• Journal of Korean Society for Geospatial Information Science
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• v.14 no.2 s.36
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• pp.63-68
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• 2006

Although it is more recommended to use satellite images for an accurate understanding of the natural environment over a large area, what should proceed obtaining such satellite images is to make basic model equations based firmly upon the on-land experiments and field experiments. It may be more accurate and objective to investigate correlations between satellite images and actual water quality factors obtained for the same area. Thus, this study was conducted in order to determined which band of Landsat ETM+ images is appropriate to estimate the density of chlorophyll-a in a closed laboratory without atmospheric interference, using pure water and sea water. As a result of this study, it was found that the best band that exhibited the highest degree of correlations among the compounded bands rated (B3-B4)/B2 in pure water and (B2+B4)/B3 in sea water. The correlation coefficient here is 0.9747 and 0.9892 respectively. Thus, compounding this band ran be quite useful for estimation density of Chlorophyll-a using Landsat ETM+ image data.

• Proceedings of the KSRS Conference
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• v.2
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• pp.864-867
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• 2006

Thermal infrared images of Landsat-5 TM and Landsat-7 ETM+ sensors have been unrivalled sources of high resolution thermal remote sensing (60m for ETM+, 120m for TM) for more than two decades. Atmospheric effect that degrades the accuracy of Sea Surface Temperature (SST) measurement significantly, however, can not be corrected as the sensors have only one thermal channel. Recently, MODIS sensor onboard Terra satellite is equipped with dual-thermal channels (31 and 32) of which the difference of at-satellite brightness temperature can provide atmospheric correction with 1km resolution. In this study we corrected the atmospheric effect of Landsat SST by using MODIS data obtained almost simultaneously. As a case study, we produced the Landsat SST near the eastern and western coast of Korea. Then we have obtained Terra/MODIS image of the same area taken approximately 30 minutes later. Atmospheric correction term was calculated by the difference between the MODIS SST (Level 2) and the SST calculated from a single channel (31 of Level 1B). This term with 1km resolution was used for Landsat SST atmospheric correction. Comparison of in situ SST measurements and the corrected Landsat SSTs has shown a significant improvement in $R^2$ from 0.6229 to 0.7779. It is shown that the combination of the high resolution Landsat SST and the Terra/MODIS atmospheric correction can be a routine data production scheme for the thermal remote sensing of ocean.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.717-720
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• 2005

Recently as large sized urban development and the city ward drifting of population are caused, the urban surface temperature is raised very seriously and rapidly. These artificial developments have destroyed the inner and outer landscapes such as topography and have changed complex local climate such as a sudden rise in temperature, the change of wind field and air pollution. In order to clarify this problem visually, the studies on extracting the thermal infrared and the characteristic analysis of local climate in urban area had been performed by using the sixth band of Landsat TM and ETM+. However, there is a need to alternate Landsat TM and ETM+ because these satellite images are not applied any more. Therefore, in this paper it is proposed to use 2 Aster image (2004.4.17 daily 2b03, 2004.10.10 night 2b03) of EOS AM and to extract the surface temperature. Also, the pattern of surface temperature in urban area and the application possibility in local climate study are proposed by verifying the correlation with A WS data. Also, IKONOS image was used to figure out the artificial development area in visual.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2006.05a
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• pp.116-121
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• 2006

광범위한 지역의 자연환경 정보를 파악하기 위하여 위성 영상자료를 이용하는 것이 적합하지만 선행되어야 할 것은 이러한 위성영상자료를 이용하기 위한 지상에서의 내부 실험과 현장실험을 통한 기초적인 모델식을 만드는 것이 중요하다. 이를 위하여 위성영상자료와 실측수질인자들의 상관관계를 조사하는 것이 보다 정확하고 객관적인 평가 방법이 될 수 있다. 따라서 대기의 영향이 없는 실험실내에서 순수한 담수와 해수를 이용하여 Landsat ETM 영상자료의 어느 밴드가 클로로필a 농도파악에 적합한가를 평가하고자 하였다. 그 결과 밴드조합 중 가장 높은 상관관계를 보인 최적밴드는 담수에서 (83-B4)/B2이고, 해수에서는 (82+B4)/B3로 이 때의 상관계수가 각각 0.9747, 0.9892이므로 향후 이 밴드를 조합하여 위성영상 평가 시 사용하는 것이 유효할 것으로 생각된다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2B
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• pp.187-197
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• 2008

