Accuracy of surface water maps derived from radar satellite imagery compared to multispectral satellite imagery

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DOI	Trouver le DOI : https://doi.org/10.1080/07038992.2024.2433591
Auteur	Rechercher : Kirby, Katelyn¹Identifiant ORCID : https://orcid.org/0000-0001-9763-9617; Rechercher : Rennie, Colin D.Identifiant ORCID : https://orcid.org/0000-0003-0683-1932; Rechercher : Poot, Riley; Rechercher : Ferguson, Sean¹Identifiant ORCID : https://orcid.org/0000-0001-8007-9211; Rechercher : Cousineau, Julien¹Identifiant ORCID : https://orcid.org/0000-0002-0883-6836; Rechercher : Nistor, Ioan Identifiant ORCID : https://orcid.org/0000-0001-8436-4781
Affiliation	Conseil national de recherches Canada. Génie océanique, côtier et fluvial
Bailleur de fonds	Rechercher : Natural Sciences and Engineering Research Council of Canada; Rechercher : Natural Resources Canada. Office of Energy Research and Development; Rechercher : National Research Council Canada
Format	Texte, Article
Sujet	multispectral Sentinel-2 satellite imagery; synthetic aperture radar Sentinel-1 satellite imagery; classification detection of earth surface water; earth open water observation; comparison of remote sensing products and methods
Résumé	Optical and radar remote sensing are both used to map surface water features. Since use cases range considerably in the literature between applications, a direct comparison is warranted to assess how well each perform in a wide range of geographic settings using a range of classification methods. Thus, surface water maps generated from Sentinel-1 Synthetic Aperture Radar (S1SAR) and Sentinel-2 Multispectral Instrument (S2MSI) imagery were compared across four machine learning techniques and eight diverse image areas in Canada. Additionally, the polarizations and multispectral bands were varied to understand their effect. The results were validated using high resolution satellite imagery, and analysis of variance was calculated. S2MSI consistently produced higher accuracy surface water maps compared to S1SAR. Contrary to previous understanding, the cross-polarization did not produce significantly more accurate surface water maps than like-polarization, and the same was true for dual and single polarization. The introduction of an additional band of multispectral imagery improved accuracy significantly. In flooded conditions, dual polarization produced the best results, and for the detection of ice, cross-polarization produced the best results. These findings will increase the quality and efficient generation of surface water maps for water resource management, climate change impact studies, and other disciplines.
Date de publication	2024-12-05
Maison d’édition	Informa UK Limited
Licence	Creative Commons, Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/deed.fr
Dans	Canadian Journal of Remote Sensing 50, nº 1, 2433591 (5 décembre 2024).
Langue	anglais
Publications évaluées par des pairs	Oui
Exporter la notice	Exporter en format RIS
Signaler une correction	Signaler une correction (s'ouvre dans un nouvel onglet)
Identificateur de l’enregistrement	9a511706-a469-49e6-a57d-a5224b9acb54
Enregistrement créé	2025-06-24
Enregistrement modifié	2025-11-03

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Date de modification :: 2026-09-12