Using Data from Multiple SAR Sensors in Landslide Characterization: Case Studies from Different Geomorphological Contexts in Italy

Novellino, Alessandro; Agostini, Anna; Martire, Diego Di; Ramondini, Massimo; Floris, Mario; Calcaterra, Domenico

doi:10.1007/978-3-319-09057-3_62

Cited by 4 publications

(3 citation statements)

References 6 publications

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“…By adopting a γ threshold of 0.7, implementation of the Coherent Pixels Technique [9] led to an average target density of ~500 points/km 2 for the same area of interest [10]. With the ISBAS algorithm only those pixels showing coherence higher than 0.5 were employed for the unwrapping step, provided that the number of coherent interferograms for those pixels exceeded 50.…”

Section: Isbas Analysismentioning

confidence: 99%

Intermittent small baseline subset (ISBAS) InSAR analysis to monitor landslides in Costa Della Gaveta, Southern Italy

Novellino

Cigna

Sowter

et al. 2015

2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

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This work presents a Differential SAR Interferometry (DInSAR) analysis of slow-moving landslides in Costa della Gaveta (southern Italy) exploiting the improved spatial density of radar targets provided by the novel Intermittent SBAS (ISBAS) algorithm. Several landslides occurred in this area over the past decade, producing a ground displacement of several centimeters and causing unsafe road and rail traffic conditions. In the 2.4 km 2 study area, ISBAS analysis of TerraSAR-X data acquired in 2010-2011 has shown the presence of sixteen phenomena with a southeastern main direction of motion. The DInSAR results agree with both the magnitude and the deformation mechanisms that were mapped during field observations and reported in the geotechnical literature.

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Section: Isbas Analysismentioning

confidence: 99%

Intermittent small baseline subset (ISBAS) InSAR analysis to monitor landslides in Costa Della Gaveta, Southern Italy

Novellino

Cigna

Sowter

et al. 2015

2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

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“…Differently from optical images, SAR sensors have the advantage to be able to gather ground surface information regardless of weather and illumination conditions. Geoscientists have widely exploited Interferometric SAR (InSAR, Gabriel et al 1989) techniques to resolve the spatial distribution and temporal evolution of ground instabilities by considering phase values associated with SAR scenes (Novellino et al 2015;Confuorto et al 2017;Raspini et al 2017;Spinetti et al 2019). Due, to the inherent limitations of current space observation systems and data processing techniques (Colesanti and Wasowski 2006;Wasowski and Bovenga 2014), InSAR approaches are mostly applicable to extremely slow (<16mm/yr) and very-slow movements (≥1.6mm/yr and ≤16mm/yr) landslides (Cruden and Varnes 1996) which typically correspond to deep-seated gravitational slope deformations, creep, and, in some cases, slides and complex landslides (Saroli et al 2005;Di Martire et al 2016;Bozzano et al 2017).…”

Section: Introductionmentioning

confidence: 99%

SAR data and field surveys combination to update rainfall-induced shallow landslide inventory

Miele

Napoli

Novellino

et al. 2022

Remote Sensing Applications: Society and Environment

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“…Differently from optical images, SAR data gather ground surface information regardless of weather and illumination conditions. Geoscientists have widely exploited Interferometric SAR (InSAR (Gabriel et al 1989) techniques to resolve the spatial distribution and temporal evolution of ground instabilities by considering the phase values associated to SAR scenes (Novellino et al 2015;Confuorto et al 2017;Raspini et al 2017;Spinetti et al 2019). However, due to the inherent limitations of current space observation systems and data processing techniques (Colesanti and Wasowski 2006;Wasowski and Bovenga 2014), InSAR approaches are currently applicable only to extremely slow (<16mm/yr) and very-slow movements (≥1.6mm/yr and ≤16mm/yr) landslides (Cruden and Varnes 1996) which typically correspond to deep-seated gravitational slope deformations, creep, and, in some cases, slides and complex landslides (Saroli et al 2005;Di Martire et al 2016;Bozzano et al 2017).…”

Section: Introductionmentioning

confidence: 99%

SAR data and field surveys combination to update rainfall-induced shallow landslides inventory

Miele¹,

Napoli²,

Novellino³

et al. 2021

Preprint

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The Campania region has been recurrently hit by severe landslides in volcanoclastic deposits. The city of Naples, and in particular the Camaldoli and Agnano hills, also suffered several landslide crises in weathered volcanoclastic rocks as a consequence of intense rainfalls or wildfires. This work provides an updated landslide database for the suburbs of Naples. The obtained database consists of about 1322 landslides considering available information dated back to 1816, identified thanks to the historical newspaper's examination; 62 landslides were recorded between 2019 and 2020. Furthermore, the achieved database is the result of the standardization of available information from different sources, organized in a completely different way. The newly identified phenomena have been recognized thanks to a combination of optical satellite imagery with Google Earth, Sentinel-1 radar satellite imagery and field investigation. The implemented methodology is based on change detection analysis of satellite imagery by using polarimetric features. Subsequently, output derived from the segmentation procedure of satellite images have been compared with field trip observations. The main purpose of this procedure is to emphasize areas where land cover changes, potentially related to slope failures, occur in the Phegraean Fields, facilitating the following possible phases of mapping and/or field survey. Eventually, this type of information is expected to help decision-makers with land planning and risk assessment.

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Using Data from Multiple SAR Sensors in Landslide Characterization: Case Studies from Different Geomorphological Contexts in Italy

Cited by 4 publications

References 6 publications

Intermittent small baseline subset (ISBAS) InSAR analysis to monitor landslides in Costa Della Gaveta, Southern Italy

Intermittent small baseline subset (ISBAS) InSAR analysis to monitor landslides in Costa Della Gaveta, Southern Italy

SAR data and field surveys combination to update rainfall-induced shallow landslide inventory

SAR data and field surveys combination to update rainfall-induced shallow landslides inventory

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