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• W3135092891 endingPage "107683" @default.
• W3135092891 startingPage "107683" @default.
• W3135092891 abstract "Intertidal wetlands are dynamic geomorphological areas located at the land-sea interface and perform multiple ecosystem functions. Owing to increased human activities, intertidal wetlands have been subjected to dramatic changes in recent decades; therefore, high-resolution monitoring of wetland topography is critical to its management. However, satellite imagery with high spatial resolution usually demonstrates a low revisit frequency (e.g. several days to greater than ten days) and is frequently obstructed by clouds, limiting its capability to display the high-resolution time-series information of intertidal wetland terrain elevation variations. Conversely, satellite imagery with a high revisit frequency generally demonstrates a lower spatial resolution. In this study, a spatial-temporal data fusion method was utilised to generate hourly time-series images with a spatial resolution of 16 m by combining the satellite GF-1/WFV data (spatial resolution: 16 m; revisit frequency: 4 days) with geostationary satellite GOCI data (spatial resolution: 500 m; revisit frequency: 1 h). In combination with the tidal level information, digital terrain elevation (DTM) data of the intertidal wetland can be derived from fusion images. The DTM was synchronously validated by the terrain elevation data acquired on the same day utilising unmanned aerial vehicle (UAV)-borne LiDAR in the North Branch intertidal wetland of Chongming Island, Yangtze Estuary, with a root mean square error of 0.16 m. The application in Chongming-Dongtan indicates that this method is effective for monitoring high dynamic changes in intertidal wetland terrain elevations." @default.
• W3135092891 created "2021-03-15" @default.
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• W3135092891 date "2021-06-01" @default.
• W3135092891 modified "2023-10-16" @default.
• W3135092891 title "Monitoring terrain elevation of intertidal wetlands by utilising the spatial-temporal fusion of multi-source satellite data: A case study in the Yangtze (Changjiang) Estuary" @default.
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• W3135092891 doi "https://doi.org/10.1016/j.geomorph.2021.107683" @default.
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