Landslide monitoring on the Stromboli volcano through SAR interferometry

2004 ◽  
pp. 803-808 ◽  
Author(s):  
N Casagli ◽  
P Farina ◽  
D Leva ◽  
D Tarchi
Keyword(s):  
Sar Interferometry ◽  
Landslide Monitoring ◽  
Stromboli Volcano

Landslide monitoring on a short and long time scale by using ground-based SAR interferometry

2003 ◽  
Author(s):  
Nicola Casagli ◽  
Paolo Farina ◽  
Davide Leva ◽  
Giovanni Nico ◽  
Dario Tarchi
Keyword(s):  
Time Scale ◽  
Sar Interferometry ◽  
Landslide Monitoring ◽  
Long Time

Corner Reflector Network as a Geodetic Reference for Landslide Monitoring via InSAR Time Series: Case Study from Slovakia

2021 ◽  
Author(s):  
Richard Czikhardt ◽  
Juraj Papco ◽  
Peter Ondrejka ◽  
Peter Ondrus ◽  
Pavel Liscak
Keyword(s):  
Time Series ◽  
Horizontal Displacement ◽  
Terrestrial Reference Frame ◽  
Sar Interferometry ◽  
Global Navigation Satellite Systems ◽  
Reference Network ◽  
Landslide Monitoring ◽  
First Order ◽  
Order Estimation ◽  
Better Than

<p>SAR interferometry (InSAR) is inherently a relative geodetic technique requiring one temporal and one spatial reference to obtain the datum-free estimates on millimetre-level displacements within the network of radar scatterers. To correct the systematic errors, such as the varying atmospheric delay, and solve the phase ambiguities, it relies on the first-order estimation network of coherent point scatterers (PS).</p><p>For vegetated and sparsely urbanized areas, commonly affected by landslides in Slovakia, it is often difficult to construct a reliable first-order estimation network, as they lack the PS. Purposedly deploying corner reflectors (CR) at such areas strengthens the estimation network and, if these CR are collocated with a Global Navigation Satellite Systems (GNSS), they provide an absolute geodetic reference to a well-defined terrestrial reference frame (TRF), as well as independent quality control.</p><p>For landslides, line-of-sight (LOS) InSAR displacements can be difficult to interpret. Using double CR, i.e. two reflectors for ascending/descending geometries within a single instrument, enables the assumption-less decomposition of the observed cross-track LOS displacements into the vertical and the horizontal displacement components.</p><p>In this study, we perform InSAR analysis on the one-year of Sentinel-1 time series of five areas in Slovakia, affected by landslides. 24 double back-flipped trihedral CR were carefully deployed at these sites to form a reference network, guaranteeing reliable displacement information over the critical landslide zones. To confirm the measurement quality, we show that the temporal average Signal-to-Clutter Ratio (SCR) of the CR is better than 20 dB. The observed CR motions in vertical and east-west directions vary from several millimetres up to 3 centimetres, with average standard deviation better than 0.5 mm.<br>Repeated GNSS measurements of the CR confirm the displacement observed by the InSAR, improve the positioning precision of the nearby PS, and attain the transformation into the national TRF.</p>

scholarly journals MULTI-TEMPORAL SAR INTERFEROMETRY FOR LANDSLIDE MONITORING

2016 ◽  
Vol XLI-B8 ◽  
pp. 55-58
Author(s):  
R. Dwivedi ◽  
A. B. Narayan ◽  
A. Tiwari ◽  
O. Dikshit ◽  
A. K. Singh
Keyword(s):  
Surface Deformation ◽  
Deformation Monitoring ◽  
Sar Interferometry ◽  
Line Of Sight ◽  
Landslide Monitoring ◽  
Deformation Pattern ◽  
Mean Velocity ◽  
Study Region ◽  
Persistent Scatterer ◽  
Multi Temporal

In the past few years, SAR Interferometry specially InSAR and D-InSAR were extensively used for deformation monitoring related applications. Due to temporal and spatial decorrelation in dense vegetated areas, effectiveness of InSAR and D-InSAR observations were always under scrutiny. Multi-temporal InSAR methods are developed in recent times to retrieve the deformation signal from pixels with different scattering characteristics. Presently, two classes of multi-temporal InSAR algorithms are available- Persistent Scatterer (PS) and Small Baseline (SB) methods. This paper discusses the Stanford Method for Persistent Scatterer (StaMPS) based PS-InSAR and the Small Baselines Subset (SBAS) techniques to estimate the surface deformation in Tehri dam reservoir region in Uttarkhand, India. Both PS-InSAR and SBAS approaches used sixteen ENVISAT ASAR C-Band images for generating single master and multiple master interferograms stack respectively and their StaMPS processing resulted in time series 1D-Line of Sight (LOS) mean velocity maps which are indicative of deformation in terms of movement towards and away from the satellites. From 1D LOS velocity maps, localization of landslide is evident along the reservoir rim area which was also investigated in the previous studies. Both PS-InSAR and SBAS effectively extract measurement pixels in the study region, and the general results provided by both approaches show a similar deformation pattern along the Tehri reservoir region. Further, we conclude that StaMPS based PS-InSAR method performs better in terms of extracting more number of measurement pixels and in the estimation of mean Line of Sight (LOS) velocity as compared to SBAS method. It is also proposed to take up a few major landslides area in Uttarakhand for slope stability assessment.

