摄影测量学
概率逻辑
计算机科学
下沉
工程类
建筑工程
法律工程学
土木工程
地质学
人工智能
构造盆地
古生物学
作者
Mirko Calò,Sergio Ruggieri,Angelo Doglioni,Maria Morga,Andrea Nettis,Vincenzo Simeone,Giuseppina Uva,Mirko Calò,Sergio Ruggieri,Angelo Doglioni,Maria Morga,Andrea Nettis,Vincenzo Simeone,Giuseppina Uva
标识
DOI:10.1080/15732479.2024.2423032
摘要
Among the natural risks to which structures and infrastructures are subjected, the action of geohazards is often ignored. Several efforts are required to predict geological effects on the existing built heritage, such as by employing sensor-based systems or by performing periodical visual inspections. Alternatively, novel cost-effective techniques could be used. The paper presents a probabilistic-based approach to evaluate the occurrence of subsidence phenomena affecting existing structures and infrastructures, by combining information provided by multitemporal interferometry via synthetic aperture radar (MTInSAR) data and unmanned aerial vehicle (UAV) photogrammetry. Given a structure to monitor and a period of observation, the idea consists of retrieving MTInSAR data about the structure and performing UAV flight surveys on the surrounding area at the beginning and end of the considered period. From both surveys, statistical distributions of the spatiotemporal velocities can be processed and evaluated toward a predefined limit state. The obtained results are classified under different scenarios, to reveal the occurrence of possible subsidence phenomena. The proposed methodology was firstly validated on a real landslide (the vertical component was assessed) and, subsequently, was tested on another case for risk prediction, showing a satisfying capacity of providing warnings to employ risk mitigation plans.
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