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).
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References
An L, Zhang J, Gong L, Li Q (2016) Integration of SAR image and vulnerability data for building damage degree estimation. In: 2016 IEEE international geoscience and remote sensing symposium (IGARSS). IEEE, pp 4263–4266
Chesnel AL, Binet R, Wald L (2007) Quantitative assessment of building damage in urban area using very high resolution images. In: 2007 urban remote sensing joint event. IEEE, pp 1–5
Copernicus (2016) http://emergency.copernicus.eu/mapping/list-of-components/EMSR177
GdL INGV 2016, Gruppo di Lavoro INGV sul terremoto di Amatrice (2016). Secondo rapporto di sintesi sul Terremoto di Amatrice Ml6.0 del 24 agosto 2016 (Italia Centrale). doi:10.5281/zenodo.154400
Huang S, Dou A, Wang X, Wang J (2016) Earthquake-induced building damage detection method based on normal computation of neighboring points searching on 2D-plane. In: 2016 IEEE international geoscience and remote sensing symposium (IGARSS). IEEE, pp 4251–4254
Masi A, Santarsiero G, Digrisolo A, Chiauzzi L, Manfredi V (2016) Procedures and experiences in the post-earthquake usability evaluation of ordinary buildings. Boll Geofis Teor Appl 57(2):199–210
Saito K, Spence R (2004) Rapid damage mapping using post-earthquake satellite images. In: Proceedings of 2004 IEEE international geoscience and remote sensing symposium, 2004. IGARSS’04, vol. 4. IEEE, pp 2272–2275
Santarsiero G, Chiauzzi L, Masi A (2016) Analisi del danneggiamento di edifici situati nella zona Sud del comune di Amatrice: confronto pre e post sisma del 24/08/2016 (V2). http://www.reluis.it
Yamazaki F, Kouchi KI, Kohiyama M, Muraoka N, Matsuoka M (2004) Earthquake damage detection using high-resolution satellite images. In: Proceedings of 2004 IEEE international geoscience and remote sensing symposium, 2004. IGARSS’04, vol 4. IEEE, pp 2280–2283
Zhai W, Shen HF, Huang CL, Pei WS (2016) Building damage information investigation after earthquake using single post-event PolSAR image. In: 2016 IEEE international Geoscience and remote sensing symposium (IGARSS). IEEE, pp 7338–7341
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Masi, A., Chiauzzi, L., Santarsiero, G. et al. Seismic damage recognition based on field survey and remote sensing: general remarks and examples from the 2016 Central Italy earthquake. Nat Hazards 86 (Suppl 1), 193–195 (2017). https://doi.org/10.1007/s11069-017-2776-8
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DOI: https://doi.org/10.1007/s11069-017-2776-8