The contribution of PSInSAR interferometry to landslide hazard in weak rock-dominated areas

Oliveira, Sérgio C.; Zêzere, José Luı́s; Catalão, João; Nico, Giovanni

doi:10.1007/s10346-014-0522-9

Cited by 78 publications

(47 citation statements)

References 31 publications

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“…Two commonly used methods were chosen: the bivariate statistical information value method (IV; Yin and Yan, 1988) and the infinite slope method (IS; Sharma, 2002) based on the calculation of the factor of safety (FS). Both methods are in line with the experts panel recommendations to assess landslide susceptibility (Cascini, 2008;Fell et al, 2008a, b;Corominas et al, 2014) and have been applied successfully in similar geological and geomorphological context in the region north of Lisbon (Zêzere, 2002;Pimenta, 2011;Guillard and Zêzere, 2012;Oliveira et al, 2015). In order to model the shallow slide susceptibility, the dependent variables (shallow slide training and validation groups), the independent dataset of variables used as predisposing factors, and the maps representing geotechnical and hydraulic parameters were rasterized using a pixel of 5 m × 5 m.…”

Section: Methods and Datasupporting

confidence: 55%

Combination of statistical and physically based methods to assess shallow slide susceptibility at the basin scale

Oliveira

Zêzere²,

Lajas

et al. 2017

Nat. Hazards Earth Syst. Sci.

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Abstract. Approaches used to assess shallow slide susceptibility at the basin scale are conceptually different depending on the use of statistical or physically based methods. The former are based on the assumption that the same causes are more likely to produce the same effects, whereas the latter are based on the comparison between forces which tend to promote movement along the slope and the counteracting forces that are resistant to motion. Within this general framework, this work tests two hypotheses: (i) although conceptually and methodologically distinct, the statistical and deterministic methods generate similar shallow slide susceptibility results regarding the model's predictive capacity and spatial agreement; and (ii) the combination of shallow slide susceptibility maps obtained with statistical and physically based methods, for the same study area, generate a more reliable susceptibility model for shallow slide occurrence. These hypotheses were tested at a small test site (13.9 km 2 ) located north of Lisbon (Portugal), using a statistical method (the information value method, IV) and a physically based method (the infinite slope method, IS). The landslide susceptibility maps produced with the statistical and deterministic methods were combined into a new landslide susceptibility map. The latter was based on a set of integration rules defined by the cross tabulation of the susceptibility classes of both maps and analysis of the corresponding contingency tables. The results demonstrate a higher predictive capacity of the new shallow slide susceptibility map, which combines the independent results obtained with statistical and physically based models. Moreover, the combination of the two models allowed the identification of areas where the results of the information value and the infinite slope methods are contradictory. Thus, these areas were classified as uncertain and deserve additional investigation at a more detailed scale.

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Section: Methods and Datasupporting

confidence: 55%

Combination of statistical and physically based methods to assess shallow slide susceptibility at the basin scale

Oliveira

Zêzere²,

Lajas

et al. 2017

Nat. Hazards Earth Syst. Sci.

View full text Add to dashboard Cite

show abstract

“…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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“…Lu et al (2014) introduced an approach for updating landslide hazard and risk maps based on Persistent Scatterer Interferometry (PSI). Piacentini et al (2015) exploited the results of PSI analysis for the implementation of a statistical model for landslide susceptibility; on the same subject, Oliveira et al (2015) proposed a methodology to determine landslide susceptibility at regional scale in weak rock-dominated areas from Persistent Scatterer deformation maps. More recently, Ciampalini et al (2016) used PSInSAR data to refine landslide susceptibility maps and to reduce false negatives.…”

Section: Introductionmentioning

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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The contribution of PSInSAR interferometry to landslide hazard in weak rock-dominated areas

Cited by 78 publications

References 31 publications

Combination of statistical and physically based methods to assess shallow slide susceptibility at the basin scale

Combination of statistical and physically based methods to assess shallow slide susceptibility at the basin scale

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

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

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