Seismic damage recognition based on field survey and remote sensing: general remarks and examples from the 2016 Central Italy earthquake

A. Masi (), L. Chiauzzi, G. Santarsiero, M. Liuzzi and V. Tramutoli
Additional contact information
A. Masi: University of Basilicata
L. Chiauzzi: University of Basilicata
G. Santarsiero: University of Basilicata
M. Liuzzi: University of Basilicata
V. Tramutoli: University of Basilicata

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2017, vol. 86, issue 1, No 13, 193-195

Abstract: Abstract One of the most critical issues in the management of post-earthquake emergency is the prompt identification of the most damaged urban areas. Rapid detection of damage distribution is crucial for Civil Protection during the management of the first emergency phase, in order to both address assistance teams and identify priorities in planning the usability inspections, thus permitting people to go back, as safe as possible, to their houses. Generally, the estimation of building usability is performed by means of a building-by-building survey based on a form to be filled out by expert technicians (Masi et al. 2016). Different countries adopt different forms whose result in terms of usability is dependent essentially on building damage and, in some cases, vulnerability conditions of buildings. When the affected area is large, usability inspections can require a lot of time and a huge number of expert technicians. Therefore, great efforts have been made during past earthquakes in order to define rapid procedures to identify areas not severely damaged and then potentially with a low percentage of unusable buildings. In this framework, many experiences have been carried out worldwide in order to identify, in the immediate aftermath of an earthquake, the damage distribution through remote sensing approaches, possibly combined to field survey data (e.g., Saito and Spence 2004; Yamazaki et al. 2004; Chesnel et al. 2007; Zhai et al. 2016; An et al. 2016; Huang et al. 2016).

Keywords: Earthquake; Buildings; Damage recognition; Field survey; Remote sensing (search for similar items in EconPapers)
Date: 2017
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11069-017-2776-8 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:nathaz:v:86:y:2017:i:1:d:10.1007_s11069-017-2776-8

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11069

DOI: 10.1007/s11069-017-2776-8

Access Statistics for this article

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards is currently edited by Thomas Glade, Tad S. Murty and Vladimír Schenk

More articles in Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards from Springer, International Society for the Prevention and Mitigation of Natural Hazards
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().