A robust and flexible satellite aerosol retrieval algorithm for multi-angle polarimetric measurements with physics-informed deep learning method-Reference-Cited by-同舟云学术

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A robust and flexible satellite aerosol retrieval algorithm for multi-angle polarimetric measurements with physics-informed deep learning method

Published:2023-11 Issue: Volume:297 Page:113763
ISSN:0034-4257
Container-title:Remote Sensing of Environment
language:en
Short-container-title:Remote Sensing of Environment

Author:

Tao Minghui,Chen Jinxi,Xu Xiaoguang,Man Wenjing,Xu Lina,Wang Lunche,Wang Yi,Wang Jun,Fan Meng,Shahzad Muhammad Imran,Chen Liangfu

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Geology,Soil Science

Reference47 articles.

1. Validation of GRASP algorithm product from POLDER/PARASOL data and assessment of multi-angular polarimetry potential for aerosol monitoring;Chen;Earth Syst. Sci. Data,2020

2. Multi-angular polarimetric remote sensing to pinpoint global aerosol absorption and direct radiative forcing;Chen;Nat. Commun.,2022

3. Advances in multiangle satellite remote sensing of speciated airborne particulate matter and association with adverse health effects: from MISR to MAIA;Diner;J. Appl. Remote. Sens.,2018

4. Analytical prediction of scattering properties of spheroidal dust particles with machine learning;Chen;Geophys. Res. Lett.,2022

5. Use of neural networks in ground-based aerosol retrievals from multi-angle spectropolarimetric observations;Di Noia;Atmos. Meas. Tech.,2015

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