ArticleScientific data2022
High-resolution global maps of tidal flat ecosystems from 1984 to 2019.
Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
6 citing papers in PubMed.
- Spatio-temporal patterns and environmental controls of soil organic carbon stocks in global tidal wetlands since 2009.Nature communications · 2026Article
- Priority questions for the next decade of blue carbon science.Nature ecology & evolution · 2026Article
- National coastal wetland mapping over the last four decades: An annual classification with high accuracy.Scientific data · 2026Article
- Dynamics and drivers of tidal flat morphology in China.Nature communications · 2025Article
- Global annual wetland dataset at 30 m with a fine classification system from 2000 to 2022.Scientific data · 2024Article
- High-resolution global maps of tidal flat ecosystems from 1984 to 2019.Scientific data · 2022Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Assessments of the status of tidal flats, one of the most extensive coastal ecosystems, have been hampered by a lack of data on their global distribution and change. Here we present globally consistent, spatially-explicit data of the occurrence of tidal flats, defined as sand, rock or mud flats that undergo regular tidal inundation. More than 1.3 million Landsat images were processed to 54 composite metrics for twelve 3-year periods, spanning four decades (1984-1986 to 2017-2019). The composite metrics were used as predictor variables in a machine-learning classification trained with more than 10,000 globally distributed training samples. We assessed accuracy of the classification with 1,348 stratified random samples across the mapped area, which indicated overall map accuracies of 82.2% (80.0-84.3%, 95% confidence interval) and 86.1% (84.2-86.8%, 95% CI) for version 1.1 and 1.2 of the data, respectively. We expect these maps will provide a means to measure and monitor a range of processes that are affecting coastal ecosystems, including the impacts of human population growth and sea level rise.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.