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Editorial

Remote Sensing of Landslides—A Review

1
School of Geology Engineering and Geomatics, Chang’an University, No. 126, Yanta Road, Xi’an 710054, China
2
Huffington Department of Earth Sciences, Southern Methodist University, P.O. Box 750395, Dallas, TX 75275, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(2), 279; https://doi.org/10.3390/rs10020279
Submission received: 7 February 2018 / Revised: 7 February 2018 / Accepted: 8 February 2018 / Published: 11 February 2018
(This article belongs to the Special Issue Remote Sensing of Landslides)

Abstract

Triggered by earthquakes, rainfall, or anthropogenic activities, landslides represent widespread and problematic geohazards worldwide. In recent years, multiple remote sensing techniques, including synthetic aperture radar, optical, and light detection and ranging measurements from spaceborne, airborne, and ground-based platforms, have been widely applied for the analysis of landslide processes. Current techniques include landslide detection, inventory mapping, surface deformation monitoring, trigger factor analysis and mechanism inversion. In addition, landslide susceptibility modelling, hazard assessment, and risk evaluation can be further analyzed using a synergic fusion of multiple remote sensing data and other factors affecting landslides. We summarize the 19 articles collected in this special issue of Remote Sensing of Landslide, in the terms of data, methods and applications used in the papers.
Keywords: landslide; remote sensing; deformation; detection; susceptibility modelling landslide; remote sensing; deformation; detection; susceptibility modelling

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MDPI and ACS Style

Zhao, C.; Lu, Z. Remote Sensing of Landslides—A Review. Remote Sens. 2018, 10, 279. https://doi.org/10.3390/rs10020279

AMA Style

Zhao C, Lu Z. Remote Sensing of Landslides—A Review. Remote Sensing. 2018; 10(2):279. https://doi.org/10.3390/rs10020279

Chicago/Turabian Style

Zhao, Chaoying, and Zhong Lu. 2018. "Remote Sensing of Landslides—A Review" Remote Sensing 10, no. 2: 279. https://doi.org/10.3390/rs10020279

APA Style

Zhao, C., & Lu, Z. (2018). Remote Sensing of Landslides—A Review. Remote Sensing, 10(2), 279. https://doi.org/10.3390/rs10020279

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