Geological Interpretation of PSInSAR Data at Regional Scale

Meisina, Claudia; Zucca, Francesco; Notti, Davide; Colombo, Alessio; Cucchi, A.; Savio, G.; Giannico, C.; Bianchi, Marco

doi:10.3390/s8117469

Cited by 143 publications

(107 citation statements)

References 17 publications

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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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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 the study area of this work, PS populations of ERS and ENVISAT sensors are characterized by an almost Gaussian (normal) distribution, with coincident mean and median values and with standard deviation values ranging 1.5-2. As a result, we decided to establish the stability threshold of velocity at AE2 mm/year, since this is the widely and mostly used value in literature for this type of analysis with Cband radar data (Wasowski et al 2002;Meisina et al 2008;Righini et al 2012) and since it fits our data and case study well.…”

Section: Discussionmentioning

confidence: 99%

Landslide inventory updating by means of Persistent Scatterer Interferometry (PSI): the Setta basin (Italy) case study

Sara

Bianchini

Moretti

2014

Geomatics, Natural Hazards and Risk

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This paper illustrates the contribution of Persistent Scatterer SAR Interferometry (PSInSAR) technique to landslide detection, using interferometric data acquired in C-band by European remote-sensing satellite (ERS) 1/2 and environmental satellite (ENVISAT) satellites. The main purpose is to update a pre-existing landslide inventory map, by changing or confirming the landslide geometry and state of activity and eventually, identifying new phenomena.This work presents an application of satellite remote sensing to analyse ground displacement movements in the Setta basin, located on the northern Appennine (Bologna province, Italy) and extended up 268 km 2 .The proposed methodology, resting upon pre-existing works already consolidated in the scientific community, combines interferometric measures with aerial imagery and other auxiliary data, in order to detect landslide indicators, finally validated with field surveys. The use of an activity matrix allows the identification of the state of activity of landslide phenomena with respect to the velocity of the radar displacement rates. Field validations are carried out in the areas that are more relevant because of the highest ground velocities and the presence of structures extensively affected by ground movements.The final updated landslide database of the Setta basin, based on Persistent Scatterer Interferometry analysis and in situ checks, consists of 1550 landslides, 236 of which have persistent scatterer information.

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“…A comparison of precise levelling and persistent scatterer SAR interferometry has been done 58,59 and PSI results show good agreement with the levelling data. PSInSAR analyses detect ground deformation and help in focusing the attention of geologists 56 and geo-scientists to analyse the results in identifying risk zones.…”

Section: Assessment Of Sar Interferometric Measurementsmentioning

confidence: 99%

“…Many PSI approaches have been developed over the years; their description is beyond the scope of this article. Examples of PSInSAR application in the field of mine surface 14,15,25,26,28,30,34,35,38 and urban [54][55][56][57][58][59][60][61][62][63][64] subsidence have shown the large spectrum of this technique on ground deformation assessment. About 21 TerraSAR X-band ( -3.1 cm) images have been used by Liu et al 28 to extract subsidence hazard map (SHM) around Xishan coal mine in China, that suffered from subsidence related to underground mining activities.…”

Section: Analyses On Applications Of Dinsar In Surface Subsidencementioning

confidence: 99%

Application of DInSAR in Mine Surface Subsidence Monitoring and Prediction

Ishwar¹,

Kumar²

2017

Current Science

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Most studies of surface subsidence and its impacts have been done on underground coal mines. There are few studies on the occurrences of surface subsidence in underground metal mines, particularly in India, even though the fundamental subsidence engineering principles are the same for both coal and metal mines. The current ground-based measurement techniques monitor ground subsidence on a particular point and are time-consuming as well as costly. To study hardrock mine surface deformation due to underground mining, new and effective technologies must be adopted. The spaceborne subsidence monitoring has emerged as a better technique after the development of satellite radar interferometry. The technology is fast improving with enhanced synthetic aperture radar (SAR) sensors on different spaceborne platforms. Differential interferometric SAR techniques are widely used to measure the topographic profile and surface deformations. This article reviews the applications of spaceborne SAR interferometric techniques in the prediction and monitoring of surface subsidence due to underground mining.

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Geological Interpretation of PSInSAR Data at Regional Scale

Cited by 143 publications

References 17 publications

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

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

Landslide inventory updating by means of Persistent Scatterer Interferometry (PSI): the Setta basin (Italy) case study

Application of DInSAR in Mine Surface Subsidence Monitoring and Prediction

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