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  1. H300 宇宙地球環境研究所
  2. H300a 雑誌掲載論文
  3. 学術雑誌

A Neural Network Model for K(λ) Retrieval and Application to Global Kpar Monitoring

http://hdl.handle.net/2237/25263
http://hdl.handle.net/2237/25263
70367202-8bde-4c23-a3c8-a8326824564b
名前 / ファイル ライセンス アクション
journal_pone_0127514.pdf journal_pone_0127514.pdf (12.7 MB)
Item type 学術雑誌論文 / Journal Article(1)
公開日 2016-12-19
タイトル
タイトル A Neural Network Model for K(λ) Retrieval and Application to Global Kpar Monitoring
言語 en
著者 Chen, Jun

× Chen, Jun

WEKO 68337

en Chen, Jun

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Zhu, Yuanli

× Zhu, Yuanli

WEKO 68338

en Zhu, Yuanli

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Wu, Yongsheng

× Wu, Yongsheng

WEKO 68339

en Wu, Yongsheng

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Cui, Tingwei

× Cui, Tingwei

WEKO 68340

en Cui, Tingwei

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Ishizaka, Joji

× Ishizaka, Joji

WEKO 68341

en Ishizaka, Joji

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Ju, Yongtao

× Ju, Yongtao

WEKO 68342

en Ju, Yongtao

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アクセス権
アクセス権 open access
アクセス権URI http://purl.org/coar/access_right/c_abf2
権利
言語 en
権利情報 © 2015 Chen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
抄録
内容記述タイプ Abstract
内容記述 Accurate estimation of diffuse attenuation coefficients in the visible wavelengths Kd(λ) from remotely sensed data is particularly challenging in global oceanic and coastal waters. The objectives of the present study are to evaluate the applicability of a semi-analytical Kd(λ) retrieval model (SAKM) and Jamet’s neural network model (JNNM), and then develop a new neural network Kd(λ) retrieval model (NNKM). Based on the comparison of Kd(λ) predicted by these models with in situ measurements taken from the global oceanic and coastal waters, all of the NNKM, SAKM, and JNNM models work well in Kd(λ) retrievals, but the NNKM model works more stable and accurate than both SAKM and JNNM models. The near-infrared band-based and shortwave infrared band-based combined model is used to remove the atmospheric effects on MODIS data. The Kd(λ) data was determined from the atmospheric corrected MODIS data using the NNKM, JNNM, and SAKM models. The results show that the NNKM model produces <30% uncertainty in deriving Kd(λ) from global oceanic and coastal waters, which is 4.88-17.18% more accurate than SAKM and JNNM models. Furthermore, we employ an empirical approach to calculate Kpar from the NNKM model-derived diffuse attenuation coefficient at visible bands (443, 488, 555, and 667 nm). The results show that our model presents a satisfactory performance in deriving Kpar from the global oceanic and coastal waters with 20.2% uncertainty. The Kpar are quantified from MODIS data atmospheric correction using our model. Comparing with field measurements, our model produces ~31.0% uncertainty in deriving Kpar from Bohai Sea. Finally, the applicability of our model for general oceanographic studies is briefly illuminated by applying it to climatological monthly mean remote sensing reflectance for time ranging from July, 2002- July 2014 at the global scale. The results indicate that the high Kd(λ) and Kpar values are usually found around the coastal zones in the high latitude regions, while low Kd(λ) and Kpar values are usually found in the open oceans around the low-latitude regions. These results could improve our knowledge about the light field under waters at either the global or basin scales, and be potentially used into general circulation models to estimate the heat flux between atmosphere and ocean.
言語 en
出版者
出版者 PLOS
言語 en
言語
言語 eng
資源タイプ
資源タイプresource http://purl.org/coar/resource_type/c_6501
タイプ journal article
出版タイプ
出版タイプ VoR
出版タイプResource http://purl.org/coar/version/c_970fb48d4fbd8a85
DOI
関連タイプ isVersionOf
識別子タイプ DOI
関連識別子 https://doi.org/10.1371/journal.pone.0127514
ISSN
収録物識別子タイプ EISSN
収録物識別子 1932-6203
書誌情報 en : PLoS ONE

巻 10, 号 6, p. e0127514, 発行日 2015-06-17
著者版フラグ
値 publisher
URI
識別子 http://dx.doi.org/10.1371/journal.pone.0127514
識別子タイプ DOI
URI
識別子 http://hdl.handle.net/2237/25263
識別子タイプ HDL
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