The Rheticus (R) cloud-based platform provides continuous monitoring services of the Earth's surface. One of the services provided by Rheticus (R) is the Displacement Geo-information Service, which offers monthly monitoring of millimetric displacements of the ground surface, landslide areas, the stability of infrastructures, and subsidence due to groundwater withdrawal/entry or from the excavation of mines and tunnels. To provide this information, the Rheticus (R) platform processes a large amount of Geospatial Big Data. In particular, Rheticus (R) is capable to process Synthetic Aperture Radar images acquired by the X-band COSMO-SkyMed constellation, as well as satellite Open Data provided by Copernicus Sentinels, and it is capable to integrate local INSPIRE data sources. In this paper, we summarize the main features of the Rheticus (R) services and we provide examples of the detection and monitoring of geohazard and infrastructure instabilities through Multi-temporal InSAR techniques. Furthermore, we outline the porting activity and the efficient implementation of the most time-consuming algorithmic kernels in the GPGPU environment.

RHETICUS (R): A CLOUD-BASED GEO-INFORMATION SERVICE FOR GROUND INSTABILITIES DETECTION AND MONITORING

Bovenga Fabio
2018

Abstract

The Rheticus (R) cloud-based platform provides continuous monitoring services of the Earth's surface. One of the services provided by Rheticus (R) is the Displacement Geo-information Service, which offers monthly monitoring of millimetric displacements of the ground surface, landslide areas, the stability of infrastructures, and subsidence due to groundwater withdrawal/entry or from the excavation of mines and tunnels. To provide this information, the Rheticus (R) platform processes a large amount of Geospatial Big Data. In particular, Rheticus (R) is capable to process Synthetic Aperture Radar images acquired by the X-band COSMO-SkyMed constellation, as well as satellite Open Data provided by Copernicus Sentinels, and it is capable to integrate local INSPIRE data sources. In this paper, we summarize the main features of the Rheticus (R) services and we provide examples of the detection and monitoring of geohazard and infrastructure instabilities through Multi-temporal InSAR techniques. Furthermore, we outline the porting activity and the efficient implementation of the most time-consuming algorithmic kernels in the GPGPU environment.
2018
Istituto per il Rilevamento Elettromagnetico dell'Ambiente - IREA
Inglese
IEEE International Geoscience and Remote Sensing Symposium proceedings 2018
2238
2240
3
978-1-5386-7149-8
23-27/07/2018
Valenzia, Spagna
Geospatial Big Data
MTInSAR
Cloud computing
GPU computing
ESA Sentinel-1
1
none
Samarelli, Sergio; Agrimano, Luigi; Epicoco, Italo; Cafaro, Massimo; Nutricato, Raffaele; Nitti, Davide Oscar; Bovenga, Fabio
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/354079
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