A Review of Tidal-Flat Remote Sensing Methods and Applications 2000–2025

Tidal-flats buffer coasts support biodiversity and are changing rapidly, yet reported global declines contrast with local expansions, leaving managers uncertain about the direction and drivers of change. Here we investigate this tension by systematically reviewing how monitoring by remote sensing has been used to observe, extract, validate, and interpret tidal-flat dynamics. We considered the literature from January 2000 to March 2025 and screened 951 records related to 339 research articles, classifying 63% (215/339) predominantly focused on tidal-flat extraction and area change, while 37% (124/339) emphasized the analysis of driving factors. Publications surged after 2019, and three tidal-flat extraction families dominate practice: waterline methods (most widely applied), image classification, and composite/optical–Synthetic Aperture Radar (SAR) fusion. Across studies, the prevailing trend is net decline in tidal-flat extent, attributed to reduced riverine sediment supply, sea level rise, and reclamation; however, robust local counter-examples exist (e.g., ~18% expansion in Germany’s Wadden Sea, 1998–2016), underscoring strong spatial heterogeneity. Although ~31% of global tidal-flats fall within protected areas, effectiveness is uneven under sustained human pressure. We synthesize common failure modes (tide/scale mismatch, validation gaps) and outline standards for multimodal data fusion and benchmarking. This review synthesizes current knowledge on tidal-flat remote sensing methods, identifies key methodological challenges, and outlines priorities for future research to support reliable monitoring.

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Publication Details

Journal
Journal of Marine Science and Engineering
Published
2026-07-27
DOI
https://doi.org/10.3390/jmse14151368
Primary Topic
Coastal wetland ecosystem dynamics
Type
article
Field-Weighted Citation Impact
0.00

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article

A Review of Tidal-Flat Remote Sensing Methods and Applications 2000–2025

Fenzhen Su, Fengqin Yan, Vincent Lyne, Xinyi Wang et al.
Journal of Marine Science and Engineering
Coastal wetland ecosystem dynamics
article

A Review of Tidal-Flat Remote Sensing Methods and Applications 2000–2025

Fenzhen Su, Fengqin Yan, Vincent Lyne, Xinyi Wang, Jiaojie Zhang
article en

Abstract

Tidal-flats buffer coasts support biodiversity and are changing rapidly, yet reported global declines contrast with local expansions, leaving managers uncertain about the direction and drivers of change. Here we investigate this tension by systematically reviewing how monitoring by remote sensing has been used to observe, extract, validate, and interpret tidal-flat dynamics. We considered the literature from January 2000 to March 2025 and screened 951 records related to 339 research articles, classifying 63% (215/339) predominantly focused on tidal-flat extraction and area change, while 37% (124/339) emphasized the analysis of driving factors. Publications surged after 2019, and three tidal-flat extraction families dominate practice: waterline methods (most widely applied), image classification, and composite/optical–Synthetic Aperture Radar (SAR) fusion. Across studies, the prevailing trend is net decline in tidal-flat extent, attributed to reduced riverine sediment supply, sea level rise, and reclamation; however, robust local counter-examples exist (e.g., ~18% expansion in Germany’s Wadden Sea, 1998–2016), underscoring strong spatial heterogeneity. Although ~31% of global tidal-flats fall within protected areas, effectiveness is uneven under sustained human pressure. We synthesize common failure modes (tide/scale mismatch, validation gaps) and outline standards for multimodal data fusion and benchmarking. This review synthesizes current knowledge on tidal-flat remote sensing methods, identifies key methodological challenges, and outlines priorities for future research to support reliable monitoring.

Journal of Marine Science and EngineeringVol. 14(15)
University of Tasmania (AU), Chinese Academy of Sciences (CN), Institute of Geographic Sciences and Natural Resources Research (CN), University of Chinese Academy of Sciences (CN), Virginia Tech (US)
National Natural Science Foundation of China, Youth Innovation Promotion Association of the Chinese Academy of Sciences
Life below water
Openalex Percentile: Top 9%
Coastal wetland ecosystem dynamics
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