Interferometric Synthetic Aperture Radar Applicability Analysis for Potential Landslide Identification in Steep Mountainous Areas with C/L Band Data

Landslides frequently occur in the mountainous area of southwest China, resulting in infrastructure damage, as well as a loss of life and property. The use of interferometric synthetic aperture radar (InSAR) technology has become increasingly popular due to its wide coverage, high precision, and eff...

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Bibliographic Details
Main Authors: Jin Deng, Keren Dai, Rubing Liang, Lichuan Chen, Ningling Wen, Guang Zheng, Hong Xu
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/15/18/4538
Description
Summary:Landslides frequently occur in the mountainous area of southwest China, resulting in infrastructure damage, as well as a loss of life and property. The use of interferometric synthetic aperture radar (InSAR) technology has become increasingly popular due to its wide coverage, high precision, and efficiency in identifying potential landslides in steep mountainous regions to mitigate risks. This study focused on the Mao County region in China and utilized a small baseline subset of InSAR (SBAS−InSAR) technology with Sentinel-1 and ALOS-2 data to identify the potential landslides and analyze their applicability. To ensure accuracy, the findings were verified using optical image and field surveys. Additionally, a comparative analysis was performed on C-band and L-band SAR data to examine differences in the coherence, geometric distortion, and displacement results, revealing that the L-band has clear advantages in the coherence, suitable observation coverage, and displacement results, while C-band can detect relatively slight displacements. This study aimed to determine the applicability of different SAR satellites for early landslide identification in steep mountainous areas, which can serve as a technical reference for selecting appropriate SAR data and enhancing InSAR identification abilities for potential landslides in the future.
ISSN:2072-4292