Performance Study of Landslide Detection Using Multi-Temporal SAR Images

Performance Study of Landslide Detection Using Multi-Temporal SAR Images

This study addresses one of the most commonly-asked questions in synthetic aperture radar (SAR)-based landslide detection: How the choice of datatypes affects the detection performance. In two examples, the 2018 Hokkaido landslides in Japan and the 2017 Putanpunas landslide in Taiwan, we utilize the...

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Bibliographic Details
Main Authors:	Yunung Nina Lin, Yi-Ching Chen, Yu-Ting Kuo, Wei-An Chao
Format:	Article
Language:	English
Published:	MDPI AG 2022-05-01
Series:	Remote Sensing
Subjects:	SAR-based landslide detection Growing Split-Based Approach (GSBA) Hokkaido landslide Putanpunas landslide SAR polarimetry model-free 3-component decomposition for full polarimetric data (MF3CF)
Online Access:	https://www.mdpi.com/2072-4292/14/10/2444

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