Multi-sensor advanced DInSAR monitoring of very slow landslides: The Tena Valley case study (Central Spanish Pyrenees)

Herrera, Gerardo; Gutiérrez, Francisco; García-Davalillo, J.C.; Guerrero, Jesús; Notti, Davide; Arnedo, Jorge Pedro Galve; Merodo, J. A. Fernández; Cooksley, G.

doi:10.1016/j.rse.2012.09.020

Cited by 256 publications

(146 citation statements)

References 31 publications

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“…Our L-band results and X-band results are complementary; thus, the L-band data are more suitable for long-term monitoring and the X-band data for short-term monitoring of unstable slopes in the mountainous regions of Southern Kyrgyzstan. Similar observations of the performance of L-band ALOS data compared with X-band and C-band data have been made in the Tena Valley of the Central Spanish Pyrenees [3]. However, the X-band data preserve the spatial details and short-term slope deformations well.…”

Section: Sbas Results Assessmentsupporting

confidence: 71%

“…On the contrary, the Satellite Synthetic Aperture Radar (SAR) Interferometry (InSAR) technique has evolved as a powerful tool to assess the slope deformation related to the activation of deep-seated landslides [3][4][5][6]. With the increasing availability of suitable radar data, advanced time-series analysis techniques have been developed, which allow for the quantitative derivation of spatially variable deformation rates with increasing improvements in the temporal resolution.…”

Section: Introductionmentioning

confidence: 99%

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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: Sbas Results Assessmentsupporting

confidence: 71%

Section: Introductionmentioning

confidence: 99%

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

et al. 2015

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“…Active deformation areas The ADA generation procedure is an adapted version of the methodology proposed by Bianchini et al (2013), Herrera et al (2013) and Notti et al (2014). The input PSI dataset, composed of hundreds of thousand/millions of points, are analysed by means of statistical tools to define those areas affected by an active deformation of a certain magnitude, above a specific threshold, that constitute a potential geohazard.…”

Section: Intermediate Outputs Of the Methodologymentioning

confidence: 99%

“…Abidin et al 2013;Tomas et al 2014;Solari et al 2016;Bejar-Pizarro et al 2017) or landslides (i.e. Notti et al 2010;Herrera et al 2013;Kim et al 2015;Oliveira et al 2015). Moreover, the temporal and spatial resolution of the PSI products has been also exploited to define the state of activity of geohazards and update pre-existent geohazard inventories in order to provide useful information for the risk management and urban planning of a region or a municipality (e.g.…”

mentioning

confidence: 99%

Fast detection of ground motions on vulnerable elements using Sentinel-1 InSAR data

Solari

Barra

Herrera

et al. 2017

Geomatics, Natural Hazards and Risk

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The detection of active movements that could threat the infrastructures and the population is one of the main priorities of the risk management chain. Interferometric Synthetic Aperture Radar (InSAR) techniques represent one of the most useful answers to this task; however, it is difficult to manage the huge amount of information derived from the interferometric analysis. In this work, we present a procedure for deriving impact assessment maps, over a regional test site, using as starting point Sentinel-1 SAR (Synthetic Aperture Radar) images and a catalogue of elements at risk that acts as a second input of the methodology. We applied the proposed approach, named as Vulnerable Elements Activity Maps (VEAM), to the islands of Gran Canaria, La Gomera and Tenerife (Spain), where we analysed SAR images covering the time interval November 2014-September 2016. The methodology, meant to be a powerful tool for reducing the time needed for a complete analysis of a full stack of InSAR data, is ideally suited for Civil Protection Authorities. The application of the methodology allowed to detect 108 areas affected by active deformation that are threatening one or more elements at risk in 25 municipalities of the three islands.

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“…Moreover, this conversion permits comparing landslide velocities with different slope orientations, resolving the satellite acquisition orbit differences and allowing a more feasible interpretation. Following the procedure initially proposed by COLESANTI and WASOWSKI (2006), and then successfully applied in several scientific works (CIGNA et al 2013;GRIEF and VLCKO 2012;BIANCHINI et al 2013;HERRERA et al 2013), a correction factor (C) was applied to each LOS measurement, in order to determine the ''real'' V SLOPE velocity (intended as not the one measured in the LOS direction, but the one occurring in the landslide direction), taking into account satellite-dependant parameters, i.e., incidence angle and track angle, as well as topographic parameters, i.e., terrain slope and orientation, The track angle and the incidence angle are provided within the processed SAR images for each satellite (Table 1). The slope and aspect of the area of interest are derived from a DEM with 20 m cell resolution.…”

Section: Insar Processing and Datamentioning

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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Multi-sensor advanced DInSAR monitoring of very slow landslides: The Tena Valley case study (Central Spanish Pyrenees)

Cited by 256 publications

References 31 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

Fast detection of ground motions on vulnerable elements using Sentinel-1 InSAR data

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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