Long-term time series of ground displacement are key information for the interpretation of several natural and anthropic hazards. In high mountain environments, the analysis of surface displacements and their relationship with meteo-climatic variables can be exploited to better understand the effects of climate changes on the frequency and the intensity of the landslides and their triggering phenomena (Huggel et al., 2012). In this scenario, the use of straightforward tools and approaches to analyse surface displacements at high spatial and temporal resolutions is a real need. Here we present the preliminary results of the HAMMER project, developed in the framework of NextData initiative (http://www.nextdataproject.it/). HAMMER aims at collecting ground deformation time series, and analysing eventual changes of the deformation trends associated to meteo-climatic variables. In particular, we exploited Differential SAR Interferometry (DInSAR) technique to analyse space-born measurements of surface displacements over areas characterized by slope instability and/or gravitational spreading. We used the Parallel-SBAS, namely PSBAS (Casu et al., 2014), service recently released within the ESA's Grid Processing On Demand (G-POD, http://gpod.eo.esa.int/) environment for the generation of Earth's surface deformation time series and interferometric production. This service performs the full SBAS-DInSAR (Berardino et al., 2002) chain starting from Level 0 data, and generates displacement time series. Data are retrieved through the Virtual Archive 4 (http://eo-virtual-archive4.esa.int/, in the framework of Supersite initiative). The P-SBAS service within G-POD is accessible through a user-friendly web-interface, which allows selecting rapidly the input SAR data, and set easily some useful input parameters for processing (e.g., selection of temporal range, baseline and coherence thresholds set, reference point selection). We produced mean deformation, velocity maps, as well as deformation time series, on a regional scale case (Aosta Valley Region, northern Italy), and at local landslide scale (Puy landslide, Piedmont, northen Italy). The possibility to gather the final results in less than 24h (by processing an average of about 30 SAR images for each frame considered), allowed to perform in relatively short time a large number of attempts. By "tuning" the processing, we have maximized for both datasets the final coverage of coherent points where displacement time series can be traced over time. This was performed by analysing the effect of SAR images acquired in the winter season, as well as of the impact of perpendicular and temporal baseline constraints. We show here the results obtained with PSBAS G-POD service on Valle d'Aosta region, which have been compared to the Deep Seated Gravitational Slope Deformation (DGSD) (reference IFFI project), finding a good correlation with the anomalous areas of surface deformation and the catalogued DGSD (Fig.1). In addition, the results obtained on Valle d'Aosta and Piedmont regions show a good agreement to the mean velocity maps available retrieved from the "Portale Cartografico Nazionale" http://www.pcn.minambiente.it/GN/, which was instead processed by considering PSInSAR technique on the same Envisat ASAR dataset (Fig.2). Finally, we discuss possible future developments of the P-SBAS G-POD service in the Sentinel-1 scenario, when a large amount of SAR images will be available to a greater audience, and how this may impact on the analysis of surface deformation at different spatial and temporal scales.

ESA-GPOD service: new potential for the analysis and interpretation of surface deformation in mountain regions by exploiting the Parallel-SBAS technique

Martina Cignetti;Andrea Manconi;Francesca Ardizzone;Daniele Giordan;Paolo Allasia;Manunta;Francesco Casu
2015

Abstract

Long-term time series of ground displacement are key information for the interpretation of several natural and anthropic hazards. In high mountain environments, the analysis of surface displacements and their relationship with meteo-climatic variables can be exploited to better understand the effects of climate changes on the frequency and the intensity of the landslides and their triggering phenomena (Huggel et al., 2012). In this scenario, the use of straightforward tools and approaches to analyse surface displacements at high spatial and temporal resolutions is a real need. Here we present the preliminary results of the HAMMER project, developed in the framework of NextData initiative (http://www.nextdataproject.it/). HAMMER aims at collecting ground deformation time series, and analysing eventual changes of the deformation trends associated to meteo-climatic variables. In particular, we exploited Differential SAR Interferometry (DInSAR) technique to analyse space-born measurements of surface displacements over areas characterized by slope instability and/or gravitational spreading. We used the Parallel-SBAS, namely PSBAS (Casu et al., 2014), service recently released within the ESA's Grid Processing On Demand (G-POD, http://gpod.eo.esa.int/) environment for the generation of Earth's surface deformation time series and interferometric production. This service performs the full SBAS-DInSAR (Berardino et al., 2002) chain starting from Level 0 data, and generates displacement time series. Data are retrieved through the Virtual Archive 4 (http://eo-virtual-archive4.esa.int/, in the framework of Supersite initiative). The P-SBAS service within G-POD is accessible through a user-friendly web-interface, which allows selecting rapidly the input SAR data, and set easily some useful input parameters for processing (e.g., selection of temporal range, baseline and coherence thresholds set, reference point selection). We produced mean deformation, velocity maps, as well as deformation time series, on a regional scale case (Aosta Valley Region, northern Italy), and at local landslide scale (Puy landslide, Piedmont, northen Italy). The possibility to gather the final results in less than 24h (by processing an average of about 30 SAR images for each frame considered), allowed to perform in relatively short time a large number of attempts. By "tuning" the processing, we have maximized for both datasets the final coverage of coherent points where displacement time series can be traced over time. This was performed by analysing the effect of SAR images acquired in the winter season, as well as of the impact of perpendicular and temporal baseline constraints. We show here the results obtained with PSBAS G-POD service on Valle d'Aosta region, which have been compared to the Deep Seated Gravitational Slope Deformation (DGSD) (reference IFFI project), finding a good correlation with the anomalous areas of surface deformation and the catalogued DGSD (Fig.1). In addition, the results obtained on Valle d'Aosta and Piedmont regions show a good agreement to the mean velocity maps available retrieved from the "Portale Cartografico Nazionale" http://www.pcn.minambiente.it/GN/, which was instead processed by considering PSInSAR technique on the same Envisat ASAR dataset (Fig.2). Finally, we discuss possible future developments of the P-SBAS G-POD service in the Sentinel-1 scenario, when a large amount of SAR images will be available to a greater audience, and how this may impact on the analysis of surface deformation at different spatial and temporal scales.
2015
monitoring
SAR interferometry
G-POD service
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/376704
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