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Zhang X, Liu L, Zhao T, Wang J, Liu W, Chen X. Global annual wetland dataset at 30 m with a fine classification system from 2000 to 2022. Sci Data 2024; 11:310. [PMID: 38521796 PMCID: PMC10960823 DOI: 10.1038/s41597-024-03143-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 03/14/2024] [Indexed: 03/25/2024] Open
Abstract
Wetlands play a key role in maintaining ecological balance and climate regulation. However, due to the complex and variable spectral characteristics of wetlands, there are no publicly available global 30-meter time-series wetland dynamic datasets at present. In this study, we present novel global 30 m annual wetland maps (GWL_FCS30D) using time-series Landsat imagery on the Google Earth Engine platform, covering the period of 2000-2022 and containing eight wetland subcategories. Specifically, we make full use of our prior globally distributed wetland training sample pool, and adopt the local adaptive classification and spatiotemporal consistency checking algorithm to generate annual wetland maps. The GWL_FCS30D maps were found to achieve an overall accuracy and Kappa coefficient of 86.95 ± 0.44% and 0.822, respectively, in 2020, and show great temporal variability in the United States and the European Union. We expect the dataset would provide vital support for wetland ecosystems protection and sustainable development.
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Affiliation(s)
- Xiao Zhang
- International Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China
- Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
| | - Liangyun Liu
- International Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China.
- Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China.
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049, China.
| | - Tingting Zhao
- International Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China
- Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
- College of Geomatics, Xi'an University of Science and Technology, Xi'an, 710054, China
| | - Jinqing Wang
- International Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China
- Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Wendi Liu
- International Research Center of Big Data for Sustainable Development Goals, Beijing, 100094, China
- Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100094, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xidong Chen
- Future Urbanity & Sustainable Environment (FUSE) Lab, The University of Hong Kong, Hong Kong, 999007, China
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Santos CD, Catry T, Dias MP, Granadeiro JP. Global changes in coastal wetlands of importance for non-breeding shorebirds. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 858:159707. [PMID: 36306834 DOI: 10.1016/j.scitotenv.2022.159707] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 10/20/2022] [Accepted: 10/21/2022] [Indexed: 06/16/2023]
Abstract
Shorebird declines are occurring worldwide but the causes are not fully understood. Recent literature suggests that the deterioration of habitat quality at their non-breeding areas, mostly located in temperate and tropical coastal wetlands, might be a major contributing factor. However, most studies carried out so far tend to be restricted to a few regions. Remote sensing can help correct such geographical bias on knowledge by providing a standardized approach on how shorebird habitats have been changing over the last few decades at a global scale. Here we analyzed time series of remote sensing classifications of tidal flats and land cover to quantify worldwide habitat changes in coastal Important Bird and Biodiversity Areas (IBAs) relevant for non-breeding shorebirds over the last two decades. Globally, supratidal areas (used as roosting habitat) have changed more significantly than tidal flats (used as feeding habitat). Yet, we found striking losses of tidal flats in IBAs distributed in several regions of the East Asian - Australasian Flyway. At supratidal areas, there was a general expansion of marshland, grassland and urban areas, contrasting with a decline of barren land, woodland and cropland. The expansion of marshland occurred in IBAs of most regions of the world. Urban areas also expanded consistently in supratidal areas within the most populated regions of the world. The loss of barren land is particularly concerning as it may translate into a loss of high-quality roosts and it was highly frequent in IBAs of all migratory flyways. Overall, our results confirm the large losses of shorebird habitat in the East Asian - Australasian Flyway reported in the literature, and highlight unreported generalized changes in supratidal habitats, such as the expansion of marshland and the loss of barren land, that may have negative implications for shorebirds, deserving further research and consideration in conservation programs.
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Affiliation(s)
- Carlos D Santos
- CESAM Centro de Estudos do Ambiente e do Mar, Faculdade de Ciências, Universidade de Lisboa, Campo Grande, 1749-016 Lisboa, Portugal; Department of Migration, Max Planck Institute of Animal Behavior, Am Obstberg 1, 78315 Radolfzell, Germany; Núcleo de Teoria e Pesquisa do Comportamento, Universidade Federal do Pará, Rua Augusto Correa 01, Guamá, 66075-110 Belém, Brazil.
| | - Teresa Catry
- CESAM Centro de Estudos do Ambiente e do Mar, Faculdade de Ciências, Universidade de Lisboa, Campo Grande, 1749-016 Lisboa, Portugal.
| | - Maria P Dias
- cE3c Center for Ecology, Evolution and Environmental Changes & CHANGE - Global Change and Sustainability Institute, Department of Animal Biology, Faculdade de Ciências, Universidade de Lisboa, Campo Grande, 1749-016 Lisboa, Portugal.
| | - José P Granadeiro
- CESAM Centro de Estudos do Ambiente e do Mar, Faculdade de Ciências, Universidade de Lisboa, Campo Grande, 1749-016 Lisboa, Portugal.
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