Global_Distribution_of_Tidal_Flat_Ecosystems_Det (Map Service)
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Current Version: 10.81
Service Description: The dataset contains global maps of tidal flat ecosystems produced via a supervised classification of 707,528 Landsat Archive images. Each pixel was classified into tidal flat, permanent water or other with reference to a globally distributed set of training data.
The maps were created to identify the non-vegetated areas of Earth’s coastline that undergo regular tidal inundation. In some areas, these occur as tidal flats up to 24-km wide, such as the tidal mudflats of western Europe and East Asia. Our analysis included 56 predictor layers of which many were Landsat composite metrics designed to identify individual pixels that undergo frequent wetting and drying.
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Description: The dataset contains global maps of tidal flat ecosystems produced via a supervised classification of 707,528 Landsat Archive images. Each pixel was classified into tidal flat, permanent water or other with reference to a globally distributed set of training data.
The maps were created to identify the non-vegetated areas of Earth’s coastline that undergo regular tidal inundation. In some areas, these occur as tidal flats up to 24-km wide, such as the tidal mudflats of western Europe and East Asia. Our analysis included 56 predictor layers of which many were Landsat composite metrics designed to identify individual pixels that undergo frequent wetting and drying.
Copyright Text: Murray N. J., Phinn S. R., DeWitt M., Ferrari R., Johnston R., Lyons M. B., Clinton N., Thau D. & Fuller R. A. (2019) The global distribution and trajectory of tidal flats. Nature. 565:222-225. http://dx.doi.org/10.1038/s41586-018-0805-8
Spatial Reference: 102100
Single Fused Map Cache: true
Capabilities: Map,TilesOnly,Tilemap
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- Spatial Reference:
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Export Tiles Allowed: false
Max Export Tiles Count: 100000
Document Info: - Title: Global Distribution of Tidal Flat Ecosystems
- Author: osgur.mcdermott.long_UNEP_WCMC
- Comments:
- Subject: Intertidal Marsh
- Category:
- Keywords: Intertidal Marsh, Extent, Global, Remote sensing