Analysis with C- and X-band satellite SAR data of the Portalet landslide area

Herrera, Gerardo; Notti, Davide; García-Davalillo, Juan Carlos; Mora, Oscar; Cooksley, G.; Sánchez, Mónica López; Arnaud, Alain; Crosetto, Michele

doi:10.1007/s10346-010-0239-3

Cited by 103 publications

(60 citation statements)

References 21 publications

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“…A higher temporal resolution will also permit to improve the identification of the nonlinear components of ground deformation, i.e., accelerating and decelerating events (Herrera et al 2011).…”

Section: Discussionmentioning

confidence: 99%

A simple method to help determine landslide susceptibility from spaceborne InSAR data: the Montescaglioso case study

2016

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On December 3, 2013, a large complex landslide was triggered SW of the town of Montescaglioso (Southern Italy), causing the destruction of roads, commercial buildings and private dwellings, as well as several direct and indirect economic losses. A set of interferometric ground measurements acquired by the Cosmo-SkyMed satellite constellation and processed by means of the SqueeSAR algorithm was used to study the pre-event slope displacements in the entire Montescaglioso municipal area. Data span from January 30, 2012, to December 2, 2013, and show average line-of-sight velocities of 1-10 mm/year in the slope sector ultimately affected by the collapse. In retrospect, a time series analysis of the radar targets was performed in order to identify and characterize all the slope instabilities in proximity of the town. This was based on the setup of characteristic thresholds of displacement. The procedure permitted to locate several areas which recurrently exceeded these previously established thresholds, in consistency with the amount of precipitation. In particular, the major source of potential hazard in the area was indeed found where the December 3, 2013, landslide eventually occurred. The results of this quick data processing technique were validated through comparison with two independently developed landslide maps. This simple method, which is not supposed to diminish the importance of geomorphologic field surveys, could improve both the accuracy and the update rate of landslide susceptibility maps.Not relying on arbitrary or empirically derived approaches, it has the advantage of computing statistically based thresholds specific for each time series. By indicating the slope sectors in higher need of deeper in situ investigation, more support could be provided to administrative bodies for the processes of risk assessment and management.

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Section: Discussionmentioning

confidence: 99%

A simple method to help determine landslide susceptibility from spaceborne InSAR data: the Montescaglioso case study

2016

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“…Among them, two InSAR (interferometric synthetic aperture radar) techniques, PSInSAR (Ferretti et al 2001) and its evolution SqueeSAR (Ferretti et al 2011), have been widely exploited for the detection, mapping, definition of the state of activity, and monitoring of slow-moving landslide (Meisina et al 2008;Herrera et al 2011Herrera et al , 2013Bianchini et al 2013;Lu et al 2014;Notti et al 2014;Bianchini et al 2015a, b;Oliveira et al 2015;Raspini et al 2015;Bardi et al 2016;Calvello et al 2016;Béjar-Pizarro et al 2017).…”

Section: Introductionmentioning

confidence: 99%

Satellite radar data for back-analyzing a landslide event: the Ponzano (Central Italy) case study

et al. 2018

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In this manuscript, an integrated strategy that exploits both phase and amplitude features of satellite SAR (synthetic aperture radar) images and ground data is proposed for deriving the deformation field induced by a complex landslide that affected part of the village of Ponzano (Abruzzi Region, Central Italy). The February 12, 2017, landslide was triggered by the combined effects of intense rainfalls and snowmelt that saturated the slope. The SqueeSAR algorithm was applied to two C-band SAR datasets, composed by Radarsat-2 and Sentinel-1 images, spanning a nineyear time interval before the landslide occurrence. Moreover, the amplitude information carried by two TerraSAR-X images, acquired immediately before and after the event, was exploited to derive the total displacement generated by the landslide movement by means of the RMT (rapid motion tracking) algorithm. The obtained results allow describing the landslide behavior before and after its failure. In particular, the back-monitoring analysis shows that the landslide was already slowly moving, with deformation rates increasing from the Radarsat-2 to the Sentinel-1 monitored periods, 10 years before its complete mobilization. The landslide failure of February 2017 produced maximum displacements of about 10 m in some sectors of the affected area. The registered deformation rates and the localization of the maximum displacements areas were confirmed by field data, collected during a field campaign and a helicopter recognizance of the damaged areas, both performed after the event.

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“…The photo-and radar-interpretation procedures have been recently exploited and validated by several scientific applications [8,[11][12][13][14][15][16]. Following these procedures, the radar data acquired from different datasets are combined with geological and geomorphological evidences resulting from the auxiliary data such as aerial orthophotos referred to different dates and existing landslide databases.…”

Section: Methodsmentioning

confidence: 99%

Monitoring Landslide-Induced Displacements with TerraSAR-X Persistent Scatterer Interferometry (PSI): Gimigliano Case Study in Calabria Region (Italy)

Bianchini¹,

Cigna²,

Chiara³

et al. 2013

IJG

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This work provides a detailed detection of landslide-induced displacements at local scale on Gimigliano site (Italy), by means of PSI (Persistent Scatterers Interferometry) analysis, exploiting TerraSAR-X data acquired in November 2010-October 2011. In February-March 2010, several landslides affected Gimigliano, following high-intensity precipitation, and causing damages to structures and roads. In order to assess any spatial and temporal patterns of deformation, the present X-band PS data were compared with historical motion rates derived from ERS1/2 and ENVISAT satellites, and with geological and geomorphological evidences resulting from auxiliary data such as landslide databases and orthophotos referred to different dates, finally validated with recent field checks. The PSI analysis of the historical ground motion rates highlighted that the modern built-up area located downhill was already affected by surface ground deformation since 1993. A significant enlargement of the instability phenomena is detected across time. The recent PS data analysis and the in situ observations permitted us to accurately update the ground movements in the investigated site: their evidence allowed assessing a reactivation of the large deep-seated landslide zone on which the new urbanized area had built-up, with an average deformation rate of about 8 -9 mm/yr. The higher instability phenomenon is affecting the eastern part of Gimigliano old village, with a mean displacement velocity reaching up values of −30 mm/yr, in the radar temporal acquisition of only 10 months. These outcomes can be taken into account for further hazard-reduction analysis and to support risk mitigation design within the investigated area.

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Analysis with C- and X-band satellite SAR data of the Portalet landslide area

Cited by 103 publications

References 21 publications

A simple method to help determine landslide susceptibility from spaceborne InSAR data: the Montescaglioso case study

A simple method to help determine landslide susceptibility from spaceborne InSAR data: the Montescaglioso case study

Satellite radar data for back-analyzing a landslide event: the Ponzano (Central Italy) case study

Monitoring Landslide-Induced Displacements with TerraSAR-X Persistent Scatterer Interferometry (PSI): Gimigliano Case Study in Calabria Region (Italy)

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