A DATA INTEGRATION FRAMEWORK FOR URBAN AREA DISASTER SIMULATIONS

Abstract eng:
In order to make a practical disaster assessment based on simulations, we need detailed urban models, which include all individual buildings in a target city. However, the quantity and quality of single raw data sources for buildings are limited. Thus we need to construct the detailed urban model from multiple data sources. To make urban modeling automatic and efficient, we have developed a framework which can extract important information from fragmented heterogeneous data sources, integrate multiple data sets and make input models for disaster simulations. Utilizing the framework, we have developed an urban model with all individual buildings of Kobe city in Japan, from various data sources such as 3D building shapes and the official building inventory. Using the model as input, we have performed a large-scale simulation to make an assessment of building damages caused by earthquake. It is verified that the framework can make urban modeling automatic and efficient.

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