Landslide Displacement Monitoring by a Fully Polarimetric SAR Offset Tracking Method

Wang, Changcheng; Mao, Xiaokang; Wang, Qijie

doi:10.3390/rs8080624

Cited by 30 publications

(23 citation statements)

References 40 publications

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“…The first campaign was implemented by the Brigham Young University using an X-band sensor, with the purpose of correlating the measured movements to the soil water content [24]. More recently, some studies exploiting airborne L-band remote sensing have been presented [25][26][27]. However, so far, the use of satellite technologies in the literature was limited, despite they can provide a cost-effective and continuous update of the landslide state.…”

Section: Introductionmentioning

confidence: 99%

Long-Term Satellite Monitoring of the Slumgullion Landslide Using Space-Borne Synthetic Aperture Radar Sub-Pixel Offset Tracking

Amitrano

Guida

Dell'Aglio³

et al. 2019

Remote Sensing

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Kinematic characterization of a landslide at large, small, and detailed scale is today still rare and challenging, especially for long periods, due to the difficulty in implementing demanding ground surveys with adequate spatiotemporal coverage. In this work, the suitability of space-borne synthetic aperture radar sub-pixel offset tracking for the long-term monitoring of the Slumgullion landslide in Colorado (US) is investigated. This landslide is classified as a debris slide and has so far been monitored through ground surveys and, more recently, airborne remote sensing, while satellite images are scarcely exploited. The peculiarity of this landslide is that it is subject to displacements of several meters per year. Therefore, it cannot be monitored with traditional synthetic aperture radar differential interferometry, as this technique has limitations related to the loss of interferometric coherence and to the maximum observable displacement gradient/rate. In order to overcome these limitations, space-borne synthetic aperture radar sub-pixel offset tracking is applied to pairs of images acquired with a time span of one year between August 2011 and August 2013. The obtained results are compared with those available in the literature, both at landslide scale, retrieved through field surveys, and at point scale, using airborne synthetic aperture radar imaging and GPS. The comparison showed full congruence with the past literature. A consistency check covering the full observation period is also implemented to confirm the reliability of the technique, which results in a cheap and effective methodology for the long-term monitoring of large landslide-induced movements.

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Section: Introductionmentioning

confidence: 99%

Long-Term Satellite Monitoring of the Slumgullion Landslide Using Space-Borne Synthetic Aperture Radar Sub-Pixel Offset Tracking

Amitrano

Guida

Dell'Aglio³

et al. 2019

Remote Sensing

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“…Qu et al [21] develop the hybrid-SAR procedure to combine both amplitude-based and phase-based methods to map and monitor large landslides exhibiting different deformation magnitudes, sliding modes and slope geometries. Using the Slumgullion landslide (southwestern Colorado, USA) as an example, Wang et al [22] propose a fully polarimetric SAR offset tracking method to improve the precision of landslide movement monitoring. Taking the Shuping landslide (Three Gorges, China) as a case study, Sun and Muller [23] demonstrate the capability of sub-Pixel Offset Tracking techniques to monitor relatively fast slope movements in densely vegetated areas with and without the presence of artificial corner reflectors.…”

Section: Landslide Hazardsmentioning

confidence: 99%

Earth Observations for Geohazards: Present and Future Challenges

Tomás

2017

Remote Sensing

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Earth Observations (EO) encompasses different types of sensors (e.g., Synthetic Aperture Radar, Laser Imaging Detection and Ranging, Optical and multispectral) and platforms (e.g., satellites, aircraft, and Unmanned Aerial Vehicles) and enables us to monitor and model geohazards over regions at different scales in which ground observations may not be possible due to physical and/or political constraints. EO can provide high spatial, temporal and spectral resolution, stereo-mapping and all-weather-imaging capabilities, but not by a single satellite at a time. Improved satellite and sensor technologies, increased frequency of satellite measurements, and easier access and interpretation of EO data have all contributed to the increased demand for satellite EO data. EO, combined with complementary terrestrial observations and with physical models, have been widely used to monitor geohazards, revolutionizing our understanding of how the Earth system works. This Special Issue presents a collection of scientific contributions focusing on innovative EO methods and applications for monitoring and modeling geohazards, consisting of four Sections: (1) earthquake hazards; (2) landslide hazards; (3) land subsidence hazards; and (4) new EO techniques and services.

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“…This method was first used to monitor glacial drifts [29][30][31][32][33][34][35][36] and earthquakes [37][38][39][40]. With improvements in SAR resolution, this method has now been used to monitor landslide movements [27,28,[41][42][43] and ground subsidence caused by mining [23][24][25][26].…”

Section: Introductionmentioning

confidence: 99%

An Improved Adaptive Template Size Pixel-Tracking Method for Monitoring Large-Gradient Mining Subsidence

et al. 2017

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The monitoring of large-gradient deformation caused by coal mining is of great significance to the prevention and management of disasters in mining areas. The interferometric synthetic aperture radar (InSAR) method captures the small-gradient ground deformation on the edge of the subsidence basin accurately but is unreliable for capturing large-gradient deformation. The intensitybased pixel-tracking method (e.g., the normalized cross-correlation (NCC) method) can overcome the limitations of InSAR's maximum detectable displacement gradient and incoherence. However, the pixel-tracking method is sensitive to template size. It is difficult to estimate ground subsidence accurately by the conventional pixel-tracking method with fixed template size. In this paper, the signal-to-noise ratio (SNR) is redefined and an improved locally adaptive template size method is proposed by identifying optimal template adaptively based on maximization of the redefined SNR. The constraint radius is used to constrain the search area in this improved method. The frequency of misrepresentation is reduced by finding the peak of the correlation coefficient surface within the search area. Both simulation data and real ground subsidence data are used to test this algorithm. The results show that this method can improve monitoring accuracy compared with the traditional pixel-tracking method for fixed template size.

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Landslide Displacement Monitoring by a Fully Polarimetric SAR Offset Tracking Method

Cited by 30 publications

References 40 publications

Long-Term Satellite Monitoring of the Slumgullion Landslide Using Space-Borne Synthetic Aperture Radar Sub-Pixel Offset Tracking

Long-Term Satellite Monitoring of the Slumgullion Landslide Using Space-Borne Synthetic Aperture Radar Sub-Pixel Offset Tracking

Earth Observations for Geohazards: Present and Future Challenges

An Improved Adaptive Template Size Pixel-Tracking Method for Monitoring Large-Gradient Mining Subsidence

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