• Fire Science and Engineering
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• v.23 no.6
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• pp.116-125
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• 2009

This study is progressed function ratio, it's trued taste by an experiment to present data for human work light weight aggregate development that use clink ash progressed liquid limit, small success limit, wear loss in quantity, sand equivalent, sieve cutting examination. 80 : 20's match of function rain examination is 1.4, and that use rubble Goljae as ckink ash lightweight aggregate's capacity ratio increases by 1.0 increase of function rain many. Also, examination multiplied delicate flavor gradually according to increase of the mixing rate, and absorption coefficient increased. This is judged by phenomenon that appear by special quality upper clink ash of polystyrene bid and porosity's increase between lightweight aggregate. It is case that use aggregate of wear loss in quantity is 13.5 in sand equivalent and a wear loss in quantity experiment and although case that mix 20% increases by 14.4, this phenomenon by weak tissue of lightweight aggergate be judge. When it's as a these experiment, the statue prevention floor of a street improvement specifications is prescribing so that satisfy by sand equivalent 20, CBR 10. This is showed result that this satisfies in quality standard all in match experiment ago that see.

• Korean Journal of Remote Sensing
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• v.30 no.1
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• pp.109-126
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• 2014

We improved the Land Surface Emissivity (LSE) data (Kongju National University LSE v.2: KNULSE_v2) over the Communication, Ocean and Meteorological Satellite (COMS) observation region using recent(2009-2012) Moderate Resolution Imaging Spectroradiometer (MODIS) data. The surface emissivity was derived using the Vegetation Cover Method (VCM) based on the assumption that the pixel is only composed of ground and vegetation. The main issues addressed in this study are as follows: 1) the impacts of snow cover are included using Normalized Difference Snow Index (NDSI) data, 2) the number of channels is extended from two (11, 12 ${\mu}m$) to four channels (3.7, 8.7, 11, 12 ${\mu}m$), 3) the land cover map data is also updated using the optimized remapping of the five state-of-the-art land cover maps, and 4) the latest look-up table for the emissivity of land surface according to the land cover is used. The updated emissivity data showed a strong seasonal variation with high and low values for the summer and winter, respectively. However, the surface emissivity over the desert or evergreen tree areas showed a relatively weak seasonal variation irrespective of the channels. The snow cover generally increases the emissivity of 3.7, 8.7, and 11 ${\mu}m$ but decreases that of 12 ${\mu}m$. As the results show, the pattern correlation between the updated emissivity data and the MODIS LSE data is clearly increased for the winter season, in particular, the 11 ${\mu}m$. However, the differences between the two emissivity data are slightly increased with a maximum increase in the 3.7 ${\mu}m$. The emissivity data updated in this study can be used for the improvement of accuracy of land surface temperature derived from the infrared channel data of COMS.