This study is to assess the impact of future land use change on hydrology and water quality in Gyungan-cheon watershed ($255.44km^2$) using SWAT (Soil and Water Assessment Tool) model. Using the 5 past Landsat TM (1987, 1991, 1996, 2004) and $ETM^+$ (2001) satellite images, time series of land use map were prepared, and the future land uses (2030, 2060, 2090) were predicted using CA-Markov technique. The 4 years streamflow and water quality data (SS, T-N, T-P) and DEM (Digital Elevation Model), stream network, and soil information (1:25,000) were prepared. The model was calibrated for 2 years (1999 and 2000), and verified for 2 years (2001 and 2002) with averaged Nash and Sutcliffe model efficiency of 0.59 for streamflow and determination coefficient of 0.88, 0.72, 0.68 for Sediment, T-N (Total Nitrogen), T-P (Total Phosphorous) respectively. The 2030, 2060 and 2090 future prediction based on 2004 values showed that the total runoff increased 1.4%, 2.0% and 2.7% for 0.6, 0.8 and 1.1 increase of watershed averaged CN value. For the future Sediment, T-N and T-P based on 2004 values, 51.4%, 5.0% and 11.7% increase in 2030, 70.5%, 8.5% and 16.7% increase in 2060, and 74.9%, 10.9% and 19.9% increase in 2090.

• Journal of the Korean Institute of Landscape Architecture
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• v.43 no.3
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• pp.101-113
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• 2015

The purpose of this study is increasing ventilation network usability for urban green space planning by enhancing its practicality and detail. A ventilation network feature extraction technique using roughness length($z_0$) was proposed. Continuously surfaced DZoMs generated from $z_0$(cadastral unit) using three interpolations(IDW, Spline, and Kriging) were compared to choose the most suitable interpolation method. Ventilation network features were extracted using the most suitable interpolation technique and studied with land cover and land surface temperature by spatial overlay comparison. Results show Kriging is most suitable for DZoM and feature extraction in comparison with IDW and Spline. Kriging based features are well fit to the land surface temperature(Landsat-7 ETM+) on summer and winter nights. Noteworthy is that the produced ventilation network appears to mitigate urban heat loads at night. The practical use of proposed ventilation network features are highly expected for urban green space planning, though strict validation and enhancement should follow. (1) $z_0$ enhancement, (2) additional ventilation network interpretation and editing, (3) linking disconnected ventilation network features, and (4) associated dataset enhancement with data integrity should technically preceded to enhance the applicability of a ventilation network for green space planning. The study domain will be expanded to the Seoul metropolitan area to apply the proposed ventilation network to green space planning practice.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2B
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• pp.215-224
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• 2008

The effect of streamflow considering future land use change and vegetation index information by climate change scenario was assessed using SLURP (Semi-distributed Land-Use Runoff Process) model. The model was calibrated and verified using 4 years (1999-2002) daily observed streamflow data for the upstream watershed ($260.4km^2$) of Gyeongan water level gauging station. By applying CA-Markov technique, the future land uses (2030, 2060, 2090) were predicted after test the comparison of 2004 Landsat land use and 2004 CA-Markov land use by 1996 and 2000 land use data. The future land use showed a tendency that the forest and paddy decreased while urban, grassland and bareground increased. The future vegetation indices (2030, 2060, 2090) were estimated by the equation of linear regression between monthly NDVI of NOAA AVHRR images and monthly mean temperature of 5 years (1998-2002). Using CCCma CGCM2 simulation result based on SRES A2 and B2 scenario (2030s, 2060s, 2090s) of IPCC and data were downscaled by Stochastic Spatio-Temporal Random Cascade Model (SST-RCM) technique, the model showed that the future runoff ratio was predicted from 13% to 34% while the runoff ratio of 1999-2002 was 59%. On the other hand, the impact on runoff ratio by land use change showed about 0.1% to 1% increase.