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Data and codes for "Observed thresholds in sea-level rise driving global tidal wetland loss"

Identification

Public canonical key

radar:r-0dde3e93302de44676112e26eddb2b9e

Authors

Luo, Jiejun

Reported year

2026

Reported language

und

Source type

ComputationalNotebook

First detected

2026-11-13T15:28:28.581929+00:00

Last metadata observation

2026-11-13T15:28:28.581929+00:00

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Not checked

Institutions reported by the source

East China Normal University

Documentary abstract — original language

Data and code for reproducing the results of this study are provided, implemented in Python 3.11.0 and executable in Jupyter notebooks.   The uploaded data are organized into three folders: Data – Contains the data required to reproduce the main results of the paper. Data_Processing – Illustrates the main data processing workflow. Figures_and_Tables – Presents the main results shown in the main text. Public datasets used in this study (data name and access link only): Global local sea‑level trends and uncertainties (Prandi et al., 2021) – https://www.seanoe.org/data/00637/74862 Vertical land motion trends and uncertainties (Oelsmann et al., 2024) – https://zenodo.org/records/8308347 Global salt marsh gain/loss maps (Campbell et al., 2022) – https://www.earthdata.nasa.gov/data/catalog/ornl-cloud-global-salt-marsh-change-2122-1 Global mangrove change (Bunting et al., 2022) – https://zenodo.org/records/6894273 Global tidal wetland change (salt marshes & mangroves; Murray et al., 2022) – https://developers.google.com/earth-engine/datasets/catalog/JCU_Murray_GIC_global_tidal_wetland_change_2019 Global tidal marsh extent in 2020 (Worthington et al., 2024)– https://zenodo.org/records/8420753 Global Mangrove extent in 2020 (Bunting et al., 2024) – https://zenodo.org/records/12756047 Global permanent surface water distribution in 2020 (Pekel et al., 2016) – https://developers.google.com/earthengine/datasets/catalog/JRC_GSW1_4_YearlyHistory Global aquaculture pond dataset in 2020 (Wang et al., 2022) – https://doi.org/10.5281/zenodo.5643036 Global tidal elevations (FES2014 tide model; Lyard et al., 2021) – https://www.aviso.altimetry.fr/en/data/products/auxiliary-products/global-tide-fes.html Monthly non‑organic solid particulate matter (SPM) in sea water – https://data.marine.copernicus.eu/product/OCEANCOLOUR_GLO_BGC_L4_NRT_009_102 Tide gauge relative sea level trends (NOAA) – https://tidesandcurrents.noaa.gov/sltrends/sltrends.html Global ocean gridded sea surface heights (0.125°) – https://data.marine.copernicus.eu/product/SEALEVEL_GLO_PHY_L4_MY_008_047 References Prandi, P. et al. Local sea level trends, accelerations and uncertainties over 1993–2019. Sci Data 8, 1 (2021). Oelsmann, J. et al. Regional variations in relative sea‑level changes influenced by nonlinear vertical land motion. Nat. Geosci. 17, 137–144 (2024). Campbell, A. D., Fatoyinbo, L., Goldberg, L. & Lagomasino, D. Global hotspots of salt marsh change and carbon emissions. Nature 612, 701–706 (2022). Bunting, P. et al. Global mangrove extent change 1996–2020: Global mangrove watch version 3.0. Remote Sensing 14, 3657 (2022). Murray, N. J. et al. High‑resolution mapping of losses and gains of Earth’s tidal wetlands. Science 376, 744–749 (2022). Worthington, T. A. et al. The distribution of global tidal marshes from Earth observation data. Glob. Ecol. Biogeogr. 33, e13852 (2024). Bunting, P. et al. Global Mangrove Watch: Annual Mangrove Extent (4.0.19) [Data set]. Zenodo (2024). https://doi.org/10.5281/zenodo.12756047 Pekel, J.-F., Cottam, A., Gorelick, N. & Belward, A. S. High‑resolution mapping of global surface water and its long‑term changes. Nature 540, 418–422 (2016). Wang, Z. et al. Global mapping of the landside clustering of aquaculture ponds from dense time‑series 10 m Sentinel‑2 images on Google Earth Engine. Int. J. Appl. Earth Obs. Geoinf. 115, 103100 (2022). Lyard, F. H., Allain, D. J., Cancet, M., Carrère, L. & Picot, N. FES2014 global ocean tide atlas: design and performance. Ocean Sci. 17, 615–649 (2021).

Identifiers

DOI

10.5281/zenodo.20138963

OAI

oai:zenodo.org:20138963

Documentary context

Documentary family

unknown

Source-reported types

ComputationalNotebook

Publishers

Zenodo

Entity mentions are not evidence of legal recognition. Jurisdiction studied is separate from author affiliation country.

Sources

DataCite · Record 1

• Document · https://zenodo.org/doi/10.5281/zenodo.20138963

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