Satellite Long-Term Monitoring of Wetland Ecosystem Functioning in Ramsar Sites for Their Sustainable Management

Sustainability Pub Date : 2024-07-23 DOI:10.3390/su16156301
Quentin Demarquet, S. Rapinel, D. Arvor, S. Corgne, L. Hubert‐Moy
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Abstract

The long-term monitoring of wetland ecosystem functioning is critical because wetlands, which provide multiple services, can be affected by human activities and climate change. The aim of this study was to monitor wetland ecosystem functioning in the long term using the Landsat archive. Four contrasting, Ramsar wetlands were selected in boreal, temperate, arid, and tropical areas. First, the annual sum of the normalized difference vegetation index (NDVI-I) was calculated as an indicator of annual net primary productivity for the period 1984–2021 using the continuous change detection and classification (CCDC) algorithm. Next, the influence of the number of Landsat images and class of land use and land cover (LULC) on the accuracy of the CCDC was investigated. Finally, correlations between annual NDVI-I and climate were analyzed. The results revealed that NDVI-I accuracy was influenced mainly by the LULC class and to a lesser extent by the number of cloud-free Landsat observations. Infra- and inter-site variations in NDVI-I were high and showed an overall increasing trend. NDVI-I was positively correlated with the mean temperature. This study shows that this approach applied in contrasting sites is robust for the long-term monitoring of wetland ecosystem functioning and can be used to improve the implementation of international biodiversity conservation policies.
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对拉姆萨尔湿地生态系统功能进行卫星长期监测,促进湿地的可持续管理
对湿地生态系统功能进行长期监测至关重要,因为提供多种服务的湿地可能会受到人类活动和气候变化的影响。本研究旨在利用大地遥感卫星档案对湿地生态系统功能进行长期监测。研究人员在寒带、温带、干旱和热带地区选取了四个不同的拉姆萨尔湿地。首先,使用连续变化检测和分类(CCDC)算法计算归一化差异植被指数(NDVI-I)的年度总和,作为 1984-2021 年期间年度净初级生产力的指标。接下来,研究了陆地卫星图像的数量以及土地利用和土地覆被类别(LULC)对 CCDC 精确度的影响。最后,分析了年度 NDVI-I 与气候之间的相关性。结果表明,NDVI-I 的准确性主要受 LULC 类别的影响,其次才是无云陆地卫星观测数据的数量。NDVI-I 的站内和站间差异很大,且总体呈上升趋势。NDVI-I 与平均气温呈正相关。这项研究表明,在不同地点采用这种方法可以对湿地生态系统功能进行长期监测,并可用于改善国际生物多样性保护政策的实施。
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