School of Geography and Ocean Science, Collaborative Innovation Center of South China Sea Studies, Nanjing University, Nanjing, Jiangsu 210023, China; Key Laboratory of Coastal Zone Exploitation and Protection, Ministry of Natural Resources, Nanjing, Jiangsu 210019, China.
School of Geography and Ocean Science, Collaborative Innovation Center of South China Sea Studies, Nanjing University, Nanjing, Jiangsu 210023, China; Key Laboratory of Coastal Zone Exploitation and Protection, Ministry of Natural Resources, Nanjing, Jiangsu 210019, China; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, Jiangsu 210023, China.
Mar Pollut Bull. 2020 Nov;160:111697. doi: 10.1016/j.marpolbul.2020.111697. Epub 2020 Sep 29.
Coastal wetland vegetation is crucial for providing multiple ecosystem services. However, accurate assessment of wetland vegetation is problematic due to the challenging coastal environment. Using Xiangshan Bay (XB) in China as a typical case study, we developed a time series biological phenological approach to classifying coastal wetland vegetation using Landsat time-series images from 1984 to 2018. The results demonstrate that the total vegetation area of coastal wetlands in XB in 2018 was ~85.3 km. The interannual dynamics of coastal wetland vegetation area in XB in the last 35 years can be divided into three periods: increasing volatility (1984-1998), decreasing (1999-2004), and increasing volatility (2005-2018). Our results emphasize the potential of the use of the time-series biological phenological approach for monitoring coastal wetland vegetation, which can contribute to the sustainable management of coastal ecosystems.
滨海湿地植被对于提供多种生态系统服务至关重要。然而，由于沿海环境具有挑战性，因此准确评估湿地植被存在问题。本研究以中国象山湾为例，利用 1984 年至 2018 年的陆地卫星时间序列图像，开发了一种时间序列生物物候方法来对滨海湿地植被进行分类。结果表明，2018 年象山湾滨海湿地的植被总面积约为 85.3km2。在过去 35 年中，象山湾滨海湿地植被面积的年际动态可分为三个时期：增加的不稳定性（1984-1998 年）、减少（1999-2004 年）和增加的不稳定性（2005-2018 年）。本研究结果强调了使用时间序列生物物候方法监测滨海湿地植被的潜力，这有助于沿海生态系统的可持续管理。
