Contribution of GPR method in monitoring and evaluating the conservation state of Fortezza, Rethymno, Greece

Manataki, Meropi; Sarris, Apostolos; Oikonomou, Dimitrios; Simirdanis, Kleanthis; Strapazzon, Guglielmo; Fernández, Pedro Trapero

doi:10.1109/icgpr.2018.8441632

Cited by 3 publications

(2 citation statements)

References 6 publications

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“…As part of this effort, the fortress has been selected and included in the STORM project, with the aim to assist EFARETH in assessing and managing risks associated with natural hazards. More specifically, the local partners of the project EFARETH and the Geophysical-Satellite Remote Sensing and Archaeoenvironment Lab of the Institute for Mediterranean Studies -Foundation for Research and Technology, in collaboration with the European partners, conducted hazard studies [12], non-destructive investigation works [13] and developed a methodology and associated supporting tools for early warning and decision making for risk mitigation [1].…”

Section: Structural Health Monitoring Campaignmentioning

confidence: 99%

Long-Term Structural Health Monitoring of the Fortezza Fortress: Application of Damage Detection Techniques on Existing Cracks

Drygiannakis¹,

Vlachakis²,

Tzigounaki³

2021

12th International Conference on Structural Analysis of Historical Constructions

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Structural Health Monitoring (SHM) consists of an elaborated technique, assisting the assessment of existing structures through the detection of active or sudden damages, as well as the diagnosis of possible causes for them. Within the STORM-project [1], the SHM strategy selected for the assessment of the Venetian fortress of Fortezza in Rethymno, Greece was the continuous crack monitoring of four different existing cracks of the structure, due to their relatively large width, located at the Bastion of St. Paul's, Prophet Elias' and St. Luke's as well as the Episcopal mansion.Besides the crack displacement measurements, several other environmental quantities were monitored at the weather stations, which are known to have a strong influence on the crack width. Considering the fact that most weather fluctuations have reversible effects on structural integrity, it is of great importance to recognize the environmental and operational variation of the structure, and subsequently identify any separate structural change caused by damage [2], [3]. This was achieved by employing a statistical ARX model (Auto-Regressive model with eXogenous input) [4], calibrated for each case after several months. Once this process was completed it was possible to detect possible active damage on the examined structures and estimate possible causes for them.The successful application of the methodology at the four monitored cracks provided important information about their state of damage, possible causes and early warnings in case of hazard. Over the evaluated period, it appears that the bastion of Prophet Elias is in stable condition, while the bastion of St. Luke and St. Paul are vulnerable to heavy precipitation. Moreover, the Episcopal mansion showed a destabilization response during the rainfall period, which is possible to result in the activation of an overturning mechanism.

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Section: Structural Health Monitoring Campaignmentioning

confidence: 99%

Long-Term Structural Health Monitoring of the Fortezza Fortress: Application of Damage Detection Techniques on Existing Cracks

Drygiannakis¹,

Vlachakis²,

Tzigounaki³

2021

12th International Conference on Structural Analysis of Historical Constructions

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“…Recently, the visual inspections, such as photogrammetry and laser scanning (A. Oliveira, 2012) (A. Manzo, 2019), infrared thermal imaging techniques, and ground-penetrating radar (D. Angelis et al, 2017) (M. Manataki et al, 2018) (B. Johnston et al, 2018) are widely used to detect damage to cultural properties. In particular, after acquiring image and point cloud data of cultural property, the damage detection by photogrammetry and laser scanning is analyzed by a 3D-textured mesh model.…”

Section: Introductionmentioning

confidence: 99%

Automatic Damage Detection of Stone Cultural Property Based on Deep Learning Algorithm

Kwon

2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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<p><strong>Abstract.</strong> Outdoor stone cultural properties are continuously affected by the external environment such as wind, rain, and earthquakes. These cause damage to the cultural properties by not only threatening structural stability but also damaging the aesthetic value. Quick detection of these damages is important to enable appropriate preservation treatment in terms of cultural property conservation management. Even though conventional manual damage detection methods are widely used, they are limited by manpower, cost, and other external conditions. In this paper, we propose a system that automatically detects and classifies damage occurring in cultural properties using deep-learning technique to settle these drawbacks. In detail, the damages are classified into four types (i.e., crack, loss, detachment, biological colonization) based on Faster region-based convolutional neural network (R-CNN) algorithm. In addition, we construct an image dataset of stone damage, which is collected by the regular report of the National Designated Cultural Property in 2017 conducted by the Cultural Heritage Administration of S. Korea, and augment its dataset to enhance damage detection performance. From the experiment conducted, we achieved an average confidence score of 94.6&thinsp;% or more on the 20 test images.</p>

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Technologies for the Preservation of Cultural Heritage—A Systematic Review of the Literature

2023

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This work establishes the technological elements that have enabled the preservation, promotion, and dissemination of tangible and intangible cultural heritage in the period from 2018 to 2022. For this, a Systematic Literature Review (SLR) was conducted in the scientific databases Scopus, Science Direct, IEEE and Web of Science, which facilitated the identification of 146 articles related to the topic. A quantitative and qualitative analysis of the journals, authors and topics was carried out, detailing the important variables required to establish the sought-out elements; for this purpose, the following were quantified in the papers: type, topic, categorization, country, and language; in the publications, the type of heritage chosen, the place of the heritage and the type of intervention were investigated. The number of publications reporting the use of some type of technology was also identified, finding that 70% of them show a technological approach to preserve cultural heritage, while 30% refer to other types of interventions. The technologies reported to be used the most are 3D digital technologies (44% of those showing technological applications), augmented reality or virtual reality, henceforth AR/VR (15%).

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Contribution of GPR method in monitoring and evaluating the conservation state of Fortezza, Rethymno, Greece

Cited by 3 publications

References 6 publications

Long-Term Structural Health Monitoring of the Fortezza Fortress: Application of Damage Detection Techniques on Existing Cracks

Long-Term Structural Health Monitoring of the Fortezza Fortress: Application of Damage Detection Techniques on Existing Cracks

Automatic Damage Detection of Stone Cultural Property Based on Deep Learning Algorithm

Technologies for the Preservation of Cultural Heritage—A Systematic Review of the Literature

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