日本リモートセンシング学会誌
Online ISSN : 1883-1184
Print ISSN : 0289-7911
ISSN-L : 0289-7911
小論文
Development and Verification of SGLI/GCOM-C1 Ocean Algorithms
平田 貴文平譯 享境田 太樹山口 寿史鈴木 光次石坂 丞二小林 拓村上 浩虎谷 充浩藤原 周齊藤 誠一
著者情報
キーワード: Ocean, SGLI, GCOM-C, algorithm
ジャーナル フリー

2014 年 34 巻 4 号 p. 278-285

詳細
抄録
Several ocean algorithms have been developed for the Second-Generation Global Imager (SGLI) on the Global Climate Observation Mission - Climate (GCOM-C) satellite (planned launch, 2016). Here we present verification of the ocean algorithms designed to retrieve the inherent optical properties, phytoplankton functional types and primary productivity. The satellite algorithm verification is defined here to evaluate accuracy of target variables using input parameter(s) obtained from in situ measurements rather than from satellite measurements. The verification of inherent optical properties (IOP) algorithms showed RMSE of 0.12, 0.22, and 0.05 for the absorption coefficient of phytoplankton, detrital materials plus colored dissolved organic materials, and the backscattering coefficient of suspended particles, respectively. Verification of the primary production algorithm indicated that it almost satisfied the values measured in situ by a factor of 2. Other algorithms such as phytoplankton functional types (PFTs) and size classes (PSCs) algorithms, which can be derived from the optical properties of phytoplankton rather than from chlorophyll a concentration, showed RMSE of 10.1-11.6 % in a relative abundance of PFTs/PSCs. Towards validation of the ocean algorithms, a radiometer called the Compact-Optical Profiling System (C-OPS), as well as another compact radiometer system specifically designed for turbid waters, were configured for in situ observation. The latter was found to reduce shelf-shading error to within 10 %. Furthermore, Ultra-High Performance Liquid Chromatography systems (UHPLC) have been developed for rapid measurements (7 min) of phytoplankton pigments in a water sample (conventional HPLC takes 30 min). This new system significantly increases spatio-temporal coverage of in situ data required for algorithm validation.
著者関連情報
© 2014 The Remote Sensing Society of Japan
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