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Articles

Analysis on the impact of Taiwan far-field earthquakes on the disaster avoidance behavior of people in high-rise buildings in large cities in southeast China

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Pages 2006-2023 | Received 11 Mar 2022, Accepted 11 Jul 2022, Published online: 27 Jul 2022

References

  • Akason JB, Olafsson S, Sigbjörnsson R. 2006. Sigbjörnsson, R (2006) Perception and observation of residential safety during earthquake exposure: a case study. Saf Sci. 44(10):919–933.
  • Alam M, Mahmoodzadeh A, Pirasteh S. 2009. A method for rapid evaluation of masonry buildings against earthquakes. Int Disaster Adv J. 2(3):15–23.
  • Altunişik AC, Atmaca B, Kartal ME, Günaydin M, Demir S, Uluşan A. 2021. Assessment of structural damage following the October 30, 2020 Aegean Sea earthquake and Tsunami. J Earthquake Tsunami. 15(6):2150029. https://doi.org/10.1142/S1793431121500299.
  • Ashbrook D, Starner T. 2003. Using GPS to learn significant locations and predict movement across multiple users. Pers Ubiquit Comput. 7(5):275–286.
  • Atmaca B, Demir S, Günaydin M, Altunişik AC, Hüsem M, Ateş Ş, Adanur S, Angin Z. 2020. Field investigation on the performance of mosques and minarets during the Elazig-Sivrice earthquake. J Perform Constr Facil. 34(6):4020120–4020121.
  • Becker JS, Paton D, Johnston DM, Ronan KR, McClure J. 2017. The role of prior experience in informing and motivating earthquake preparedness. Int J Disaster Risk Reduct. 22:179–193.
  • Bossu R, Roussel F, Fallou L, Landès M, Steed R, Mazet-Roux G, Dupont A, Frobert L, Petersen L. 2018. LastQuake: from rapid information to global seismic risk reduction. Int J Disaster Risk Reduct. 28:32–42.
  • Brown V, Jacquier G, Coulombier D, Balandine S, Belanger F, Legros D. 2001. Rapid assessment of population size by area sampling in disaster situations. Disasters. 25(2):164–171.
  • Calka B, Bielecka E. 2019. Reliability analysis of LandScan gridded population data. The case study of Poland. IJGI. 8(5):222–240.
  • D’Altri AM, Sarhosis V, Milani G, Rots J, Cattari S, Lagomarsino S, Sacco E, Tralli A, Castellazzi G, de Miranda S. 2020. Modeling strategies for the computational analysis of unreinforced masonry structures: Review and classification. Arch Comput Methods Eng. 27(4):1153–1185.
  • Dong L, Shan J. 2013. A comprehensive review of earthquake-induced building damage detection with remote sensing techniques. ISPRS J Photogramm Remote Sens. 84:85–99.
  • Erdik M, Şeşetyan K, Demircioğlu MB, Hancılar U, Zülfikar C. 2011. Rapid earthquake loss assessment after damaging earthquakes. Soil Dyn Earthq Eng. 31(2):247–266.
  • Freire S. 2010. Modeling of spatiotemporal distribution of urban population at high resolution–value for risk assessment and emergency management. In: Geographic information and cartography for risk and crisis management. Berlin Heidelberg: Springer;pp. 53–67.
  • Grasso S, Maugeri M. 2005. Vulnerability of physical environment of the city of Catania using GIS technique. Adv Earthquake Eng. 14:155–175.
  • Hadsell R, Chopra S, LeCun Y. 2006. Dimensionality reduction by learning an invariant mapping. IEEE Conf Comput Vis Pattern Recogn. 2:1735–1742.
  • Haghi M, Fatemi Ghomi SMT, Jolai F. 2017. Developing a robust multi-objective model for pre/post disaster times under uncertainty in demand and resource. J Clean Prod. 154:188–202.
  • Hartigan JA, Wong MA. 1979. Algorithm AS 136: A K-means clustering algorithm. Appl. Stat. 28(1):100–108.
  • Nie GZ, An JW, Deng Y. 2012. Advances in earthquake emergency disaster service. Seismol Geol. 34(4):728–791.
  • Rumelhart DE, Hinton GE, Williams RJ. 1986. Learning representations by back-propagating errors. Nature. 323(6088):533–536.
  • Sakaki T, Okazaki M, Matsuo Y. 2010. Earthquake shakes Twitter users: real-time event detection by social sensors. Proceedings of 19th international conference on World wide web.Raleigh, North Carolina, USA, 851–860.
  • Sandholt PE, Farrugia CJ, Moen J, Noraberg Ø, Lybekk B, Sten T, Hansen T. 1998. A classification of dayside auroral forms and activities as a function of interplanetary magnetic field orientation. J Geophys Res. 103(A10):23325–23345.
  • Setiawan B, Jaksa M, Griffith M. 2018. An investigation of local site effects in Adelaide, South Australia: learning from the past. Boll Geofis Appl. 59(1):27–46.
  • Shaham U, Stanton K, Li H. 2018. SpectralNet: Spectral clustering using deep neural networks. In International Conference on Learning Representations (ICLR2018); Vancouver, Canada. p. 1–20.
  • Smith SK. 1996. Demography of disaster: population estimates after hurricane Andrew. Popul Res Policy Rev. 15(5):459–477.
  • Sridharan H, Qiu F. 2013. A spatially disaggregated areal interpolation model using light detection and ranging-derived building volumes. Geogr Anal. 45(3):238–258.
  • Tomás L, Fonseca L, Almeida C, Leonardi F, Pereira M. 2016. Urban population estimation based on residential buildings volume using IKONOS-2 images and lidar data. Int J Remote Sens. 37(sup1):1–28.
  • Wang Y, Taylor JE. 2018. Coupling sentiment and human mobility in natural disasters: a Twitter-based study of the 2014 South Napa earthquake. Nat Hazards. 92(2):907–925.
  • Yu J, Wen JH. 2016. Multi-criteria satisfaction assessment of the spatial distribution of urban emergency shelters based on high-precision population estimation. Int J Disaster Risk Sci. 7(4):413–429.
  • Zhang XB, Kelly S, Ahmad K. 2016. The Slandail monitor: real-time processing and visualisation of social media data for emergency management. In: Proceedings of 2016 11th International Conference on Availability, Reliability and Security; New York: IEEE. p. 786–791.
  • Zhong C, Arisona SM, Huang X, Batty M, Schmitt G. 2014. Detecting the dynamics of urban structure through spatial network analysis. Int J Geogr Inf Sci. 28(11):2178–2199.