Remote sensing retrievals optical (10 Ergebnisse)
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Hardcover. Zustand: new. Hardcover. Inland waters and the coastal ocean are vital components of the biosphere, underpinning atmospheric processes and regional climate regulation through primary production, carbon storage, and greenhouse gas emissions. Inland waters also serve economic roles, providing water for agriculture, aqua…culture, recreation, and drinking. As the key zone for land-ocean material exchange, the coastal ocean holds immense ecological value. In recent decades, industrial and urban pollution has had a catastrophic impact on these aquatic systems, reducing water transparency, intensifying eutrophication, and triggering frequent cyanobacteria blooms. With large-scale synchronous observation capabilities and long-term datasets, satellite imagery has become a mainstream data source for global and regional aquatic environment research.Water colour remote sensing is a core focus of this journal, and this Special Issue is in close alignment with this theme. The research contained herein primarily involves the retrieval of the optical/non-optical parameters of inland and coastal waters from multispectral or hyperspectral radiance data. These derived products rely on bio-optical models integrating empirical/semi-empirical, analytical/semi-analytical, quasi-analytical, and machine learning algorithms. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Hardcover. Zustand: new. Hardcover. Inland waters and the coastal ocean are vital components of the biosphere, underpinning atmospheric processes and regional climate regulation through primary production, carbon storage, and greenhouse gas emissions. Inland waters also serve economic roles, providing water for agriculture, aqua…culture, recreation, and drinking. As the key zone for land-ocean material exchange, the coastal ocean holds immense ecological value. In recent decades, industrial and urban pollution has had a catastrophic impact on these aquatic systems, reducing water transparency, intensifying eutrophication, and triggering frequent cyanobacteria blooms. With large-scale synchronous observation capabilities and long-term datasets, satellite imagery has become a mainstream data source for global and regional aquatic environment research.Water colour remote sensing is a core focus of this journal, and this Special Issue is in close alignment with this theme. The research contained herein primarily involves the retrieval of the optical/non-optical parameters of inland and coastal waters from multispectral or hyperspectral radiance data. These derived products rely on bio-optical models integrating empirical/semi-empirical, analytical/semi-analytical, quasi-analytical, and machine learning algorithms. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Hardcover. Zustand: new. Hardcover. Inland waters and the coastal ocean are vital components of the biosphere, underpinning atmospheric processes and regional climate regulation through primary production, carbon storage, and greenhouse gas emissions. Inland waters also serve economic roles, providing water for agriculture, aqua…culture, recreation, and drinking. As the key zone for land-ocean material exchange, the coastal ocean holds immense ecological value. In recent decades, industrial and urban pollution has had a catastrophic impact on these aquatic systems, reducing water transparency, intensifying eutrophication, and triggering frequent cyanobacteria blooms. With large-scale synchronous observation capabilities and long-term datasets, satellite imagery has become a mainstream data source for global and regional aquatic environment research.Water colour remote sensing is a core focus of this journal, and this Special Issue is in close alignment with this theme. The research contained herein primarily involves the retrieval of the optical/non-optical parameters of inland and coastal waters from multispectral or hyperspectral radiance data. These derived products rely on bio-optical models integrating empirical/semi-empirical, analytical/semi-analytical, quasi-analytical, and machine learning algorithms. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Buch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Inland waters and the coastal ocean are vital components of the biosphere, underpinning atmospheric processes and regional climate regulation through primary production, carbon storage, and greenhouse gas emissions. Inland waters also serve econo…mic roles, providing water for agriculture, aquaculture, recreation, and drinking. As the key zone for land-ocean material exchange, the coastal ocean holds immense ecological value. In recent decades, industrial and urban pollution has had a catastrophic impact on these aquatic systems, reducing water transparency, intensifying eutrophication, and triggering frequent cyanobacteria blooms. With large-scale synchronous observation capabilities and long-term datasets, satellite imagery has become a mainstream data source for global and regional aquatic environment research.Water colour remote sensing is a core focus of this journal, and this Special Issue is in close alignment with this theme. The research contained herein primarily involves the retrieval of the optical/non-optical parameters of inland and coastal waters from multispectral or hyperspectral radiance data. These derived products rely on bio-optical models integrating empirical/semi-empirical, analytical/semi-analytical, quasi-analytical, and machine learning algorithms.
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Buch. Zustand: Neu. Remote Sensing Retrievals of Optical Properties in Inland Waters and the Coastal Ocean | Buch | Englisch | 2025 | MDPI AG | EAN 9783725859757 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
