Damage assessment of San Francesco Church in Amandola hit by Central Italy 2016-2017 seismic event

2020 ◽  
Author(s):  
Ersilia Giordano ◽  
Angela Ferrante ◽  
Elisa Ribilotta ◽  
Francesco Clementi ◽  
Stefano Lenci
Keyword(s):  
Damage Assessment ◽  
Seismic Event ◽  
Central Italy

scholarly journals POST-DISASTER DAMAGE ASSESSMENT THROUGH COHERENT CHANGE DETECTION ON SAR IMAGERY

2018 ◽  
Vol XLII-3 ◽  
pp. 431-436 ◽  
Author(s):  
L. Guida ◽  
P. Boccardo ◽  
I. Donevski ◽  
L. Lo Schiavo ◽  
M. E. Molinari ◽  
...  
Keyword(s):  
Change Detection ◽  
Damage Assessment ◽  
Central Italy ◽  
Weather Conditions ◽  
Earthquake Scenario ◽  
Central Italy Earthquake ◽  
Novel Approach ◽  
Coherent Change Detection ◽  
Sar Imagery ◽  
Bad Weather

Damage assessment is a fundamental step to support emergency response and recovery activities in a post-earthquake scenario. In recent years, UAVs and satellite optical imagery was applied to assess major structural damages before technicians could reach the areas affected by the earthquake. However, bad weather conditions may harm the quality of these optical assessments, thus limiting the practical applicability of these techniques. In this paper, the application of Synthetic Aperture Radar (SAR) imagery is investigated and a novel approach to SAR-based damage assessment is presented. Coherent Change Detection (CCD) algorithms on multiple interferometrically pre-processed SAR images of the area affected by the seismic event are exploited to automatically detect potential damages to buildings and other physical structures. As a case study, the 2016 Central Italy earthquake involving the cities of Amatrice and Accumoli was selected. The main contribution of the research outlined above is the integration of a complex process, requiring the coordination of a variety of methods and tools, into a unitary framework, which allows end-to-end application of the approach from SAR data pre-processing to result visualization in a Geographic Information System (GIS). A prototype of this pipeline was implemented, and the outcomes of this methodology were validated through an extended comparison with traditional damage assessment maps, created through photo-interpretation of high resolution aerial imagery. The results indicate that the proposed methodology is able to perform damage detection with a good level of accuracy, as most of the detected points of change are concentrated around highly damaged buildings.

scholarly journals Change Detection Based Building Damage Assessment Method Using Radar Imageries with GLCM Textural Parameters

2020 ◽  
Author(s):  
Asset Akhmadiya ◽  
Nabi Nabiyev ◽  
Khuralay Moldamurat ◽  
Kanagat Dyusekeev ◽  
Sabyrzhan Atanov
Keyword(s):  
Remote Sensing ◽  
Change Detection ◽  
Damage Assessment ◽  
Central Italy ◽  
Remote Sensing Data ◽  
Research Paper ◽  
Building Damage ◽  
Main Task ◽  
Radar Remote Sensing ◽  
Sensing Data

In this research paper, change detection based methods were considered to find collapsed and intact buildings using radar remote sensing data or radar imageries. Main task of this research paper is collection of most relevant scientific research in field of building damage assessment using radar remote sensing data. Several methods are selected and presented as best methods in present time, there are methods with using interferometric coherence, backscattering coefficients in different spatial resolution. In conclusion, methods are given in end, which show, which methods and radar remote sensing data give more accuracy and more available for building damage assessment. Low resolution Sentinel-1A/B radar remote sensing data are recomended as free available for monitoring of destruction degree in microdistrict level. Change detection and texture based method are used together to increase overall accuracy. Homogeneity and Dissimilarity GLCM texture parameters found as better for separation of a collapsed and intact buildings. Dual polarization (VV,VH) backscattering coefficients and coherence coefficients (before earthquake and coseismic) were fully utilized for this study. There were defined the better multi variable for supervised classification of none building, damaged and intact buildings features in urban areas. In this work, we were achieved overall accuracy 0.77, producer’s accuracy for none building is 0.84, for damaged building case 0.85, for intact building 0.64. Amatrice town was chosen as most damaged from 2016 Central Italy Earthquake.

scholarly journals DEEP LEARNING FOR AUTOMATIC BUILDING DAMAGE ASSESSMENT: APPLICATION IN POST-DISASTER SCENARIOS USING UAV DATA

2021 ◽  
Vol V-1-2021 ◽  
pp. 113-120
Author(s):  
A. Calantropio ◽  
F. Chiabrando ◽  
M. Codastefano ◽  
E. Bourke
Keyword(s):  
Deep Learning ◽  
Damage Assessment ◽  
Central Italy ◽  
Remote Sensing Data ◽  
Building Damage ◽  
Research Field ◽  
Future Research ◽  
Damage Classification ◽  
Research Perspectives ◽  
Post Disaster

