Annual Change Analysis of Mangrove Forests in China during 1986–2021 Based on Google Earth Engine
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by
Ziyu Wang,
Kai Liu,
Jingjing Cao,
Liheng Peng,
Xin Wen
Abstract
Mangroves are a key type of protected coastal wetland, with a range of benefits such as protection from wave damage, sand fixation, water purification and ecological tourism. As the academic knowledge of mangroves has gradually increased, the use of remote sensing to monitor their dynamic changes in China has become a hot topic of discussion and has received attention in academic circles. Remote sensing has also provided necessary auxiliary decision-making suggestions and data support for the scientific and rational conservation, restoration and management of mangrove resources. In this paper, we used Landsat satellite series data combined with the normalized difference vegetation index (NDVI) and adaptive threshold partitioning (OTSU method) to monitor mangrove dynamics in coastal China from 1986 to 2021 based on Google Earth Engine (GEE), with three main results. (1) Based on the massive data and efficient computational capability of the GEE platform, we achieved large-scale interannual mangrove distribution extraction. The overall classification accuracy for 2019 exceeded 0.93, and the mangrove distribution extraction effect was good. (2) The total mangrove area and the mean patch size in China showed overall increasing trends, and Guangdong and Guangxi were the top two provinces in China in terms of the largest mangrove area. (3) Except for Dongzhaigang National Nature Reserve, the mangrove areas in other national mangrove reserves mainly showed increasing trends, confirming the effectiveness of the reserves. Data on the spatial structure and area trends of mangroves in China can provide scientific references for mangrove conservation and development, and serve in the further restoration of mangrove ecosystems.
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