High-resolution global maps of tidal flat ecosystems from 1984 to 2019.

Sci Data

Centre for Ecosystem Science, School of Biological, Earth and Environmental Science, University of New South Wales, Sydney, Australia.

Published: September 2022

AI Article Synopsis

  • Researchers have developed globally consistent data on tidal flats, which are coastal ecosystems that regularly experience tidal flooding, to address a lack of information about their distribution and change.
  • Over 1.3 million Landsat images were analyzed to create composite metrics over 12 three-year periods from 1984 to 2019, using machine learning and over 10,000 training samples for classification.
  • The accuracy of these classifications was assessed with stratified random samples, showing overall accuracy rates of 82.2% and 86.1% for different versions of the data, which will help monitor processes affecting coastal ecosystems like human growth and sea level rise.

Article 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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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9448797PMC
http://dx.doi.org/10.1038/s41597-022-01635-5DOI Listing

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