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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Quentin Demarquet & Sébastien Rapinel & Damien Arvor & Samuel Corgne & Laurence Hubert-Moy, 2024. "Satellite Long-Term Monitoring of Wetland Ecosystem Functioning in Ramsar Sites for Their Sustainable Management," Sustainability, MDPI, vol. 16(15), pages 1-18, July.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:15:p:6301-:d:1441196
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    References listed on IDEAS

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    1. Lê, Sébastien & Josse, Julie & Husson, François, 2008. "FactoMineR: An R Package for Multivariate Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 25(i01).
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