| Literature DB >> 32405155 |
Xinxin Wang1,2, Xiangming Xiao2, Zhenhua Zou3, Luyao Hou4, Yuanwei Qin2, Jinwei Dong5, Russell B Doughty2, Bangqian Chen6, Xi Zhang1, Ying Chen7, Jun Ma1, Bin Zhao1, Bo Li1.
Abstract
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 from sea, 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 are 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 (2,798 ETM+/OLI images) and the Google Earth Engine (GEE). The resultant map had a very high overall accuracy (98%). There were 7,474.6 km2 of coastal wetlands in China in 2018, which included 5,379.8 km2 of tidal flats, 1,856.4 km2 of deciduous wetlands, and 238.3 km2 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.Entities:
Keywords: China; Coastal wetlands; Google Earth Engine; coastal vegetation; pixel- and phenology-based algorithm; tidal flats; time series Landsat images
Year: 2020 PMID: 32405155 PMCID: PMC7220062 DOI: 10.1016/j.isprsjprs.2020.03.014
Source DB: PubMed Journal: ISPRS J Photogramm Remote Sens ISSN: 0924-2716 Impact factor: 8.979