Buildings in subsiding areas may suffer from settlements causing damages of different severity levels with high impact in terms of yearly economic losses. In these contexts, a systematic damage assessment jointly with continuous monitoring of relevant parameters (e.g. settlements exhibited by points located on the roof) can be extremely useful to control the building behaviour and develop forecasting models. In this regard, the paper presents the results of an integrated analysis carried out on a subsidence-affected urban area in the Netherlands where the availability of multi-temporal building damage surveys and a long DInSAR monitoring dataset allowed both retrieving quantitative empirical relationships between the cause (magnitude of the selected intensity parameter, IP) and the effect (recorded damage severity level, DL) and generating empirical fragility and vulnerability curves. The results pointed out the importance of considering the exact dating of the onset of building damage and the corresponding magnitude of the considered IP in the generation of quantitative forecasting models.

Building damage assessment and settlement monitoring in subsidence-affected urban areas: case study in the Netherlands

Gianfranco Nicodemo;Dario Peduto;Settimio Ferlisi
2020

Abstract

Buildings in subsiding areas may suffer from settlements causing damages of different severity levels with high impact in terms of yearly economic losses. In these contexts, a systematic damage assessment jointly with continuous monitoring of relevant parameters (e.g. settlements exhibited by points located on the roof) can be extremely useful to control the building behaviour and develop forecasting models. In this regard, the paper presents the results of an integrated analysis carried out on a subsidence-affected urban area in the Netherlands where the availability of multi-temporal building damage surveys and a long DInSAR monitoring dataset allowed both retrieving quantitative empirical relationships between the cause (magnitude of the selected intensity parameter, IP) and the effect (recorded damage severity level, DL) and generating empirical fragility and vulnerability curves. The results pointed out the importance of considering the exact dating of the onset of building damage and the corresponding magnitude of the considered IP in the generation of quantitative forecasting models.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11386/4738575
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