTexte, Article
Sujetwetlands; classification; watershed; multispectral classification; image classification; data modeling; remote sensing; vegetation; image segmentation; visualization; accuracy assessment; feature extraction; roads; synthetic aperture radar
Résumé
The Conne River watershed is dominated by wetlands that provide valuable ecosystem services, including contributing to the survivability and propagation of Atlantic salmon, an important subsistence species that has shown a dramatic decline over the past 30 years. To better understand and improve the management of the watershed, and in turn, the Atlantic salmon, a wetland inventory of the area is developed using advanced remote sensing methods including field-collected data, object-based image analysis of Sentinel-1, Sentinel-2, and digital elevation model Earth observation data. The resulting classification maps consisted of bog, fen, swamp, marsh, and open water wetlands with an overall accuracy of 92% and a kappa coefficient of 0.916. Among wetland classes, user and producer accuracies range between 84% and 100%. Results show the dominance of peatland wetlands such as bog and fen, and the relative rareness of marsh wetlands.
Date de publication
Maison d’éditionSPIE
Dans
  • Journal of Applied Remote Sensing 15, nº 3 (28 août 2021).
Langueanglais
Publications évaluées par des pairsOui
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Identificateur de l’enregistrement4b9500c9-8943-4b53-bb55-f16bf01905fc
Enregistrement créé2023-02-24
Enregistrement modifié2023-02-24
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