Coastal Risk & Erosion$39
Coastal Erosion Monitoring
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Wetlands & Land Cover$39
Wetland Mapping and Loss Detection
Wetlands store approximately 30% of terrestrial carbon yet have declined by an estimated 35% since 1970.
Category
Wetlands & Land Cover
Format
PDF Report
Delivery
Digital download after purchase
Price
$39
Summary
Wetlands store approximately 30% of terrestrial carbon yet have declined by an estimated 35% since 1970. Accurate and repeatable mapping is critical for carbon market verification, biodiversity compliance, and climate modelling. This study presents a deep learning pipeline for wetland delineation and temporal change detection using freely available Sentinel-2 Level-2A imagery at 10 m resolution. A U-Net convolutional neural network, trained on labels derived from ESA WorldCover 2021 and JRC Global Surface Water, segments wetland extent across ten internationally recognised wetland complexes spanning six Köppen climate zones.
What the report covers
Wetlands store approximately 30% of terrestrial carbon yet have declined by an estimated 35% since 1970.
Accurate and repeatable mapping is critical for carbon market verification, biodiversity compliance, and climate modelling.
This study presents a deep learning pipeline for wetland delineation and temporal change detection using freely available Sentinel-2 Level-2A imagery at 10 m resolution.
Why it matters
Wetland and land-cover monitoring supports environmental reporting, compliance workflows, and change detection where repeatability matters.
Intended sectors and users
EnvironmentGovernmentCarbon marketsConservation
Methodology framing
The report is framed around Sentinel-2, SAR, deep learning, U-Net, change detection, using the methods described in the source abstract and paper title.
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Applications and use cases
Wetland delineation
Loss detection
Land-cover monitoring
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