Landslide HotSpot Mapping by means of Persistent Scatterer Interferometry

Bianchini, Silvia; Cigna, Francesca; Righini, Gaia; Proietti, Carla; Casagli, Nicola

doi:10.1007/s12665-012-1559-5

Cited by 123 publications

(120 citation statements)

References 32 publications

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“…Radar-interpretation and photo-interpretation procedures (e.g., FARINA et al 2006;BIANCHINI et al 2012;CIGNA et al 2013;RIGHINI et al 2012) combined with a field survey allowed the mapping and characterization of landslides. In particular, on the one hand, the recognition of features related to topographic surface movements and the typology classification were mainly based on visual interpretation of orthophotos; on the other hand, the evaluation of the velocity and state of activity of phenomena took advantage from multi-interferometry-based information.…”

Section: Methodsmentioning

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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Section: Methodsmentioning

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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“…These approaches are increasingly used for the detection and monitoring of ground deformation induced by very slow surface processes (up to some tens of centimetres per year), and can successfully support conventional in situ investigations (e.g. Bianchini, Cigna, Righini, Proietti, & Casagli, 2012;Bürgmann, Hilley, & Ferretti, 2006;Cigna, Del Ventisette, Liguori, & Casagli, 2010Farina, Colombo, Fumagalli, Gautieri, & Moretti, 2004a;Hilley et al, 2004). ERS1/2 images acquired in 1992 -2000 along descending orbits, ENVISAT images acquired in 2002 -2010 along descending and ascending orbits, and RADARSAT1 S3 data acquired in 2003 -2007 in ascending mode were analysed for Agrigento (Table 1).…”

Section: Persistent Scatterer Interferometry Analysismentioning

confidence: 99%

Integrated geomorphological mapping in the north-western sector of Agrigento (Italy)

et al. 2012

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The geomorphological map is an essential tool to perform a proper urban planning in mountainous or hilly areas. In this paper a multidisciplinary approach to derive a 1:2000 geomorphological map is described. The proposed methodology consists of the integration between aerial photographs, acquired in 2003, and four datasets of Persistent Scatterer Interferometry (PSI) measures to update a pre-existing landslide inventory. The integrated data were used to achieve a validated geomorphological map by means of a geomorphological survey. The study area is located in southern Italy (Agrigento, Sicily). The city of Agrigento, included in the World Heritage List of UNESCO in 1997, is located on the Girgenti hill which is exposed on its northern side, to several landslide phenomena. The top of the hill is characterized by the presence of part of the cultural heritage of the city and is affected by rockfalls, rock topples and shallow-seated landslides, representing a serious risk for important historical buildings. The results demonstrate the validity of this method to achieve a suitable tool in landscape and cultural heritage management.

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“…In particular, such Persistent Scatterer Interferometry (PSI) techniques were used for updating landslide inventories (e.g. COLESANTI AND WASOWSKY, 2006;FARINA et al, 2006;MEISINA et al, 2008;CHEN et al, 2010;BIANCHINI et al, 2012;BOVEGNA et al, 2012), as well as for detecting and mapping land subsidence (e.g. SOUSA et al, 2010;TOMAS et al2010, RASPINI et al, 2014TEATINI et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

A User-Oriented Methodology for DInSAR Time Series Analysis and Interpretation: Landslides and Subsidence Case Studies

Notti

Calò

Cigna

et al. 2015

Pure Appl. Geophys.

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Recent advances in multi-temporal Differential Synthetic Aperture Radar (SAR) Interferometry (DInSAR) have greatly improved our capability to monitor geological processes. Ground motion studies using DInSAR require both the availability of good quality input data and rigorous approaches to exploit the retrieved Time Series (TS) at their full potential. In this work we present a methodology for DInSAR TS analysis, with particular focus on landslides and subsidence phenomena. The proposed methodology consists of three main steps: (1) pre-processing, i.e., assessment of a SAR Dataset Quality Index (SDQI), (2) post-processing, i.e., application of empirical/stochastic methods to improve the TS quality, and (3) trend analysis, i.e., comparative implementation of methodologies for automatic TS analysis.Tests were carried out on TS datasets retrieved from processing of SAR imagery acquired by different radar sensors (i.e., ERS-1/2 SAR, RADARSAT-1, ENVISAT ASAR, ALOS PALSAR, TerraSAR-X, COSMO-SkyMed) using advanced DInSAR techniques (i.e., SqueeSAR TM , PSInSAR TM , SPN and SBAS). The obtained values of SDQI are discussed against the technical parameters of each data stack (e.g., radar band, number of SAR scenes, temporal coverage, revisiting time), the retrieved coverage of the DInSAR results, and the constraints related to the characterization of the investigated geological processes. Empirical and stochastic approaches were used to demonstrate how the quality of the TS can be improved after the SAR processing, and examples are discussed to mitigate phase unwrapping errors, and remove regional trends, noise and anomalies. Performance assessment of recently developed methods of trend analysis (i.e., PS-Time, Deviation Index and velocity TS) was conducted on two selected study areas in Northern Italy affected by land subsidence and landslides. Results show that the automatic detection of motion trends enhances the interpretation of DInSAR data, since it provides an objective picture of the deformation behaviour recorded through TS and therefore contributes to the understanding of the on-going geological processes.

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Landslide HotSpot Mapping by means of Persistent Scatterer Interferometry

Cited by 123 publications

References 32 publications

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

Integrated geomorphological mapping in the north-western sector of Agrigento (Italy)

A User-Oriented Methodology for DInSAR Time Series Analysis and Interpretation: Landslides and Subsidence Case Studies

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