Machine-Learning Inversion of Forest Vertical Structure Based on 2-D-SGVBVoG Model for P-Band Pol-InSAR-Reference-Cited by-同舟云学术

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Machine-Learning Inversion of Forest Vertical Structure Based on 2-D-SGVBVoG Model for P-Band Pol-InSAR

Published:2022 Issue: Volume:60 Page:1-15
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Sun Xiaofan¹,Wang Bingnan¹,Xiang Maosheng¹,Zhou Liangjiang¹,Wang Shuai¹,Jiang Shuai²

Affiliation:

1. National Key Laboratory of Microwave Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China

2. Beijing Institute of Spacecraft System Engineering, China Academy of Space Technology, Beijing, China

Funder

Equipment Development Department Pre-Research Fund

European Space Agency (ESA) through the BIOSAR 2008 Campaign

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/9633014/09756661.pdf?arnumber=9756661

Reference48 articles.

1. S‐RVoG model for forest parameters inversion over underlying topography

2. Assessment of Scattering Mechanism of Polarimetric SAR Signal From Mountainous Forest Areas

3. A Temporal Decorrelation Model for Polarimetric Radar Interferometers

4. Synthetic aperture radar interferometry

5. Forest Height Estimation by Means of Pol-InSAR Data Inversion: The Role of the Vertical Wavenumber

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Forest Parameter Inversion Method based on Double-Bounce Scattering Components of Polarimetric P-Band SAR Data;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07

2. Estimation of Canopy Height From a Multi-SINC Model in Mediterranean Forest With Single-Baseline TanDEM-X InSAR Data;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

3. Maximum a Posteriori Inversion for Forest Height Estimation Using Spaceborne Polarimetric SAR Interferometry;IEEE Transactions on Geoscience and Remote Sensing;2023

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