Wang, XX; Xiao, XM; Zou, ZH; Hou, LY; Qin, YW; Dong, JW; Doughty, RB; Chen, BQ; Zhang, X; Cheng, Y; Ma, J; Zhao, B; Li, B (2020). Mapping coastal wetlands of China using time series Landsat images in 2018 and Google Earth Engine. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 163, 312-326.

Coastal wetlands, composed of coastal vegetation and non-vegetated tidal flats, play critical roles in biodiversity conservation, food production, and the global economy. Coastal wetlands in China are changing quickly due to land reclamation, aquaculture, industrialization, and urbanization. However, accurate and updated maps of coastal wetlands (including vegetation and tidal flats) in China are unavailable, and the detailed spatial distribution of coastal wetlands is unknown. Here, we developed a new pixel- and phenology-based algorithm to identify and map coastal wetlands in China for 2018 using time series Landsat imagery (2798 ETM + /OLI images) and the Google Earth Engine (GEE). The resultant map had a very high overall accuracy (98%). There were 7474.6 km(2) of coastal wetlands in China in 2018, which included 5379.8 km(2) of tidal flats, 1856.4 km(2) of deciduous wetlands, and 238.3 km(2) of evergreen wetlands. Jiangsu Province had the largest area of coastal wetlands in China, followed by Shandong, Fujian, and Zhejiang Provinces. Our study demonstrates the high potential of time series Landsat images, pixel- and phenology-based algorithm, and GEE for mapping coastal wetlands at large scales. The resultant coastal wetland maps at 30-m spatial resolution serve as the most current dataset for sustainable management, ecological assessments, and conservation of coastal wetlands in China.