Recent Landslide Movement in Tsaoling, Taiwan Tracked by TerraSAR-X/TanDEM-X DEM Time Series

Du, Yanan; Liu, Fangzhou; Zhang, Lei; Feng, Guangcai; Li, Zhiwei; Chen, Rou Fei; Lin, Chih Chung

doi:10.3390/rs9040353

Cited by 28 publications

(20 citation statements)

References 45 publications

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“…So we adopted a refined method based on fringe frequency to correct the phase ramp in differential interferograms [18]. Before phase unwrapping, a modified Goldstein filter was used to reduce noise phases [19] and a manual mask applied to eliminate its impact on phase unwrapping from some low coherence areas such as isolated islands and sea areas. In some studies, ionospheric disturbance error of SAR interferogram also needed to be considered [20,21], but we did not find any SAR images contaminated by ionospheric disturbances in this study.…”

Section: Data Coverage and Insar Processingmentioning

confidence: 99%

Subsidence Evolution of the Leizhou Peninsula, China, Based on InSAR Observation from 1992 to 2010

Feng

Peng

2017

Applied Sciences

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Abstract:Over the past two decades, the Leizhou Peninsula has suffered from many geological hazards and great property losses caused by land subsidence. However, the absence of a deformation map of the whole peninsula has impeded the government in making the necessary decisions concerning hazard prevention and mitigation. This study aims to provide the evolution of land deformation (subsidence and uplift) in the whole peninsula from 1992 to 2010. A modified stacking procedure is proposed to map the surface deformation with JERS, ENVISAT, and ALOS1 images. The map shows that the land subsidence mainly occurs along the coastline with a maximum velocity of 32 mm/year and in a wide range of inland arable lands with a velocity between 10 and 19 mm/year. Our study suggests that there is a direct correlation between the subsidence and the surface geology. Besides, the observed subsidence in urban areas, caused by groundwater overexploitation for domestic and industrial use, is moving from urban areas to suburban areas. In nonurban areas, groundwater extraction for aquaculture and arable land irrigation are the main reason for land subsidence, which accelerates saltwater intrusion and coastline erosion if regular surface deformation measurements and appropriate management measures are not taken.

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Section: Data Coverage and Insar Processingmentioning

confidence: 99%

Subsidence Evolution of the Leizhou Peninsula, China, Based on InSAR Observation from 1992 to 2010

Feng

Peng

2017

Applied Sciences

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“…Satellite SAR data used in this special issue include archived ERS and Envisat ASAR [1], ALOS/PALSAR [2,3], COSMO-SkyMed constellation [4], TerraSAR-X [5], TerraSAR-X/TanDEM-X [6], and Sentinel-1 [7]. In addition, "Envisat 2010+" data, which started on 22 October 2010 and lasted until the communication with the Envisat satellite was suddenly lost on 8 April 2012, were involved.…”

Section: Sarmentioning

confidence: 99%

“…Digital elevation models (DEMs) were generated from Indian Remote Sensing Satellite (IRS) P5 images by stererophotogrammetry [16], and TerraSAR-X/TanDEM-X images by InSAR [6], respectively. Then, the DEM difference was used to quantify the erosion and cliff recession and to evaluate the landslide volume [16].…”

Section: Demmentioning

confidence: 99%

“…Moreover, if the mass moved away or so-called erosion occurred, differential DEM technique based on TanDEM-X data could be used geomorphological changes in the catchment region [6]. Finally, the integrated use of satellite, aerial, and drone images and ground-based GPS surveys allowed the mapping of the temporal evolution of a landslide system [1].…”

Section: Landslide Monitoringmentioning

confidence: 99%

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Remote Sensing of Landslides—A Review

2018

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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.

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“…The launches of new generations of optical (e.g., Geoeye-1, WorldView-2, Pleiades 1A and 1B, SPOT5, 6 and 7, Formosat-2 and Kompsat-2, Sentinel-2) and radar (e.g., TerraSAR-X, COSMO-SkyMed, Sentinel-1) satellites with short repeat-pass cycles and high spatial resolutions resulted in better capabilities to acquire data over wide areas shortly after major landslide triggering events [25][26][27][28] and to monitor them at regular intervals [29,30]. In particular, radar interferometry is today frequently applied to landslide detection and monitoring of ground-deformations and landslide processes [31][32][33][34][35][36][37][38].…”

Section: Introductionmentioning

confidence: 99%

Multi-Temporal X-Band Radar Interferometry Using Corner Reflectors: Application and Validation at the Corvara Landslide (Dolomites, Italy)

et al. 2017

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Abstract:From the wide range of methods available to landslide researchers and practitioners for monitoring ground displacements, remote sensing techniques have increased in popularity. Radar interferometry methods with their ability to record movements in the order of millimeters have been more frequently applied in recent years. Multi-temporal interferometry can assist in monitoring landslides on the regional and slope scale and thereby assist in assessing related hazards and risks. Our study focuses on the Corvara landslides in the Italian Alps, a complex earthflow with spatially varying displacement patterns. We used radar imagery provided by the COSMO-SkyMed constellation and carried out a validation of the derived time-series data with differential GPS data. Movement rates were assessed using the Permanent Scatterers based Multi-Temporal Interferometry applied to 16 artificial Corner Reflectors installed on the source, track and accumulation zones of the landslide. The overall movement trends were well covered by Permanent Scatterers based Multi-Temporal Interferometry, however, fast acceleration phases and movements along the satellite track could not be assessed with adequate accuracy due to intrinsic limitations of the technique. Overall, despite the intrinsic limitations, Multi-Temporal Interferometry proved to be a promising method to monitor landslides characterized by a linear and relatively slow movement rates.

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Recent Landslide Movement in Tsaoling, Taiwan Tracked by TerraSAR-X/TanDEM-X DEM Time Series

Cited by 28 publications

References 45 publications

Subsidence Evolution of the Leizhou Peninsula, China, Based on InSAR Observation from 1992 to 2010

Subsidence Evolution of the Leizhou Peninsula, China, Based on InSAR Observation from 1992 to 2010

Remote Sensing of Landslides—A Review

Multi-Temporal X-Band Radar Interferometry Using Corner Reflectors: Application and Validation at the Corvara Landslide (Dolomites, Italy)

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