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

Quentin Demarquet, Sébastien Rapinel (), Damien Arvor, Samuel Corgne and Laurence Hubert-Moy
Additional contact information
Quentin Demarquet: LETG UMR 6554, Geography Department, Université Rennes 2, Centre National de la Recherche Scientifique (CNRS), Place du Recteur Henri Le Moal, 35000 Rennes, France
Sébastien Rapinel: LETG UMR 6554, Geography Department, Université Rennes 2, Centre National de la Recherche Scientifique (CNRS), Place du Recteur Henri Le Moal, 35000 Rennes, France
Damien Arvor: LETG UMR 6554, Geography Department, Université Rennes 2, Centre National de la Recherche Scientifique (CNRS), Place du Recteur Henri Le Moal, 35000 Rennes, France
Samuel Corgne: LETG UMR 6554, Geography Department, Université Rennes 2, Centre National de la Recherche Scientifique (CNRS), Place du Recteur Henri Le Moal, 35000 Rennes, France
Laurence Hubert-Moy: LETG UMR 6554, Geography Department, Université Rennes 2, Centre National de la Recherche Scientifique (CNRS), Place du Recteur Henri Le Moal, 35000 Rennes, France

Sustainability, 2024, vol. 16, issue 15, 1-18

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.

Keywords: Landsat; Google Earth Engine; CCDC; ecosystem degradation; biodiversity preservation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/16/15/6301/pdf (application/pdf)
https://www.mdpi.com/2071-1050/16/15/6301/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:16:y:2024:i:15:p:6301-:d:1441196

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().