Commenced in January 2007
Paper Count: 31108
Exploring the Physical Environment and Building Features in Earthquake Disaster Areas
Abstract:Earthquake is an unpredictable natural disaster and intensive earthquakes have caused serious impacts on social-economic system, environmental and social resilience. Conventional ways to mitigate earthquake disaster are to enhance building codes and advance structural engineering measures. However, earthquake-induced ground damage such as liquefaction, land subsidence, landslide happen on places nearby earthquake prone or poor soil condition areas. Therefore, this study uses spatial statistical analysis to explore the spatial pattern of damaged buildings. Afterwards, principle components analysis (PCA) is applied to categorize the similar features in different kinds of clustered patterns. The results show that serious landslide prone area, close to fault, vegetated ground surface and mudslide prone area are common in those highly damaged buildings. In addition, the oldest building might not be directly referred to the most vulnerable one. In fact, it seems that buildings built between 1974 and 1989 become more fragile during the earthquake. The incorporation of both spatial statistical analyses and PCA can provide more accurate information to subsidize retrofit programs to enhance earthquake resistance in particular areas.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1125129Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 887
 K. M. Allen, “Community-based disaster preparedness and climate adaptation: local capacity-building in the Philippines,” Disasters, vol. 30 no. 1, pp. 81-101, 2006.
 E. James, “Getting ahead of the next disaster: recent preparedness efforts in Indonesia,” Dev Pract, vol. 18, no. 3, pp. 424-429, 2008.
 D. Guga-Spair, D. & F. Vos, “Earthquakes: epidemiological perspective on patterns and trends,” A draft paper submitted to Human casualties in natural disasters: progress in modeling and mitigation, pp. 1-18, 2010.
 CRED, “Annual disaster statistical review 2011: The numbers and trends,” Ciaco Imprimerie, Louvain-la-Neuve (Bulgium), 2011.
 K. O’ Brien, L. Sygna, R. Leichenko, W. N. Adger, J. Barnett, T. Mitchell, L. Schipper, T. Tanner, C. Vogel, C. Mortreux, “Disaster risk reduction, climate change adaptation and human security: A commissioned report for the Norwegian Ministry of Foreign affairs,” Global Environmental Change and Human Security, 2008.
 D. W. Edgington, “Reconstructing Kobe: The geography of crisis and opportunity,” UBC Press, 2011.
 N. N. Ambraseys, “Nicholas Neocles Ambraseys 1929–2012,” Journal of Earthquake Engineering, vol. 17, no. 3, pp. 301-303, 2013.
 Committee to Develop a Long-Term Research Agenda for the Network for Earthquake Engineering Simulation (NEES), “Preventing Earthquake Disasters: The Grand Challenge in Earthquake Engineering: A Research Agenda for the Network for Earthquake Engineering Simulation (NEES),” National Academies Press, 2003.
 W. Dong, G. Morrow, A. Tanaka, H. Kagawa, L. C. Chou, Y. B. Tsai, W. Hsu, L. Johnson, C. Van Anne, S. Segawa, C. H. Yeh, K. L. W., W. L. Chiang, “Event report: Chi-Chi, Taiwan Earthquake,” Risk Management Solution, Inc., 2000.
 Y. M. Su, and C. C. Tsai, “The research for administrable mechanisms of active faults developed circumscription and the policy assessment,” Journal of City and Planning, vol. 30, no. 4, pp. 301-323, 2003.
 C. Elachi, and A. Donnellan, “Preparing L.S. for potential earthquakes: Applications of space technology,” in The L.A. earthquake source book, Capital Offset Co. pp.58-65, 2008.
 USGS, “National seismic hazard map,” http://earthquake.usgs.gov/hazards/products/conterminous/index.php#2014 (2016/5/1)
 T. H. Jordan, “The P-word,” in The L.A. earthquake source book. Capital Offset Co. pp.36-43, 2008.
 K. Pearson, “On lines and planes of closest fit to systems of points in space,” Philos. Mag., vol. 2, pp.559-572, 1901.
 H. Hotelling, “Analysis of a complex of statistical variables into principle components,” J. Educ. Psychol., vol.24, no.6, pp.417-441, 1933.
 H. Abdi, and L. J. Williams, “Principle component analysis,” Wiley Interdisciplinary Reviews: Computational Statistics, vol.2, no.4, pp.433-459, 2010.
 M. S. Srivastava, “Methods of multivariate statistics,” Wiley-Interscience, New York, 2002.
 W. R. Tobler, “A computer movie simulating urban growth in the Detroit region,” Economic Geography, vol. 46, no. supplement, pp.234-240.
 Central Geology Survey, “Active Fault of Taiwan,” Central Geology Survey, Taipei, 2013.