scholarly journals Multi-Temporal InSAR Structural Damage Assessment: The London Crossrail Case Study

2018 ◽  
Vol 10 (2) ◽  
pp. 287 ◽  
Author(s):  
Pietro Milillo ◽  
Giorgia Giardina ◽  
Matthew DeJong ◽  
Daniele Perissin ◽  
Giovanni Milillo
Author(s):  
Gianfranco Nicodemo ◽  
Dario Peduto ◽  
Settimio Ferlisi

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.


Author(s):  
A. Vetrivel ◽  
D. Duarte ◽  
F. Nex ◽  
M. Gerke ◽  
N. Kerle ◽  
...  

Quick post-disaster actions demand automated, rapid and detailed building damage assessment. Among the available technologies, post-event oblique airborne images have already shown their potential for this task. However, existing methods usually compensate the lack of pre-event information with aprioristic assumptions of building shapes and textures that can lead to uncertainties and misdetections. However, oblique images have been already captured over many cities of the world, and the exploitation of pre- and post-event data as inputs to damage assessment is readily feasible in urban areas. In this paper, we investigate the potential of multi-temporal oblique imagery for detailed damage assessment focusing on two methodologies: the first method aims at detecting severe structural damages related to geometrical deformation by combining the complementary information provided by photogrammetric point clouds and oblique images. The developed method detected 87% of damaged elements. The failed detections are due to varying noise levels within the point cloud which hindered the recognition of some structural elements. We observed, in general that the façade regions are very noisy in point clouds. To address this, we propose our second method which aims to detect damages to building façades using the oriented oblique images. The results show that the proposed methodology can effectively differentiate among the three proposed categories: collapsed/highly damaged, lower levels of damage and undamaged buildings, using a computationally light-weight approach. We describe the implementations of the above mentioned methods in detail and present the promising results achieved using multi-temporal oblique imagery over the city of L’Aquila (Italy).


Author(s):  
A. Vetrivel ◽  
D. Duarte ◽  
F. Nex ◽  
M. Gerke ◽  
N. Kerle ◽  
...  

Quick post-disaster actions demand automated, rapid and detailed building damage assessment. Among the available technologies, post-event oblique airborne images have already shown their potential for this task. However, existing methods usually compensate the lack of pre-event information with aprioristic assumptions of building shapes and textures that can lead to uncertainties and misdetections. However, oblique images have been already captured over many cities of the world, and the exploitation of pre- and post-event data as inputs to damage assessment is readily feasible in urban areas. In this paper, we investigate the potential of multi-temporal oblique imagery for detailed damage assessment focusing on two methodologies: the first method aims at detecting severe structural damages related to geometrical deformation by combining the complementary information provided by photogrammetric point clouds and oblique images. The developed method detected 87% of damaged elements. The failed detections are due to varying noise levels within the point cloud which hindered the recognition of some structural elements. We observed, in general that the façade regions are very noisy in point clouds. To address this, we propose our second method which aims to detect damages to building façades using the oriented oblique images. The results show that the proposed methodology can effectively differentiate among the three proposed categories: collapsed/highly damaged, lower levels of damage and undamaged buildings, using a computationally light-weight approach. We describe the implementations of the above mentioned methods in detail and present the promising results achieved using multi-temporal oblique imagery over the city of L’Aquila (Italy).


Sensors ◽  
2018 ◽  
Vol 18 (5) ◽  
pp. 1571 ◽  
Author(s):  
Jhonatan Camacho Navarro ◽  
Magda Ruiz ◽  
Rodolfo Villamizar ◽  
Luis Mujica ◽  
Jabid Quiroga

Author(s):  
Brahim Benzougagh ◽  
Pierre-Louis Frison ◽  
Sarita Gajbhiye Meshram ◽  
Larbi Boudad ◽  
Abdallah Dridri ◽  
...  

Geosciences ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 133
Author(s):  
Jérémie Sublime

The Tohoku tsunami was a devastating event that struck North-East Japan in 2011 and remained in the memory of people worldwide. The amount of devastation was so great that it took years to achieve a proper assessment of the economical and structural damage, with the consequences still being felt today. However, this tsunami was also one of the first observed from the sky by modern satellites and aircrafts, thus providing a unique opportunity to exploit these data and train artificial intelligence methods that could help to better handle the aftermath of similar disasters in the future. This paper provides a review of how artificial intelligence methods applied to case studies about the Tohoku tsunami have evolved since 2011. We focus on more than 15 studies that are compared and evaluated in terms of the data they require, the methods used, their degree of automation, their metric performances, and their strengths and weaknesses.


Geosciences ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 74
Author(s):  
Luis A. Pinzón ◽  
Luis G. Pujades ◽  
Irving Medranda ◽  
Rodrigo E. Alva

In this work, the directionality effects during the MW 7.8 earthquake, which occurred in Muisne (Ecuador) on 16 April 2016, were analyzed under two perspectives. The first one deals with the influence of these effects on seismic intensity measures (IMs), while the second refers to the assessment of the expected damage of a specific building located in Manta city, Ecuador, as a function of its azimuthal orientation. The records of strong motion in 21 accelerometric stations were used to analyze directionality in seismic actions. At the closest station to the epicenter (RRup = 20 km), the peak ground acceleration was 1380 cm/s2 (EW component of the APED station). A detailed study of the response spectra ratifies the importance of directionality and confirms the need to consider these effects in seismic hazard studies. Differences between IMs values that consider the directionality and those obtained from the as-recorded accelerograms are significant and they agree with studies carried out in other regions. Concerning the variation of the expected damage with respect to the building orientation, a reinforced concrete building, which was seriously affected by the earthquake, was taken as a case study. For this analysis, the accelerograms recorded at a nearby station and detailed structural documentation were used. The ETABS software was used for the structural analysis. Modal and pushover analyses were performed, obtaining capacity curves and capacity spectra in the two main axes of the building. Two advanced methods for damage assessment were used to obtain fragility and mean damage state curves. The performance points were obtained through the linear equivalent approximation. This allows estimation and analysis of the expected mean damage state and the probability of complete damage as functions of the building orientation. Results show that the actual probability of complete damage is close to 60%. This fact is mainly due to the greater severity of the seismic action in one of the two main axes of the building. The results are in accordance with the damage produced by the earthquake in the building and confirm the need to consider the directionality effects in damage and seismic risk assessments.


Author(s):  
Chin-Hsiung Loh ◽  
Min-Hsuan Tseng ◽  
Shu-Hsien Chao

One of the important issues to conduct the damage detection of a structure using vibration-based damage detection (VBDD) is not only to detect the damage but also to locate and quantify the damage. In this paper a systematic way of damage assessment, including identification of damage location and damage quantification, is proposed by using output-only measurement. Four level of damage identification algorithms are proposed. First, to identify the damage occurrence, null-space and subspace damage index are used. The eigenvalue difference ratio is also discussed for detecting the damage. Second, to locate the damage, the change of mode shape slope ratio and the prediction error from response using singular spectrum analysis are used. Finally, to quantify the damage the RSSI-COV algorithm is used to identify the change of dynamic characteristics together with the model updating technique, the loss of stiffness can be identified. Experimental data collected from the bridge foundation scouring in hydraulic lab was used to demonstrate the applicability of the proposed methods. The computation efficiency of each method is also discussed so as to accommodate the online damage detection.


Sign in / Sign up

Export Citation Format

Share Document