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Retrieval of snow physical parameters by neural networks and optimal estimation: case study for ground based spectral radiometer system
https://jaxa.repo.nii.ac.jp/records/22632
https://jaxa.repo.nii.ac.jp/records/2263279ce850a-808a-42c8-a537-c7547cccad90
Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2016-06-13 | |||||
タイトル | ||||||
言語 | en | |||||
タイトル | Retrieval of snow physical parameters by neural networks and optimal estimation: case study for ground based spectral radiometer system | |||||
言語 | ||||||
言語 | eng | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
資源タイプ | journal article | |||||
アクセス権 | ||||||
アクセス権 | metadata only access | |||||
アクセス権URI | http://purl.org/coar/access_right/c_14cb | |||||
著者 |
谷川, 朋範
× 谷川, 朋範× Li, Wei× 朽木, 勝幸× 青木, 輝夫× 堀, 雅裕× Stamnes, Knut× Tanikawa, Tomonori× Wei, Li× Kuchiki, Katsuyuki× Aoki, Teruo× Hori, Masahiro× Stamnes, Knut |
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著者所属 | ||||||
宇宙航空研究開発機構地球観測研究センター(JAXA)(EORC): 気象庁気象研究所気候研究部 | ||||||
著者所属 | ||||||
スティーブンス工科大学 | ||||||
著者所属 | ||||||
気象庁気象研究所気候研究部 | ||||||
著者所属 | ||||||
気象庁気象研究所気候研究部 | ||||||
著者所属 | ||||||
宇宙航空研究開発機構地球観測研究センター(JAXA)(EORC) | ||||||
著者所属 | ||||||
スティーブンス工科大学 | ||||||
著者所属(英) | ||||||
en | ||||||
Eerth Observation Research Center, Japan Aerospace Exploration Agency (JAXA)(EORC): Climate Research Department, Meteorological Research Institute | ||||||
著者所属(英) | ||||||
en | ||||||
Stevens Institute of Technology | ||||||
著者所属(英) | ||||||
en | ||||||
Climate Research Department, Meteorological Research Institute | ||||||
著者所属(英) | ||||||
en | ||||||
Climate Research Department, Meteorological Research Institute | ||||||
著者所属(英) | ||||||
en | ||||||
Eerth Observation Research Center, Japan Aerospace Exploration Agency (JAXA)(EORC) | ||||||
著者所属(英) | ||||||
en | ||||||
Stevens Institute of Technology | ||||||
出版者(英) | ||||||
出版者 | The Optical Society | |||||
書誌情報 |
en : Optics Express 巻 23, 号 24, p. 1442-1462, 発行日 2015-11-30 |
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抄録(英) | ||||||
内容記述タイプ | Other | |||||
内容記述 | A new retrieval algorithm for estimation of snow grain size and impurity concentration from spectral radiation data is developed for remote sensing applications. A radiative transfer (RT) model for the coupled atmosphere-snow system is used as a forward model. This model simulates spectral radiant quantities for visible and near-infrared channels. The forward RT calculation is, however, the most time-consuming part of the forward-inverse modeling. Therefore, we replaced it with a neural network (NN) function for fast computation of radiances and Jacobians. The retrieval scheme is based on an optimal estimation method with a priori constraints. The NN function was also employed to obtain an accurate first guess in the retrieval scheme. Validation with simulation data shows that a combination of NN techniques and optimal estimation method can provide more accurate retrievals than by using only NN techniques. In addition, validation with in-situ measurements conducted by using ground-based spectral radiometer system shows that comparison between retrieved snow parameters with in-situ measurements is acceptable with satisfactory accuracy. The algorithm provides simultaneous, accurate and fast retrieval of the snow properties. The algorithm presented here is useful for airborne/satellite remote sensing. | |||||
内容記述 | ||||||
内容記述タイプ | Other | |||||
内容記述 | 形態: カラー図版あり | |||||
内容記述(英) | ||||||
内容記述タイプ | Other | |||||
内容記述 | Physical characteristics: Original contains color illustrations | |||||
ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 1094-4087 | |||||
DOI | ||||||
識別子タイプ | DOI | |||||
関連識別子 | http://dx.doi.org/10.1364/OE.23.0A1442 | |||||
関連名称 | info:doi/10.1364/OE.23.0A1442 | |||||
資料番号 | ||||||
内容記述タイプ | Other | |||||
内容記述 | 資料番号: PA1610001000 |