Landslide monitoring by using ground-based SAR interferometry: an example of application to the Tessina landslide in Italy

2003 ◽  
Vol 68 (1-2) ◽  
pp. 15-30 ◽  
Author(s):  
Dario Tarchi ◽  
Nicola Casagli ◽  
Riccardo Fanti ◽  
David D. Leva ◽  
Guido Luzi ◽  
...  
Keyword(s):  
Sar Interferometry ◽  
Landslide Monitoring

Landslide Monitoring by Integrating Multi-Sensor InSAR Time Series Datasets and Corner Reflectors in the Three Gorges Area

2020 ◽  
Author(s):  
Zhuge Xia ◽  
Mahdi Motagh ◽  
Tao Li
Keyword(s):  
Urban Areas ◽  
Regional Scale ◽  
Sar Interferometry ◽  
Landslide Monitoring ◽  
Three Gorges ◽  
Rock Falls ◽  
Three Gorges Area ◽  
The Three Gorges ◽  
Three Gorges Region ◽  
Persistent Scatterer

<p>Landslide is one of the major geohazards in the Three Gorges area as a result of steep valley-side slopes and environmental conditions, e.g., high precipitation. To monitor and detect the landslides and rock falls at a regional scale as Three Gorges area, the differential Synthetic Aperture Radar Interferometry (D-InSAR) technology could be more effective and efficient than other conventional geological and geodetic measurements that can be performed only at a few sites with proper accessibility and conditions.</p><p>Over the past few decades, InSAR technology and advanced SAR Interferometry techniques such as Persistent Scatterer Interferometry (PSI) and Small Baseline Subsets (SBAS) have been developed to derive ground displacement over large areas with high-resolution measurement points and acceptable accuracy (cm to mm level). Both PSI and SBAS methods are based on a network of coherent pixels, including natural persistent scatterer (NPS) and artificial corner reflector (CR). NPSs can be easily found in urban areas or rocky regions. However, for landslide monitoring, the NPSs are usually difficult to be identified due to the steepness, vegetated and vulnerable moisture content among the high-risk locations. In this work, multiple SAR datasets including C-band Sentinel-1, L-band ALOS-2 and X-band TerraSAR-X (TSX) are exploited for landslide monitoring along the Yangtze River in the Three Gorges area in China.  Both PSI and SBAS methods are utilized. Besides, stable artificial CRs are deployed on selected sites to evaluate their performance in deriving landslide kinematics. Results are presented and discussed for a better assessment of landslide hazards in the Three Gorges region.</p>

scholarly journals An Accurate Geocoding Method for GB-SAR Images Based on Solution Space Search and Its Application in Landslide Monitoring

2021 ◽  
Vol 13 (5) ◽  
pp. 832
Author(s):  
Jialun Cai ◽  
Hongguo Jia ◽  
Guoxiang Liu ◽  
Bo Zhang ◽  
Qiao Liu ◽  
...  
Keyword(s):  
Coordinate System ◽  
Local Coordinate System ◽  
Solution Space ◽  
High Accuracy ◽  
Deformation Monitoring ◽  
Sar Interferometry ◽  
Transformation Model ◽  
Landslide Monitoring ◽  
Surface Model ◽  
Sar Images

Although ground-based synthetic aperture radar (GB-SAR) interferometry has a very high precision with respect to deformation monitoring, it is difficult to match the fan-shaped grid coordinates with the local topography in the geographical space because of the slant range projection imaging mode of the radar. To accurately identify the deformation target and its position, high-accuracy geocoding of the GB-SAR images must be performed to transform them from the two-dimensional plane coordinate system to the three-dimensional (3D) local coordinate system. To overcome difficulties of traditional methods with respect to the selection of control points in GB-SAR images in a complex scattering environment, a high-resolution digital surface model obtained by unmanned aerial vehicle (UAV) aerial photogrammetry was used to establish a high-accuracy GB-SAR coordinate transformation model. An accurate GB-SAR image geocoding method based on solution space search was proposed. Based on this method, three modules are used for geocoding: framework for the unification of coordinate elements, transformation model, and solution space search of the minimum Euclidean distance. By applying this method to the Laoguanjingtai landslide monitoring experiment on Hailuogou Glacier, a subpixel geocoding accuracy was realized. The effectiveness and accuracy of the proposed method were verified by contrastive analysis and error assessment. The method proposed in this study can be applied for accurate 3D interpretation and analysis of the spatiotemporal characteristic in GB-SAR deformation monitoring and should be popularized.

