Estimating the model parameters for remote sensing reflectance pixel by pixel: a neural network approach for optically deep waters-Reference-Cited by-同舟云学术

Estimating the model parameters for remote sensing reflectance pixel by pixel: a neural network approach for optically deep waters

Published:2023-07-28 Issue:15 Volume:44 Page:4666-4683
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Chen Jun¹,Dou Xianhui¹,He Xianqiang²,Xu Min¹,Li Xinyue³,Pan Delu²

Affiliation:

1. Key Laboratory of Physical Electronics and Devices, Ministry of Education, Faculty of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an, China

2. State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou, China

3. School of Ocean Sciences, China University of Geosciences, Beijing, China

Funder

International Cooperation in Science and Technology Innovation among Governments

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2023.2237666

Reference45 articles.

1. An analytical model for subsurface irradiance and remote sensing reflectance in deep and shallow case-2 waters

2. The quasi-analytic remote sensing algorithm of CDOM in the China Yellow Sea and East Sea

3. Satellite remote sensing of the geographical distribution of suspended particle size in an energetic shelf sea

4. OSOAA: a vector radiative transfer model of coupled atmosphere-ocean system for a rough sea surface application to the estimates of the directional variations of the water leaving reflectance to better process multi-angular satellite sensors data over the ocean

5. Influence of the angular shape of the volume-scattering function and multiple scattering on remote sensing reflectance

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