single-dr.php

JDR Vol.13 No.1 pp. 125-137
(2018)
doi: 10.20965/jdr.2018.p0125

Note:

Understanding Regional Building Characteristics in Yangon Based on Digital Building Model

Osamu Murao*1,†, Takuma Usuda*2, Hideomi Gokon* 3, Kimiro Meguro*3, Wataru Takeuchi*3, Kazuya Sugiyasu* 1, and Khin Than Yu*4

*1International Research Institute of Disaster Science, Tohoku University
468-1 Aoba, Aramaki, Aoba-ku, Sendai 980-0845, Japan

Corresponding author

*2Former Graduate School Student, Graduate School of Engineering, Tohoku University

*3Institute of Industrial Science, The University of Tokyo, Japan

*4Yangon Technological University, Myanmar

Received:
September 11, 2017
Accepted:
February 1, 2018
Published:
February 20, 2018
Keywords:
urban vulnerability, Myanmar, building collapse risk, remote sensing, DBM
Abstract

It is indispensable for a government to assess urban vulnerability to natural disasters such as earthquakes or flood in order to take appropriate disaster measures. However, it is sometimes difficult to obtain necessary dataset for cities or regions, especially for developing countries. The authors have been involved in a SATREPS project named “Development of a Comprehensive Disaster Resilience System and Collaboration Platform in Myanmar,” which aims to make urban vulnerability maps for Yangon City based on several datasets including building inventory of each ward. However, Yangon City has not catalogued enough data for the assessment so far. In this context, in order to understand and to arrange regional building characteristics of the city, this paper explores the possibility of using digital building model (DBM) data obtained from remote sensing imageries for the urban vulnerability assessment.

Firstly, a field survey was conducted in Sanchaung Township, and building characteristics such as structural types and the number of stories were analyzed. Therefore, DBM data was prepared for the following comparative analysis. Thirdly, additional field surveys were conducted in Latha and Pabedan Townships, located in the central business districts in the city. Finally, DBM data and the actual building data obtained by the surveys were compared to examine the applicability of DBM for building collapse risk assessment. As a result, it was found that DBM data of 3 m- 7 m represent low-rise buildings, and DBM data of more than 18 m reflect high-rise buildings.

Cite this article as:
O. Murao, T. Usuda, H. Gokon, K. Meguro, W. Takeuchi, K. Sugiyasu, and K. Yu, “Understanding Regional Building Characteristics in Yangon Based on Digital Building Model,” J. Disaster Res., Vol.13 No.1, pp. 125-137, 2018.
Data files:
References
  1. [1] O. Murao, K. Meguro, K. T. Yu, T. Matsushita, H. Gokon, T. Usuda, A. Komin, T. Kato, M. Koshihara, and M. Numada, “Consideration of Making Building Vulnerability Maps for Yangon City,” Procs. of the 6th Int. Conf. on Science and Engineering 2015 (USB), 2015.
  2. [2] Bureau of Urban Development, Tokyo Metropolitan Government (TMG), “Your Community’s Earthquake Risk The Seventh Community Earthquake Risk Assessment Study,” 2013.
  3. [3] O. Murao, H. Gokon, K. Meguro, and K. T. Yu, “Tentative Building Vulnerability Assessment of Yangon,” Procs. of the 7th Int. Conf. on Science and Engineering 2016 (USB), 2016.
  4. [4] M. Koarai, H. Sato, H. Une, and K. Amano, “Interpretation of geological hazard using high-resolution optical satellite imagery: Comparison of interpretation characteristics of satellite images,” J. of the Geological Society of Japan, Vol.114, No.12, pp. 632-647, 2008 (in Japanese).
  5. [5] S. Matsuzaki, F. Yamazaki, M. Estrada, and C. Zavala, “Visual Damage Interpretation of Buildings Using QuickBird Images Following the 2007 Peru Earthquake,” the 3rd Asia Conf. on Earthquake Engineering, Bangkok, Thailand, p. 8, 2010.
  6. [6] H. Gokon, S. Koshimura, and K. Meguro, “Verification of a Method for Estimating Building Damage in Extensive Tsunami Affected Areas Using L-Band SAR Data,” J. of Disaster Research, Vol.12, No.2, pp. 251-258, 2017.
  7. [7] Y. Nakaoka and K. Nakao, “The Investigation of the Damage Situation and the Revival Situation of the Great Hanshin Awaji Earthquake disaster by the Analysis of the Satellite Remotely Sensed Image,” Research Memoirs of the Kobe Technical College, Vol.37, pp. 81-86, 1998 (in Japanese).
  8. [8] O. Murao, T. Ichiko, and I. Nakabayashi, “Evaluation of Building Reconstruction Process in Chi-Chi Area based on a GIS-Database after the 1999 Chi-Chi Earthquake, Taiwan,” Procs. of the 13th World Conf. on Earthquake Engineering (CD-ROM), No.174, p. 12, 2004.
  9. [9] O. Murao, T. Hoshi, M. Estrada, K. Sugiyasu, M. Matsuoka, and F. Yamazaki, “Urban Recovery Process in Pisco after the 2007 Peru Earthquake,” J. of Disaster Research, Vol.8, No.2, pp. 356-364, 2013.
  10. [10] T. Hoshi, O. Murao, K. Yoshino, F. Yamazaki, and M. Estrada, “Post-disaster Urban Recovery Monitoring in Pisco after the 2007 Peru Earthquake Using Satellite Image,” J. of Disaster Research, Vol.9, No.6, pp. 1059-1068, 2014.
  11. [11] H. Miura and S. Midorikawa, “Updating GIS Building Inventory Data Using High-resolution Satellite Images for Earthquake Damage Assessment: Application to Metro Manila, Philippines,” Earthquake Spectra, Vol.22, No.1, pp. 151-168, 2006.
  12. [12] I. F. Shaker, A. Abd-Elrahman, A. K. Abdel-Gawad, and M. A. Sherief, “Building Extraction from High Resolution Space Images in High Density Residential Areas in the Great Cairo Region,” Remote Sensing, Vol.3, No.4, pp. 781-791, 2011.
  13. [13] M. Matsuoka, H. Miura, S. Midorikawa, and M. Estrada, “Extraction of Urban Information for Seismic Hazard and Risk Assessment in Lima, Peru Using Satellite Imagery,” J. of Disaster Research, Vol.8, No.2, pp. 328-345, 2013.
  14. [14] T. Sritarapipat and W. Takeuchi, “Estimating Land Value and Disaster Risk in Urban Area in Yangon, Myanmar Using Stereo High-resolution Images and Multi-temporal Landsat Images,” Procs. of 36th Asian conference on remote sensing, 2015.
  15. [15] T. Sritarapipat and W. Takeuchi, “Building Classification in Yangon City, Myanmar Using Stereo GeoEye Images, Landsat Image and Night-time Light Data,” Remote Sensing Applications: Society and Environment, Vol.6, pp. 46-51, 2017.
  16. [16] Japan Int. Cooperation Agency (JICA) and Yangon City Development Committee (YCDC), “The Republic of the Union of Myanmar, A Strategic Urban Development Plan of Greater Yangon, The Project for the Strategic Urban Development Plan of the Greater Yangon,” 2014, open_jicareport.jica.go.jp/pdf/12122511.pdf [accessed October 25, 2015]

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Apr. 05, 2024