Characterizing and monitoring rockslides from SAR techniques

Singhroy, V.; Molch, Katrin

doi:10.1016/s0273-1177(03)00470-8

Cited by 106 publications

(46 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Despite modern technological advances, and the availability of new satellite products, the visual interpretation of airborne photographs is still the most common method to obtain landslide information though several other sources of information that may be used such as optical remote sensing images and LiDARderived topographic information (Ardizzone et al, 2007;van den Eeckhaut et al, 2007;Haneberg et al, 2009;Razak et al, 2013;Martha et al, 2010;van den Eeckhaut et al, 2012). Images acquired by synthetic aperture radar (SAR) satellite sensors are also considered as a powerful source of information, mainly for the recognition of slow-moving landslides (Singhroy and Molch, 2004;Zhao et al, 2012).…”

Section: Published By Copernicus Publications On Behalf Of the Europementioning

confidence: 99%

Analysis of a landslide multi-date inventory in a complex mountain landscape: the Ubaye valley case study

Schlögel

Malet

Reichenbach

et al. 2015

Nat. Hazards Earth Syst. Sci.

View full text Add to dashboard Cite

Abstract. In the paper we analyse a multi-date landslide inventory prepared for a mountainous area affected by several landslide types with different degrees of activity, we attempt to quantify the uncertainties associated to the mapping, we measure the evolution of morphological indicators and estimate landslide activity and temporal occurrence. The inventory, covering the period 1956-2010, is prepared for the middle section of the Ubaye valley (southern French Alps) based on the analysis of multi-source documents (geomorphological maps, historical reports of landslide events, field surveys, orthophotographs and SAR (synthetic aperture radar) satellite images). The uncertainties derived from the expert interpretation of different sources of information, the landslide morphological features and the affected land covers are taken into account in relation to the source documents.Morphological indicators are calculated to describe quantitatively the evolution of the landslides (length, area, relative elevation, runout distance). Frequency-area density functions are computed to estimate the changes in the landslide distributions and a Poisson model is used to estimate the probability of reactivation of the observed landslides and the occurrence of new failures. The proposed multi-date inventory and the associated statistics provide additional information to the event catalogue managed by the local policy makers.

show abstract

Section: Published By Copernicus Publications On Behalf Of the Europementioning

confidence: 99%

Analysis of a landslide multi-date inventory in a complex mountain landscape: the Ubaye valley case study

Schlögel

Malet

Reichenbach

et al. 2015

Nat. Hazards Earth Syst. Sci.

View full text Add to dashboard Cite

show abstract

“…An extensive bibliography contains works on the use of PSI for landslide monitoring [40][41][42][43][44][45]. In many cases, the PSI data have been integrated with in situ monitoring instrumentation [2,[46][47][48][49][50][51].…”

Section: Introductionmentioning

confidence: 99%

Persistent Scatterer Interferometry (PSI) Technique for Landslide Characterization and Monitoring

Tofani

Raspini

Catani

2014

Landslide Science for a Safer Geoenvironment

View full text Add to dashboard Cite

Abstract:The measurement of landslide superficial displacement often represents the most effective method for defining its behavior, allowing one to observe the relationship with triggering factors and to assess the effectiveness of the mitigation measures. Persistent Scatterer Interferometry (PSI) represents a powerful tool to measure landslide displacement, as it offers a synoptic view that can be repeated at different time intervals and at various scales. In many cases, PSI data are integrated with in situ monitoring instrumentation, since the joint use of satellite and ground-based data facilitates the geological interpretation of a landslide and allows a better understanding of landslide geometry and kinematics. In this work, PSI interferometry and conventional ground-based monitoring techniques have been used to characterize and to monitor the Santo Stefano d'Aveto landslide located in the Northern Apennines, Italy. This landslide can be defined as an earth rotational slide. PSI analysis has contributed to a more in-depth investigation of the phenomenon. In particular, PSI measurements have allowed better redefining of the boundaries of the landslide and the state of activity, while the time series analysis has permitted better understanding of the deformation pattern and its relation with the causes of the landslide itself. The integration of ground-based monitoring data and PSI data have provided sound results for landslide characterization. The punctual information deriving from inclinometers can help in defining the actual location of the sliding surface and the involved volumes, while the measuring of pore water pressure conditions or water table level can suggest a correlation between the deformation patterns and the triggering factors.

show abstract

“…As a complementary tool for conventional surveying, remote sensing offers a synoptic view for landslide characterization and prediction [4,5]. Unlike optical remote sensing (that detects changes in spectral signatures), differential synthetic aperture radar interferometry (DInSAR), particularly the multi-temporal SAR interferometry (MT-InSAR), has proved to be effective for surface motion detection and time series analysis (e.g., for phenomena ranging from landslides to tectonics, earthquakes, glacier evolution, volcanism and anthropogenic processes) [6][7][8][9][10][11][12]. MT-InSAR measures the phase difference of two or multi-temporal SAR acquisitions and can be divided into two categories: persistent scatterer (PS) SAR interferometry (PS-InSAR) [13][14][15] and small baseline SAR interferometry (SB-InSAR) [16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Slope Superficial Displacement Monitoring by Small Baseline SAR Interferometry Using Data from L-band ALOS PALSAR and X-band TerraSAR: A Case Study of Hong Kong, China

Chen

Lin

2014

Remote Sensing

View full text Add to dashboard Cite

Abstract:Owing to the development of spaceborne synthetic aperture radar (SAR) platforms, and in particular the increase in the availability of multi-source (multi-band and multi-resolution) data, it is now feasible to design a surface displacement monitoring application using multi-temporal SAR interferometry (MT-InSAR). Landslides have high socio-economic impacts in many countries because of potential geo-hazards and heavy casualties. In this study, taking into account the merits of ALOS PALSAR (L-band, good coherence preservation) and TerraSAR (X-band, high resolution and short revisit times) data, we applied an improved small baseline InSAR (SB-InSAR) with 3-D phase unwrapping approach, to monitor slope superficial displacement in Hong Kong, China, a mountainous subtropical zone city influenced by over-urbanization and heavy monsoonal rains. Results revealed that the synergistic use of PALSAR and TerraSAR data produces different outcomes in relation to data reliability and spatial-temporal resolution, and hence could be of significant value for a comprehensive understanding and monitoring of unstable slopes.

show abstract

Characterizing and monitoring rockslides from SAR techniques

Cited by 106 publications

References 7 publications

Analysis of a landslide multi-date inventory in a complex mountain landscape: the Ubaye valley case study

Analysis of a landslide multi-date inventory in a complex mountain landscape: the Ubaye valley case study

Persistent Scatterer Interferometry (PSI) Technique for Landslide Characterization and Monitoring

Slope Superficial Displacement Monitoring by Small Baseline SAR Interferometry Using Data from L-band ALOS PALSAR and X-band TerraSAR: A Case Study of Hong Kong, China

Contact Info

Product

Resources

About