Time Series Scattering Power Decomposition Using Ensemble Average in Temporal–Spatial Domains: Application to Forest Disturbance Detection-Reference-Cited by-同舟云学术

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Time Series Scattering Power Decomposition Using Ensemble Average in Temporal–Spatial Domains: Application to Forest Disturbance Detection

Published:2024 Issue: Volume:21 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Sugimoto Ryu¹^ORCID,Natsuaki Ryo²^ORCID,Nakamura Ryosuke¹,Tsutsumi Chiaki¹^ORCID,Yamaguchi Yoshio³^ORCID

Affiliation:

1. Digital Architecture Research Center, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan

2. Department of Electrical Engineering and Information Systems, The University of Tokyo, Tokyo, Japan

3. Faculty of Engineering, Niigata University, Niigata, Japan

Funder

New Energy and Industrial Technology Development Organization

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Geotechnical Engineering and Engineering Geology

Link

http://xplorestaging.ieee.org/ielx7/8859/10365397/10371285.pdf?arnumber=10371285

Reference16 articles.

1. General Four-Component Scattering Power Decomposition With Unitary Transformation of Coherency Matrix

2. Model-Based Six-Component Scattering Matrix Power Decomposition

3. Extension of Scattering Power Decomposition to Dual-Polarization Data for Tropical Forest Monitoring

4. The drivers and impacts of Amazon forest degradation

5. Refined algorithm for forest early warning system with ALOS-2/PALSAR-2 ScanSAR data in tropical forest regions

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