scholarly journals MULTI-TEMPORAL SAR INTERFEROMETRY FOR LANDSLIDE MONITORING

2016 ◽  
Vol XLI-B8 ◽  
pp. 55-58 ◽  
Author(s):  
R. Dwivedi ◽  
A. B. Narayan ◽  
A. Tiwari ◽  
O. Dikshit ◽  
A. K. Singh
Keyword(s):  
Surface Deformation ◽  
Deformation Monitoring ◽  
Sar Interferometry ◽  
Line Of Sight ◽  
Landslide Monitoring ◽  
Deformation Pattern ◽  
Mean Velocity ◽  
Study Region ◽  
Persistent Scatterer ◽  
Multi Temporal

In the past few years, SAR Interferometry specially InSAR and D-InSAR were extensively used for deformation monitoring related applications. Due to temporal and spatial decorrelation in dense vegetated areas, effectiveness of InSAR and D-InSAR observations were always under scrutiny. Multi-temporal InSAR methods are developed in recent times to retrieve the deformation signal from pixels with different scattering characteristics. Presently, two classes of multi-temporal InSAR algorithms are available- Persistent Scatterer (PS) and Small Baseline (SB) methods. This paper discusses the Stanford Method for Persistent Scatterer (StaMPS) based PS-InSAR and the Small Baselines Subset (SBAS) techniques to estimate the surface deformation in Tehri dam reservoir region in Uttarkhand, India. Both PS-InSAR and SBAS approaches used sixteen ENVISAT ASAR C-Band images for generating single master and multiple master interferograms stack respectively and their StaMPS processing resulted in time series 1D-Line of Sight (LOS) mean velocity maps which are indicative of deformation in terms of movement towards and away from the satellites. From 1D LOS velocity maps, localization of landslide is evident along the reservoir rim area which was also investigated in the previous studies. Both PS-InSAR and SBAS effectively extract measurement pixels in the study region, and the general results provided by both approaches show a similar deformation pattern along the Tehri reservoir region. Further, we conclude that StaMPS based PS-InSAR method performs better in terms of extracting more number of measurement pixels and in the estimation of mean Line of Sight (LOS) velocity as compared to SBAS method. It is also proposed to take up a few major landslides area in Uttarakhand for slope stability assessment.

Time-dependent investigation of a slow-moving landslide in Los Angeles, CA, through SAR observations and numerical simulations

2020 ◽  
Author(s):  
Nicușor Necula ◽  
Kami Mohammadi ◽  
Mostafa Khoshmanesh ◽  
Domniki Asimaki
Keyword(s):  
Los Angeles ◽  
Ground Deformation ◽  
Numerical Models ◽  
Ground Surface ◽  
Weather Conditions ◽  
Sar Interferometry ◽  
Time Dependent ◽  
Landslide Monitoring ◽  
Slow Moving

<p>As urbanized areas increasingly expand into mountainous terrains and climate change accentuates extreme weather conditions (rainfall or drought), slow-moving landslides increasingly threaten the resilience of infrastructure systems. Referred to as creeping landslides, these features may appear benign but can abruptly turn into catastrophic failures and debris flows during heavy rainfall or an earthquake. Because of the spatial extent and time evolution of ground deformation risk, conventional observation techniques such as site surveying, that rely on human resource availability and involve safety considerations, cannot be used to identify precursors of impending failures. Instead, remote sensing techniques for landslide monitoring such as differential SAR Interferometry (DInSAR) allow the spatiotemporal retrieval of surface changes with millimeter accuracy. We here test the reliability of repeat-pass interferometry techniques coupled with numerical models of creep to quantify the time-dependent deformations of a landslide in the Bel Air district of Los Angeles, USA. We validate our measurements and predictions by comparison with in-situ deformation profiles, and provide detailed representations of ground surface and subsurface displacements, along with the relationship between environmental factors and material properties. The wealth of in-situ measurements and site characterization data at the site improves our understanding of deformation precursors that can be used to minimize the risk posed to communities by slow-moving landslides.</p>

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