Quantitative Inversion of Oil Film Thickness Based on Airborne Hyperspectral Data Using the 1DCNN

Quantitative Inversion of Oil Film Thickness Based on Airborne Hyperspectral Data Using the 1DCNN_GRU Model

Author:

Wang Meiqi¹^ORCID,Yang Junfang¹,Liu Shanwei¹^ORCID,Gu Yanfeng²^ORCID,Xu Mingming¹^ORCID,Ma Yi³^ORCID,Zhang Jie¹,Wan Jianhua¹

Affiliation:

1. College of Oceanography and Space Informatics, China University of Petroleum (East China), Qingdao, China

2. School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin, China

3. First Institute of Oceanography and the Technology Innovation Center for Ocean Telemetry, Ministry of Natural Resources, Qingdao, China

Funder

National Natural Science Foundation of China

Shandong Provincial Natural Science Foundation

Fund of Technology Innovation Center for Ocean Telemetry, Ministry of Natural Resources

Qingdao Postdoctoral Application Research Project

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

Reference47 articles.

3. A new oil spill detection method based on GF-3 quad-polarization SAR imagery;zhang;Remote Sens,2018

4. Oil slick thickness estimation based on Gaussian model and hyperspectral data;chen;J Appl Remote Sens,2016

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