Quentin Demarquet, S. Rapinel, D. Arvor, S. Corgne, L. Hubert‐Moy
{"title":"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","authors":"Quentin Demarquet, S. Rapinel, D. Arvor, S. Corgne, L. Hubert‐Moy","doi":"10.3390/su16156301","DOIUrl":null,"url":null,"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.","PeriodicalId":509360,"journal":{"name":"Sustainability","volume":"115 15","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Satellite Long-Term Monitoring of Wetland Ecosystem Functioning in Ramsar Sites for Their Sustainable Management\",\"authors\":\"Quentin Demarquet, S. Rapinel, D. Arvor, S. Corgne, L. Hubert‐Moy\",\"doi\":\"10.3390/su16156301\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":509360,\"journal\":{\"name\":\"Sustainability\",\"volume\":\"115 15\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Sustainability\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3390/su16156301\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainability","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/su16156301","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Satellite Long-Term Monitoring of Wetland Ecosystem Functioning in Ramsar Sites for Their Sustainable Management
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.