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http://dx.doi.org/10.11108/kagis.2017.20.2.032

Development of Estimation Method for Velocity Pressure Exposure Coefficient of Buildings Based on Spatial Information  

SEO, Eun-Su (Department of Spatial Information, Kyungpook National University)
CHOI, Se-Hyu (School of Architecture and Civil Engineering, Kyungpook National University)
Publication Information
Journal of the Korean Association of Geographic Information Studies / v.20, no.2, 2017 , pp. 32-46 More about this Journal
Abstract
Recent rapid urban expansion and crowding of various industrial facilities has affected the features of a significant part of downtown area, resulting in areas having buildings with a wide range of height and the foothills. To compute a velocity pressure exposure coefficient, namely the design wind speed factor, this study defines ground surface roughness by utilizing concentration analysis for the height of each building. After obtaining spatial data by extracting a building layer from digital maps, the study area was partitioned for the concentration analysis and to allow investigation of the frequency distribution of building heights. Concentration analysis by building height was determined with the Variation-to-Means Ratio (VMR) and Poisson distribution analysis using a buildings distribution chart, with statistical significance determined using Chi-square verification. Applying geographic information systems (GIS) with the architectural information made it possible to estimate a velocity pressure exposure coefficient factor more quantitatively and objectively, by including geographic features, as compared to current methods. Thus, this method is expected to eliminate inaccuracies that arise when building designers calculate the velocity pressure exposure coefficient in subjective way, and to help increase the wind resistance of buildings in a more logical and cost-effective way.
Keywords
Velocity Pressure Exposure Coefficient; Surface Roughness; Density; Poisson Distribution; Geographic Information System;
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Times Cited By KSCI : 5  (Citation Analysis)
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