Remote estimation of Secchi depth using GOCI data
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Title
- Remote estimation of Secchi depth using GOCI data
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Author(s)
- 김원국
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Alternative Author(s)
- 김원국
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Publication Year
- 2017-04-17
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Abstract
- This study provides estimation of Secchi disk depth using GOCI data, and the validation results derived from in-situ measurements of Secchi depth. For the estimation, the input parameters inherent optical properties (IOP) is derived using quasi-analytical algorithm (QAA) based on the Doron’s classic algorithm. The validation results show that the mean normalized gross error is around 30% with mean normalized bias around 10%, when estimated by GOCI.uasi-analytical algorithm (QAA) based on the Doron’s classic algorithm. The validation results show that the mean normalized gross error is around 30% with mean normalized bias around 10%, when estimated by GOCI.
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URI
- https://sciwatch.kiost.ac.kr/handle/2020.kiost/24157
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Bibliographic Citation
- Pacific-Asian Marginal Seas (PAMS) Meeting, pp.1, 2017
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Publisher
- PAMS
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Type
- Conference
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Language
- English
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