Dynamic Analysis of Spartina alterniflora in Yellow River Delta Based on U-Net Model and Zhuhai-1 Satellite

作者：Huiying Li, Guoli Cui, Haojie Liu, Qi Wang, Sheng Zhao, Xiao Huang, Rong Zhang, Mingming Jia, Dehua Mao, Hao Yu, Zongming Wang, Zhiyong Lv · 发表于：Remote Sensing · 年份：2025 · DOI：10.3390/rs17020226 · 被引用次数：8 · 研究领域：Environmental Changes in China

Coastal wetlands are critical for global biodiversity and ecological stability, yet the invasive Spartina alterniflora (S. alterniflora) poses severe threats to these ecosystems. This study evaluates the effectiveness of management efforts targeting S. alterniflora in the Yellow River Delta (YRD) using Zhuhai-1 hyperspectral imagery and the U-Net method. The U-Net model, coupled with the Relief-F algorithm, achieved a superior extraction accuracy (Kappa > 0.9 and overall accuracy of 93%) compared to traditional machine learning methods. From 2019 to 2021, S. alterniflora expanded rapidly, increasing from 4055.06 hm2 to 6105.50 hm2, primarily in tidal flats and water bodies. A clearing project reduced its extent to 5063.62 hm2 by 2022, and by 2023, only 0.55 hm2 remained. These results underscore the effectiveness of Shandong’s management policies but highlight the risk of regrowth due to the species’ resilience. Continuous monitoring and maintenance are essential to prevent its resurgence and ensure wetland restoration. This study offers critical insights into dynamic vegetation monitoring and informs conservation strategies for wetland health.