Advanced low- and full-resolution DInSAR map generation for slow-moving landslide analysis at different scales

Cascini, Leonardo; Fornaro, G.; Peduto, Dario

doi:10.1016/j.enggeo.2010.01.003

Cited by 281 publications

(188 citation statements)

References 24 publications

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“…To overcome the differences between the ground geometry and the LOS direction, we projected the LOS deformations into the direction of the down slope movements [40]. We converted the LOS velocity deformation rates into downslope velocity deformation rates (Vslope) [41,42]. To transform the LOS direction into the down slope direction, we needed information about the unit LOS vectors and the slopes.…”

Section: Stamps Results Visualization and Deformation Along The Localmentioning

confidence: 99%

ALOS/PALSAR InSAR Time-Series Analysis for Detecting Very Slow-Moving Landslides in Southern Kyrgyzstan

et al. 2015

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This study focuses on evaluating the potential of ALOS/PALSAR time-series data to analyze the activation of deep-seated landslides in the foothill zone of the high mountain Alai range in the southern Tien Shan (Kyrgyzstan). Most previous field-based landslide investigations have revealed that many landslides have indicators for ongoing slow movements in the form of migrating and newly developing cracks. L-band ALOS/PALSAR data for the period between 2007 and 2010 are available for the 484 km 2 area in this study. We analyzed these data using the Small Baseline Subset (SBAS) time-series technique to assess the surface deformation related to the activation of landslides. We observed up to ±17 mm/year of LOS velocity deformation rates, which were projected along the local steepest slope and resulted in velocity rates of up to −63 mm/year. The obtained rates indicate very slow movement of the deep-seated landslides during the observation time. We also compared these movements with precipitation and earthquake records. The results suggest that the deformation peaks correlate with rainfall in the 3 preceding months and with an earthquake event. Overall, the results of this study indicated the great potential of L-band InSAR time series analysis for OPEN ACCESS Remote Sens. 2015, 7 8974 efficient spatiotemporal identification and monitoring of slope activations in this region of high landslide activity in Southern Kyrgyzstan.

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Section: Stamps Results Visualization and Deformation Along The Localmentioning

confidence: 99%

ALOS/PALSAR InSAR Time-Series Analysis for Detecting Very Slow-Moving Landslides in Southern Kyrgyzstan

et al. 2015

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“…8) has a precision of the order of 1 mm/year (see Crosetto et al (2016)). The transformation from the LOS values into displacements parallel to the slope involves the multiplication by a factor, which amplifies the errors; see Cascini et al (2010), Bovenga et al (2013) and Wasowski and Bovenga (2014). Finally, the displacement time series are usually noisier than the velocity maps: the single LOS displacement values can have error values of several millimetres.…”

Section: Discussionmentioning

confidence: 99%

“…9). The along-slope projection is discussed in Colesanti and Wasowski (2006) and Cascini et al (2010). Figure 9 shows the map of cumulative displacements over the entire observed period (from December 2007 to October 2012).…”

Section: Psi Data Processing and Analysismentioning

confidence: 99%

“…The time series of Sector A show displacements up to 80 mm. However, in this sector, the ratio between the displacements projected parallel to the local slope and the original LOS values is 19: this amplification factor makes the values of the time series unreliable; see Colesanti and Wasowski (2006), Cascini et al (2010) and Plank et al (2010). For this reason, the time series for sector A are not shown in Fig.…”

Section: Magnitude Of the Terrain Instabilitymentioning

confidence: 99%

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Monitoring soil creep landsliding in an urban area using persistent scatterer interferometry (El Papiol, Catalonia, Spain)

et al. 2018

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“…Persistent Scatterer Interferometry throughout the use of medium resolution Synthetic Aperture Radar (SAR) data in C-band (e.g., from ERS/ENVISAT satellites) has been demonstrated to be a valuable tool for back-monitoring slow-moving landslides, with good accuracy (up to 1 mm/year) and maximum detectable movement of about 15-20 cm/year (HANSSEN 2005;FERRETTI et al 2005;ADAM et al 2008;CASCINI et al 2010;CIGNA et al 2013).…”

Section: Introductionmentioning

confidence: 99%

Multi-Temporal Evaluation of Landslide Movements and Impacts on Buildings in San Fratello (Italy) By Means of C-Band and X-Band PSI Data

Bianchini

Ciampalini

Raspini

et al. 2014

Pure Appl. Geophys.

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Abstract-This work provides a multi-temporal and spatial investigation of landslide effects in the San Fratello area (Messina province within the Sicily region, Italy), by means of C-band and X-band Persistent Scatterer Interferometry (PSI) data, integrated with in situ field checks and a crack pattern survey. The Sicily region is extensively affected by hydrogeological hazards since several landslides regularly involved local areas across time. In particular, intense and catastrophic landslide phenomena have recently occurred in the San Fratello area; the last event took place in February 2010, causing large economic damage. Thus, the need for an accurate ground motions and impacts mapping and monitoring turns out to be significantly effective, in order to better identify active unstable areas and to help proper risk-mitigation measures planning. The combined use of historical and recent C-band satellites and current X-band Synthetic Aperture Radar sensors of a new generation permits spatially and temporally detection of landslide-induced motions on a local scale and to properly provide a complete multi-temporal evaluation of their effects on the area of interest. PSI ground motion rates are crosscompared with local failures and damage of involved buildings, recently recognized by in situ observations. As a result, the analysis of landslide-induced movements over almost 20 years and the validation of radar data with manufactured crack patterns, permits one to finally achieve a complete and reliable assessment in the San Fratello test site.

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Advanced low- and full-resolution DInSAR map generation for slow-moving landslide analysis at different scales

Cited by 281 publications

References 24 publications

ALOS/PALSAR InSAR Time-Series Analysis for Detecting Very Slow-Moving Landslides in Southern Kyrgyzstan

ALOS/PALSAR InSAR Time-Series Analysis for Detecting Very Slow-Moving Landslides in Southern Kyrgyzstan

Monitoring soil creep landsliding in an urban area using persistent scatterer interferometry (El Papiol, Catalonia, Spain)

Multi-Temporal Evaluation of Landslide Movements and Impacts on Buildings in San Fratello (Italy) By Means of C-Band and X-Band PSI Data

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