{"title":"利用大地遥感卫星图像和植被指数评估塞万湖漂浮水生植被的时空变化","authors":"","doi":"10.52939/ijg.v19i11.2913","DOIUrl":null,"url":null,"abstract":"This research was carried out as part of the \"Copernicus assisted environmental monitoring across the Black Sea Basin – PONTOS\" project, which aimed to support and enhance environmental monitoring in the Black Sea Basin region by utilizing Earth Observation products obtained from satellite, airborne, and ground sources. The project team evaluated the environmental monitoring system in pilot sites across Armenia, Greece, Georgia, and Ukraine. The current study focused on assessing changes in wetland and floating vegetation cover from 2009-2015 in Lake Sevan, the largest freshwater source in Armenia and one of the project's pilot sites. Monitoring spatio-temporal changes in aquatic vegetation is crucial for understanding the ecological and socioeconomic functions of lake ecosystems, and requires standardized methods. In order to identify floating aquatic vegetation in Lake Sevan, this study utilized Landsat TM and OLI imagery that were acquired during the main growing season from middle May to middle September of the years 2009-2015. To enhance the classification process, vegetation indices such as the Normalized Difference Vegetation Index (NDVI), Normalized Difference Aquatic Vegetation Index (NDAVI), and Normalized Difference Water Index (NDWI) were applied. The findings of this study indicate that medium-resolution Landsat and similar satellite images, which are freely available, can be effectively used to monitor spatiotemporal changes in lakes in a reproducible and continuous manner. However, it was also discovered that algal blooms can significantly hinder the accurate detection of floating vegetation from satellite imagery.","PeriodicalId":38707,"journal":{"name":"International Journal of Geoinformatics","volume":"10 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Assessing Spatio-temporal Changes of Floating Aquatic Vegetation in Lake Sevan Using Landsat Imagery and Vegetation Indices\",\"authors\":\"\",\"doi\":\"10.52939/ijg.v19i11.2913\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This research was carried out as part of the \\\"Copernicus assisted environmental monitoring across the Black Sea Basin – PONTOS\\\" project, which aimed to support and enhance environmental monitoring in the Black Sea Basin region by utilizing Earth Observation products obtained from satellite, airborne, and ground sources. The project team evaluated the environmental monitoring system in pilot sites across Armenia, Greece, Georgia, and Ukraine. The current study focused on assessing changes in wetland and floating vegetation cover from 2009-2015 in Lake Sevan, the largest freshwater source in Armenia and one of the project's pilot sites. Monitoring spatio-temporal changes in aquatic vegetation is crucial for understanding the ecological and socioeconomic functions of lake ecosystems, and requires standardized methods. In order to identify floating aquatic vegetation in Lake Sevan, this study utilized Landsat TM and OLI imagery that were acquired during the main growing season from middle May to middle September of the years 2009-2015. To enhance the classification process, vegetation indices such as the Normalized Difference Vegetation Index (NDVI), Normalized Difference Aquatic Vegetation Index (NDAVI), and Normalized Difference Water Index (NDWI) were applied. The findings of this study indicate that medium-resolution Landsat and similar satellite images, which are freely available, can be effectively used to monitor spatiotemporal changes in lakes in a reproducible and continuous manner. However, it was also discovered that algal blooms can significantly hinder the accurate detection of floating vegetation from satellite imagery.\",\"PeriodicalId\":38707,\"journal\":{\"name\":\"International Journal of Geoinformatics\",\"volume\":\"10 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-11-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Geoinformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.52939/ijg.v19i11.2913\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Geoinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52939/ijg.v19i11.2913","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Social Sciences","Score":null,"Total":0}
Assessing Spatio-temporal Changes of Floating Aquatic Vegetation in Lake Sevan Using Landsat Imagery and Vegetation Indices
This research was carried out as part of the "Copernicus assisted environmental monitoring across the Black Sea Basin – PONTOS" project, which aimed to support and enhance environmental monitoring in the Black Sea Basin region by utilizing Earth Observation products obtained from satellite, airborne, and ground sources. The project team evaluated the environmental monitoring system in pilot sites across Armenia, Greece, Georgia, and Ukraine. The current study focused on assessing changes in wetland and floating vegetation cover from 2009-2015 in Lake Sevan, the largest freshwater source in Armenia and one of the project's pilot sites. Monitoring spatio-temporal changes in aquatic vegetation is crucial for understanding the ecological and socioeconomic functions of lake ecosystems, and requires standardized methods. In order to identify floating aquatic vegetation in Lake Sevan, this study utilized Landsat TM and OLI imagery that were acquired during the main growing season from middle May to middle September of the years 2009-2015. To enhance the classification process, vegetation indices such as the Normalized Difference Vegetation Index (NDVI), Normalized Difference Aquatic Vegetation Index (NDAVI), and Normalized Difference Water Index (NDWI) were applied. The findings of this study indicate that medium-resolution Landsat and similar satellite images, which are freely available, can be effectively used to monitor spatiotemporal changes in lakes in a reproducible and continuous manner. However, it was also discovered that algal blooms can significantly hinder the accurate detection of floating vegetation from satellite imagery.