Understanding regional building characteristics in yangon based on digital building model

Osamu Murao, Takuma Usuda, Hideomi Gokon, Kimiro Meguro, Wataru Takeuchi, Kazuya Sugiyasu, Khin Than Yu

Research output: Contribution to journalComment/debate

1 Citation (Scopus)


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.

Original languageEnglish
Pages (from-to)125-137
Number of pages13
JournalJournal of Disaster Research
Issue number1
Publication statusPublished - 2018 Feb


  • Building collapse risk
  • DBM
  • Myanmar
  • Remote sensing
  • Urban vulnerability


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