The SGAM (Smart Geotechnical Asset Management) project will address the critical issue of natural hazards such as earthquakes and landslides that pose threats to global infrastructure. SGAM is a semi-automated decision support system that integrates cutting-edge technology, data fusion algorithms, and satellite Earth Observation data. Its comprehensive approach involves extensive data collection, which emphasizes the importance of data quality for hazard analyses. In this paper, the focus is on hazard assessment, which requires a comprehensive study of the available data and how they can be integrated to produce a meaningful result. Remote sensing analyses, including InSAR, assess the impact of geological processes on infrastructure, thereby enhancing hazard analysis. The hazard analyses conducted in the framework of the SGAM project are customized to suit various types of processes that pose threats to infrastructure. As the project progresses, the next challenge will be to effectively incorporate considerations of exposure and vulnerability into the assessment framework. Addressing this challenge will require a comprehensive and integrated approach, utilising advanced technologies and collaborative efforts with infrastructure managers to ensure a holistic understanding of infrastructure resilience across diverse contexts and conditions.

SGAM – Smart Geotechnical Asset Management / Di Renzo, Maria Elena; Belcecchi, Niccolò; Brunetti, Alessandro; Chessa, Andrea; Mazzanti, Paolo; Scancella, Stefano; Valerio, Emanuela. - In: THE E-JOURNAL OF NONDESTRUCTIVE TESTING. - ISSN 1435-4934. - 29:7(2024). ( 11th European Workshop on Structural Health Monitoring, EWSHM 2024 Potsdam ) [10.58286/29729].

SGAM – Smart Geotechnical Asset Management

Di Renzo, Maria Elena
;
Mazzanti, Paolo;Scancella, Stefano;Valerio, Emanuela
2024

Abstract

The SGAM (Smart Geotechnical Asset Management) project will address the critical issue of natural hazards such as earthquakes and landslides that pose threats to global infrastructure. SGAM is a semi-automated decision support system that integrates cutting-edge technology, data fusion algorithms, and satellite Earth Observation data. Its comprehensive approach involves extensive data collection, which emphasizes the importance of data quality for hazard analyses. In this paper, the focus is on hazard assessment, which requires a comprehensive study of the available data and how they can be integrated to produce a meaningful result. Remote sensing analyses, including InSAR, assess the impact of geological processes on infrastructure, thereby enhancing hazard analysis. The hazard analyses conducted in the framework of the SGAM project are customized to suit various types of processes that pose threats to infrastructure. As the project progresses, the next challenge will be to effectively incorporate considerations of exposure and vulnerability into the assessment framework. Addressing this challenge will require a comprehensive and integrated approach, utilising advanced technologies and collaborative efforts with infrastructure managers to ensure a holistic understanding of infrastructure resilience across diverse contexts and conditions.
2024
11th European Workshop on Structural Health Monitoring, EWSHM 2024
data-driven decision-making; hazard assessment; infrastructure resilience; large-scale monitoring; machine learning; satellite applications
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SGAM – Smart Geotechnical Asset Management / Di Renzo, Maria Elena; Belcecchi, Niccolò; Brunetti, Alessandro; Chessa, Andrea; Mazzanti, Paolo; Scancella, Stefano; Valerio, Emanuela. - In: THE E-JOURNAL OF NONDESTRUCTIVE TESTING. - ISSN 1435-4934. - 29:7(2024). ( 11th European Workshop on Structural Health Monitoring, EWSHM 2024 Potsdam ) [10.58286/29729].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1742899
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