日本地球惑星科学連合2018年大会

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セッション記号 A (大気水圏科学) » A-OS 海洋科学・海洋環境

[A-OS12] 陸域海洋相互作用

2018年5月22日(火) 10:45 〜 12:15 106 (幕張メッセ国際会議場 1F)

コンビーナ:山敷 庸亮(京都大学大学院総合生存学館)、升本 順夫(東京大学大学院理学系研究科)、Behera Swadhin(Climate Variation Predictability and Applicability Research Group, Application Laboratory, JAMSTEC, 3173-25 Showa-machi, Yokohama 236-0001、共同)、佐々木 貴教(京都大学 大学院理学研究科 宇宙物理学教室)、座長:升本 順夫佐々木 貴教(京都大学大学院理学研究科宇宙物理学教室)

12:00 〜 12:15

[AOS12-12] Mapping of submerged aquatic vegetation in the lake using the multispectral satellite remote sensing approach

*Shweta Yadav1Minoru YonedaJunichi SusakiYosuke Alexandre Yamashiki (1.Disaster Prevention Research Institute, Kyoto University, Kyoto, Japan)

キーワード:Submerged Aquatic Vegetation, Water Quality, Remote Sensing

Submerged Aquatic Vegetation (SAV) plays a central role in stabilizing the freshwater ecosystem and can also potentially affect the water quality of inland or coastal water bodies. Recently, the massive overgrowth of invasive SAV species associated primarily with the anthropogenic nutrient enrichment negatively affecting the water quality, biodiversity and recreational activities of many freshwater ecosystems in the world. However, the temporal and spatial monitoring of SAV and other optically active components such as chlorophyll is commonly hindered by the limited accessibility and the cost involved in the site-specific observations for many large lakes. In this study, we present a satellite remote sensing based approach for the monitoring of SAV for the Lake Biwa (2014-2016). A spectral decomposition algorithm was used to estimate the concentration of optically active substances and water clarity, using the Landsat-8 satellite images. The image was used to classify and map the SAV coverage area using the spectral mixture analysis. The SAV biomass estimation model was used to determine biomass of the SAV classified pixels in the lake. The satellite-derived water quality and SAV result were validated using the in-situ measurements of the lakes.