| Summary: | The maintenance and resilience of tidal flats have become critical concerns in ecological planning for coastal areas, and high-qualified maps are expected to provide worthwhile references to the authorities. Owing to the booming developments in remote sensing systems and high-performance cloud computing services, several frameworks were proposed to map tidal flats on large spatiotemporal scales, but current productions are still far from meeting the practical needs in the United States. Based on Google Earth Engine, a classification model of random forests was proposed in this study, through which we derived an annual map collection of tidal flats in the conterminous United States from 1984 to 2020. Aside from the confusion matrix, a comparison with peers’ work was implemented to further endorse the reliability of the mapping product. The whole study area was divided into four zones, and the map production was examined by analyzing the temporal characteristics, spatial features, and evolutionary trends of tidal flat dynamics in each zone. The results warn that tidal flats throughout the study area are under threat of shrinking, and particularly those along the Atlantic Coast pose a severe environmental and ecological risk for local communities and biodiversity. As such, coastal environments in the United States call for urgent conservation and restoration.
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