Abstract. During the last few years, the technical and scientific advances in the Geomatics research field have led to the validation of new mapping and surveying strategies, without neglecting already consolidated practices. The use of remote sensing data for damage assessment in post-disaster scenarios underlined, in several contexts and situations, the importance of the Geomatics applied techniques for disaster management operations, and nowadays their reliability and suitability in environmental emergencies is globally recognized. In this paper, the authors present their experiences in the framework of the 2016 earthquake in Central Italy and the 2019 Cyclone Idai in Mozambique. Thanks to the use of image-based survey techniques as the main acquisition methods (UAV photogrammetry), damage assessment analysis has been carried out to assess and map the damages that occurred in Pescara del Tronto village, using DEEP (Digital Engine for Emergency Photo-analysis) a deep learning tool for automatic building footprint segmentation and building damage classification, functional to the rapid production of cartography to be used in emergency response operations. The performed analyses have been presented, and the strengths and weaknesses of the employed methods and techniques have been outlined. In conclusion and based on the authors' experience, some operational suggestions and best practices are provided and future research perspectives within the same research topic are introduced.

scholarly journals Analysis of the 2016 Amatrice earthquake macroseismic data

2016 ◽  
Vol 59 ◽  
Author(s):  
Lorenzo Hofer ◽  
Mariano Angelo Zanini ◽  
Flora Faleschini
Keyword(s):  
Critical Analysis ◽  
Seismic Event ◽  
Residential Buildings ◽  
Central Italy ◽  
Macroseismic Data ◽  
Significant Damage ◽  
Macroseismic Scale ◽  
The University ◽  
2016 Amatrice Earthquake ◽  
Macroseismic Survey

On August 24, 2016, a sudden MW 6.0 seismic event hit Central Italy, causing 298 victims and significant damage to residential buildings and cultural heritage. In the days following the mainshock, a macroseismic survey was conducted by teams of the University of Padova, according to the European Macroseismic Scale (EMS98). In this contribution, a critical analysis of the collected macroseismic data is presented and some comparisons were performed with the recent 2012 Emilia sequence.

Damage Assessment of San Francesco Church in Amandola Hit by Central Italy 2016-2017 Seismic Event

2019 ◽  
Vol 817 ◽  
pp. 627-633
Author(s):  
Ersilia Giordano ◽  
Angela Ferrante ◽  
Elisa Ribilotta ◽  
Francesco Clementi ◽  
Stefano Lenci
Keyword(s):  
Seismic Event ◽  
Global Analysis ◽  
Central Italy ◽  
Element Model ◽  
Constitutive Law ◽  
Nonlinear Static Analysis ◽  
Local Analysis ◽  
Marche Region ◽  
Nonlinear Static ◽  
The Church

Italy is a high seismic risk country since 1900 more than 30 earthquakes with magnitude greater than Mw=5.8 have occurred, and the last one is the Central Italy seismic sequence. The first shock occurred in the 24 August (Mw=6.2) followed by another stronger quake in the 30th October (Mw=6.5). It hit the regions of Marche, Umbria, and Abruzzo heavily causing many deaths, injuries and extensive damages on the cultural heritage. This paper analyses the church of San Francesco in Amadola, located in the Marche region that has been considered condemned for the severe damages reported after these earthquakes. The church is globally analyzed by the application of nonlinear static analysis on a Finite Element Model where the nonlinearity of masonry is taking into account with a proper constitutive law. The study wants to prove how global analysis combined by the local analysis can reproduce the behavior of this structure during a quake, showing that it can repeat the real damages produced by earthquakes.

scholarly journals Damage assessment of water supply networks due to seismic events using vulnerability functions

2021 ◽  
Vol 73 (07) ◽  
pp. 737-749
Author(s):  
Stjepan Lakusic
Keyword(s):  
Water Supply ◽  
Damage Assessment ◽  
Seismic Event ◽  
Seismic Events ◽  
Supply Networks ◽  
Water Supply Networks ◽  
Repair Costs ◽  
The Given ◽  
The City ◽  
Vulnerability Functions

The paper presents commonly used methodology for assessing damage of water supply networks after a seismic event. The methodology relies on deriving and applying so-called vulnerability function. An overview of the existing vulnerability functions is given together with parameters, primarily related to soil deformations, which are influencing the assessment. Also, a critical review of the possibility of their use is given. Finally, by using two approaches, the estimated number of damages, with associated repair costs, is given for the water supply network of the City of Petrinja after the earthquake on December 29, 2020. With a total of 3 800 new damages, it is estimated that the total repair costs are around HRK 28 million. The accuracy of these estimates should be verified after detailed collection and processing of relevant data in accordance with the given guidelines.

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