Lu Zhigang, Chen Zihao, Zhou Meng, Lei Daxing, Chen Yifan
School of Resources and Civil Engineering, Gannan University of Science and Technology, Ganzhou, Jiangxi, China.
School of Civil and Surveying, Jiang xi university of Science and Technology, Ganzhou, Jiangxi, China.
PLoS One. 2025 Jul 31;20(7):e0327579. doi: 10.1371/journal.pone.0327579. eCollection 2025.
Continuous monitoring and research on Poyang Lake is essential to understand its ecological dynamics and promote sustainable development. Spatial and temporal dynamic monitoring and analyses of vegetation changes in the water body of Poyang Lake are still limited. This study fills this gap by using remote sensing and GIS techniques for dynamic monitoring and analysing the changes of water bodies and vegetation in Poyang Lake from 2013 to 2021. We used a combination of Maximum Likelihood Classification (MLC) and Support Vector Machine (SVM) to preprocess and classify 42 Landsat 8 OLI images. The results showed that the stability of the water body and vegetation varied greatly, with the water body showing the obvious change pattern of water rises, vegetation recedes and water recedes, vegetation grows, and the high-frequency inundation area was concentrated in the northeastern part of the lake (accounting for 60% of the total inundation area). Vegetation frequency distribution showed a pattern of sparse in the north and dense in the south, with the middle frequency area being the most, accounting for 19.88%, and the low frequency area being the least, accounting for 16.09%. The results show that the spatial and temporal distribution characteristics of water body and vegetation in Poyang Lake show low stability, which is a highly dynamic ecosystem. This study relatively makes up for the missing analysis of the stability change of water body and vegetation in the cycle of Poyang Lake, and provides a solid scientific basis for the protection and sustainable management work.
对鄱阳湖进行持续监测和研究对于了解其生态动态和促进可持续发展至关重要。目前对鄱阳湖水体植被变化的时空动态监测与分析仍较为有限。本研究利用遥感和地理信息系统(GIS)技术对2013年至2021年鄱阳湖水体和植被变化进行动态监测与分析,填补了这一空白。我们采用最大似然分类法(MLC)和支持向量机(SVM)相结合的方法对42景Landsat 8 OLI影像进行预处理和分类。结果表明,水体和植被的稳定性差异较大,水体呈现出明显的涨水植被退、落水植被长的变化规律,高频淹没区集中在湖泊东北部(占总淹没面积的60%)。植被频率分布呈北疏南密格局,中频区面积最大,占19.88%,低频区面积最小,占16.09%。结果表明,鄱阳湖水体和植被的时空分布特征稳定性较低,是一个高度动态的生态系统。本研究相对弥补了鄱阳湖周期内水体和植被稳定性变化分析的缺失,为保护和可持续管理工作提供了坚实的科学依据。