基于多传感器时间序列的湿地退化监测——以长江湿地为例

Jinquan Ai, Chunmei Niu, Jiangtao Zhu, Huangjing Li, Lijuan Chen
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引用次数: 1

摘要

有效监测和评估土地退化对土地管理者和决策者作出最佳土地管理决策至关重要。本研究旨在提出一种监测崇明东滩湿地土地退化的方法,该湿地在过去几十年中已经观察到湿地退化和植物入侵。选取2013 - 2016年多传感器影像时间序列,基于土地覆盖分类和变化检测技术,识别复垦导致的土地退化速率和状况。结果表明,各图像分类的总体准确率均在80%以上,Kappa统计一致性大于0.74。根据分类结果和变化检测结果,分别生成各时期土地退化分布图。滨海湿地退化的主要类型为湿地退化、生物多样性丧失和湿地水文状态变化。虽然气候变化在研究区土地退化中起着重要的作用,但人类活动,特别是大规模开垦活动更直接地受到研究区土地退化的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Wetland degradation monitoring using time series of multi-sensor data: A case study of Yangtze River
Effective monitoring and assessment of land degradation are essential for the land manager and decision-makers to make optimal land management decisions. This work aims to present a methodology to monitor land degradation in the Chongming Dongtan wetland, where wetland degradation and plant invasions have been observed in the past few decades. Time series of multi-sensor imagery from 2013 to 2016 were selected to identify the rate and status of land degradation due to reclamation based on land cover classification and change detection techniques. Results showed that the overall accuracy of each image classification was higher than 80% and Kappa statistics of agreement more than 0.74. The distribution maps of land degradation in each period were generated respectively based on the classification and change detection results. Coastal wetlands decline, biodiversity loss and wetland hydrological regime change are the main degraded types. Although climate change plays an important role, human activities especially via large-scale reclamations are more directly impacted by land degradation in the study area.
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