• Journal of Environmental Impact Assessment
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• v.25 no.6
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• pp.514-524
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• 2016

The Bio-Climatic impact Assessment System, BioCAS was utilized to produce analysis maps of daily maximum perceived temperature ($PT_{max}$) and excess mortality ($r_{EM}$) over the entire Seoul area on a heat wave event. The spatial resolution was 25 m and the Aug. 5, 2012 was the selected heat event date. The analyzed results were evaluated by comparing with observed health impact data - mortality and morbidity - during heat waves in 2004-2013 and 2006-2011,respectively. They were aggregated for 25 districts in Seoul. Spatial resolution of the comparison was equalized to district to match the lower data resolution of mortality and morbidity. Spatial maximum, minimum, average, and total of $PT_{max}$ and $r_{EM}$ were generated and correlated to the health impact data of mortality and morbidity. Correlation results show that the spatial averages of $PT_{max}$ and $r_{EM}$ were not able to explain the observed health impact. Instead, spatial minimum and maximum of $PT_{max}$ were correlated with mortality (r=0.53) and morbidity (r=0.42),respectively. Spatial maximum of $PT_{max}$, determined by building density, affected increasing morbidity at daytime by heat-related diseases such as sunstroke, whereas spatial minimum, determined by vegetation, affected decreasing mortality at nighttime by reducing heat stress. On the other hand, spatial maximum of $r_{EM}$ was correlated with morbidity (r=0.52) but not with mortality. It may have been affected by the limit of district-level irregularity such as difference in base-line heat vulnerability due to the age structure of the population. Areal distribution of the heat impact by local building and vegetation, such as spatial maximum and minimum, was more important than spatial mean. Such high resolution analyses are able to produce quantitative results in health impact and can also be used for economic analyses of localized urban development.

• Land and Housing Review
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• v.2 no.4
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• pp.559-568
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• 2011

This study aims at listing up those manufacturing activities sensitive to regional characteristics by analyzing locational hierarchy designed on the urban rank-size rule. This locational hierarchy by manufacturing activities is expected to provide a ground for the proper supply of an industrial complex. The analysis of the locational hierarchy by manufacturing activities can work as a method of observing the characteristics of the distribution of location for each economic activity by analyzing the trend in the change of manufacturing location. Consequently, it can be used to determine the appropriate manufacturing activities for the industrial complex of a particular region. Here, the locational hierarchy is analyzed depending on the base of the basic local government such as Gun(district level) and Si(city level), and manufacturing activities are categorized by Korea Standard Industry Code. Those activities demonstrating growth pattern are Manufacture of Electronic Equipment(KSIC 26), Manufacture of Medical Precision Optical Instruments Watch(KSIC 27), Manufacture of Motor Vehicles (KSIC 30, 31), etc. With proper infrastructures, these activities can be located everywhere. Those sectors on the decline pattern in the locational hierarchy can be summarized as Manufacture of Tobacco Products(KSIC 12), Manufacture of wearing apparel Fur Articles(KSIC 14), etc. Those sectors scattered widely in the locational hierarchy are Manufacture of Food Products(KSIC 10), Manufacture of Coke Petroleum Products(KSIC 19), Manufacture of Chemical Products(KSIC 20), Manufacture of Electronic Equipment(KSIC 26). These particular manufacturing activities can be operated in those regions in a sufficient supply of unskilled workers regardless of proper infrastructures. Those activities that have a tendency to reconcentrate on larger cities are Manufacture of Textiles(KSIC 13), Manufacture of Wearing Apparel Clothing Fur Articles(KSIC 14), Manufacture of Other Transport Equiptmen(KSIC 31). In most cases, these sectors tend to favor their existing agglomerated areas and concentrate around large cities. Therefore, it is inefficient to promote these sectors in small or medium-sized cities or underdeveloped regions. The establishment of developmental strategies of an industrial complex can gain greater competitiveness by observing such characteristics of the locational hierarchy.