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First wetland mapping at 10-m spatial resolution in South America using multi-source and multi-feature remote sensing data

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摘要 Wetland degradation has been accelerating in recent years globally. Accurate information on the geographic distribution and categories of wetlands is essential for their conservation and management. Despite being the world′s fourth largest continent, South America has limited research on wetland mapping, and there is currently no available map that provides comprehensive information on wetland distribution and categories in the region. To address this issue, we used Sentinel-1, Sentinel-2 and SRTM data, developed a sample collection method and a wetland mapping method with a collection of multi-source features such as optical features, polarization features and shape features for South American wetlands. We produced a 10-m resolution wetland map based on the Google Earth Engine(GEE) platform. Our Level-1 wetland cover map accurately captured six wetland sub-categories with an overall accuracy of 96.24% and a kappa coefficient of 0.8649, while our Level-2 water cover map included five sub-categories with an overall accuracy of 97.23% and a kappa coefficient of0.9368. The results show that the total area of existing wetlands in South America is approximately 1,737,000 km~2, which is6.8% of the total land area. Among the ten wetland categories, shallow sea had the largest area(960,527.4 km~2), while aquaculture ponds had the smallest area 1513.6 km~2. Swamp had the second largest area(306,240.1 km~2). Brazil, Argentina,Venezuela, Bolivia, and Colombia were found to have the largest wetland areas, with Brazil and Colombia having the most diverse wetland categories. This product can serve as baseline data for subsequent monitoring, management, and conservation of South American wetlands.
出处 《Science China Earth Sciences》 SCIE EI CAS CSCD 2024年第10期3252-3269,共18页 中国科学(地球科学英文版)
基金 supported by the National Natural Science Foundation of China (Grant Nos.42271340,42122009) the Ningbo Science and Technology Innovation 2025 Major Special Project (Grant Nos.2022Z189,2021Z107,2022Z181) the Zhejiang Province ‘Pioneering Soldier’ and ‘Leading Goose’ R&D Project (Grant No.2023C01027)。
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