Sub-continental-scale mapping of tidal wetland composition for East Asia: A novel algorithm integrating satellite tide-level and phenological features

Abstract

Tidal wetlands, the global hotspots of biodiversity and carbon stocks, are currently experiencing widespread modifications in their composition due to human disturbances and changing climate. Accurate mapping of tidal wetland composition is crucial and urgently required for the conservation and management of coastal ecosystem, as well as for maximizing their associated services. However, remote sensing of tidal wetlands is still challenge due to periodic tidal fluctuations, frequent cloud cover, and similar spectral characteristics with terrestrial land-cover types. Previous approaches to mapping the tidal wetlands have been restricted to small study regions or have focused on an individual tidal wetland type, thus limiting their ability to consistently monitor the composition of tidal wetlands over large geographic extents. To address the above issues, we proposed a novel algorithm on Google Earth Engine, called Multi-class Tidal Wetland Mapping by integrating Tide-level and Phenological features (MTWM-TP), to simultaneously map mangroves, salt marshes and tidal flats for specifying large-scale tidal wetland composition. The MTWM-TP algorithm firstly generates several noise-free composite images with different tide levels and phenological stages and then concatenates them into a random forest classifier for further classification. The usage of tide-level and phenological features eliminates inland landscapes and help to distinguish deciduous salt marshes and evergreen mangroves, leading to a statistically significant improvement in accuracy. We applied the algorithm to 10,274 Sentinel-2 images of East Asia and derived a 10-m-resolution multi-class tidal wetland map with an overall accuracy of 97.02% at a sub-continental scale. We found that tidal wetlands occupied 1,308,241 ha of areas in East Asia in 2020, of which 89.12% were tidal flats, 9.39% were salt marshes, and only 1.49% were mangroves. This spatially explicit map of tidal wetland composition will provide valuable guidance for coastal biodiversity protection and blue carbon restoration. In addition, the proposed MTWM-TP algorithm can serve as a reliable means for monitoring sub-continental- or larger-scale tidal wetland composition more broadly.