• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.556-559
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• 2007

The Urban Environmental Quality (UEQ) indicates a complex and various parameters resulting from both human and natural factors in an urban area. Vegetation, climate, air quality, and the urban infrastructure may interact to produce effects in an urban area. There are relationships among air pollution, vegetation, and degrading environmental the urban heat island (UHI) effect. This study investigates the application of multi-spectral remote sensing data from the Landsat ETM and TM sensors for the mapping of air quality and UHI intensity in Seoul from 2000 to 2006 in fine resolution (30m) using the emissivity-fusion method. The Haze Optimized Transform (HOT) correction approach has been adopted for atmospheric correction on all bands except thermal band. The general UHI values (${\Delta}(T_{urban}-T_{rural})$) are 8.45 (2000), 9.14 (2001), 8.61 (2002), and $8.41^{\circ}C$ (2006), respectively. Although the UHI values are similar during these years, the spatial coverage of "hot" surface temperature (>$24^{\circ}C$) significantly increased from 2000 to 2006 due to the rapid urban development. Furthermore, high correlations between vegetation index and land surface temperature were achieved with a correlation coefficients of 0.85 (2000), 0.81 (2001), 0.84(2002), and 0.89 (2006), respectively. Air quality is shown to be an important factor in the spatial variation of UEQ. Based on the quantifiable fine resolution satellite image parameters, UEQ can promote the understanding of the complex and dynamic factors controlling urban environment.

• Korea Science and Art Forum
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• v.27
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• pp.101-114
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• 2017

Based on the relationship between urban public space, urban lighting and the sense of place, this paper aims to analyze the lighting environment types with the sense of place and their characteristics. First, with the theory study as the research foundation, it extracts six spatial factors of public space lighting design and then analyzes 12 relevant cases on the basis. Finally, it divides the 12 cases into four types, Basic types, Storytelling, Interactive and Multi-Media and analyzes the core design factor and characteristics of various types. The results show that: first, functionality, sustainability and aesthetics are the basic factors to realize the urban public space lighting places. Second, the six cases of "Storytelling" show that the theme of specific areas, namely the exploration of "story" is conducive for lighting design to form clear and definite environment recognition. Third, for "Interactive" and "Multi-Media", the intervention of new media technology and new lighting way has made the wide expansion of urban lighting design connotation and extension. The research results show that strengthening the urban location performance by the lighting design could improve the city image, which provides the basis for the development of urban public space lighting design.

• Journal of Korean Society for Atmospheric Environment
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• v.33 no.5
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• pp.497-514
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• 2017

This study quantitatively analyzes the effects of emission inventory choices on the simulated particulate matter (PM) concentrations and the domestic/foreign contributions in the Seoul Metropolitan Area (SMA) with an air quality forecasting system. The forecasting system is composed of Weather Research and Forecasting (WRF)-Sparse Matrix Operator Kernel Emissions (SMOKE)-Community Multi-Scale Air Quality (CMAQ). Different domestic and foreign emission inventories were selectively adopted to set up four sets of emissions inputs for air quality simulations in this study. All modeling cases showed that model performance statistics satisfied the criteria levels (correlation coefficient >0.7, fractional error <50%) suggested by previous studies. Notwithstanding the apparently good model performance of total PM concentrations by all emission cases, annual average concentrations of simulated total PM concentrations varied up to $20{\mu}g/m^3$ (160%) depending on the combination of emission inventories. In detail, the difference in simulated annual average concentrations of the primary PM coarse (PMC) was up to $25.2{\mu}g/m^3$ (6.5 times) compared with other cases. Furthermore, model performance analyses on PM species showed that the difference in the simulated primary PMC led to gross model overestimation in general, which indicates that the primary PMC emissions need to be improved. The contribution analysis using model direct outputs indicated that the domestic contributions to the annual average PM concentrations in the SMA vary from 44% to 67%. To account for the uncertainty of the simulated concentration, the contribution correction factor method proposed by Bae et al. (2017) was applied, which resulted in converged contributions(from 48% to 57%). We believe this study shows that it is necessary to improve the simulated concentrations of PM components in order to enhance the accuracy of the forecasting model. It is deemed that these improvements will provide more accurate contribution results.