A neural network method to correct bidirectional effects in water-leaving radiance

Yongzhen Fan, Wei Li, Kenneth Voss, Charles K. Gatebe, Knut Stamnes

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

The standard method to convert the measured water-leaving radiances from the observation direction to the nadir direction developed by Morel and coworkers requires knowledge of the chlorophyll concentration (CHL). Also, the standard method was developed for open ocean water, which makes it unsuitable for turbid coastal waters. We introduce a neural network method to convert the water-leaving radiance (or the corresponding remote sensing reflectance) from the observation direction to the nadir direction. This method does not require any prior knowledge of the water constituents or the inherent optical properties (IOPs). This method is fast, accurate and can be easily adapted to different remote sensing instruments. Validation using NuRADS measurements in different types of water shows that this method is suitable for both open ocean and coastal waters. In open ocean or chlorophyll-dominated waters, our neural network method produces corrections similar to those of the standard method. In turbid coastal waters, especially sediment-dominated waters, a significant improvement was obtained compared to the standard method.

Original languageEnglish (US)
Title of host publicationRadiation Processes in the Atmosphere and Ocean, IRS 2016: Proceedings of the International Radiation Symposium (IRC/IAMAS)
PublisherAmerican Institute of Physics Inc.
Volume1810
ISBN (Electronic)9780735414785
DOIs
StatePublished - Feb 22 2017
EventInternational Radiation Symposium 2016: Radiation Processes in the Atmosphere and Ocean, IRS 2016 - Auckland, New Zealand
Duration: Apr 16 2016Apr 22 2016

Other

OtherInternational Radiation Symposium 2016: Radiation Processes in the Atmosphere and Ocean, IRS 2016
CountryNew Zealand
CityAuckland
Period4/16/164/22/16

Fingerprint

radiance
coastal water
water
oceans
chlorophylls
remote sensing
sediments
reflectance
optical properties

ASJC Scopus subject areas

  • Physics and Astronomy(all)

Cite this

Fan, Y., Li, W., Voss, K., Gatebe, C. K., & Stamnes, K. (2017). A neural network method to correct bidirectional effects in water-leaving radiance. In Radiation Processes in the Atmosphere and Ocean, IRS 2016: Proceedings of the International Radiation Symposium (IRC/IAMAS) (Vol. 1810). [120001] American Institute of Physics Inc.. https://doi.org/10.1063/1.4975575

A neural network method to correct bidirectional effects in water-leaving radiance. / Fan, Yongzhen; Li, Wei; Voss, Kenneth; Gatebe, Charles K.; Stamnes, Knut.

Radiation Processes in the Atmosphere and Ocean, IRS 2016: Proceedings of the International Radiation Symposium (IRC/IAMAS). Vol. 1810 American Institute of Physics Inc., 2017. 120001.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Fan, Y, Li, W, Voss, K, Gatebe, CK & Stamnes, K 2017, A neural network method to correct bidirectional effects in water-leaving radiance. in Radiation Processes in the Atmosphere and Ocean, IRS 2016: Proceedings of the International Radiation Symposium (IRC/IAMAS). vol. 1810, 120001, American Institute of Physics Inc., International Radiation Symposium 2016: Radiation Processes in the Atmosphere and Ocean, IRS 2016, Auckland, New Zealand, 4/16/16. https://doi.org/10.1063/1.4975575
Fan Y, Li W, Voss K, Gatebe CK, Stamnes K. A neural network method to correct bidirectional effects in water-leaving radiance. In Radiation Processes in the Atmosphere and Ocean, IRS 2016: Proceedings of the International Radiation Symposium (IRC/IAMAS). Vol. 1810. American Institute of Physics Inc. 2017. 120001 https://doi.org/10.1063/1.4975575
Fan, Yongzhen ; Li, Wei ; Voss, Kenneth ; Gatebe, Charles K. ; Stamnes, Knut. / A neural network method to correct bidirectional effects in water-leaving radiance. Radiation Processes in the Atmosphere and Ocean, IRS 2016: Proceedings of the International Radiation Symposium (IRC/IAMAS). Vol. 1810 American Institute of Physics Inc., 2017.
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