• 한국태양에너지학회:학술대회논문집
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• 2008.11a
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• pp.69-74
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• 2008

This study is to analyze and compare on the sky condition of cloud amount and measured solar horizontal irradiation in Seoul. Sky cover method is determination of sky condition used by cloud amount of the Meteorological Administration. And HCI method is determination of sky condition used by measured solar horizontal irradiation. The HCI methods of Erbs et al.(1982), Orgill and Hollands(1977) appear a lot of error because of the air pollution such as smog phenomenon or yellow sand phenomenon and so on. Therefore, The purpose of this study is to improve the method for determination of sky condition.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.1
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• pp.19-27
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• 2010

Sky cover method can be used to determine sky condition by cloud amount of the Korea Meteorological Administration. And, HCI (Hourly Clearness Index) method is another method determined by measured horizontal global radiation data. The results of the HCI methods of Erbs et al. (1982), Orgill and Hollands (1977) seem to be not good enough because of the air pollution such as smog phenomenon or yellow sand phenomenon and so on. Therefore, HCI should be corrected. The aim of this study is to improve HCI. Therefore, this study is to analyze and compare on the sky conditions from Sky cover method and HCI, and then presents hourly correction factor based on Sky 채팩 method. The results of corrected HCI improved.

• Atmosphere
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• v.27 no.4
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• pp.483-498
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• 2017

Sky view factor can quantify the influence of complex obstructions. This study aims to evaluate the best available SVF method that represents an urban thermal condition with land cover in complex city of Korea and also to quantify a correlation between SVF and mean air temperature; the results are as follows. First, three SVF methods comparison result shows that urban thermal study should consider forest canopy induced effects because the forest canopy test (on/off) on SVF reveals significant difference range (0.8, between maximum value and minimum value) in comparison with the range (0.1~0.3) of SVFs (Fisheye, SOLWEIG and 3DPC) difference. The significance is bigger as a forest cover proportion become larger. Second, R-square between SVF methods and urban local mean air temperature seems more reliable at night than a day. And as the value of SVF increased, it showed a positive slope in summer day and a negative slope in winter night. In the SVF calculation method, Fisheye SVF, which is the observed value, is close to the 3DPC SVF, but the grid-based SWG SVF is higher in correlation with the temperature. However, both urban climate monitoring and model/analysis study need more development because of the different between SVF and mean air temperature correlation results in the summer night period, which imply other major factors such as cooling air by the forest canopy, warming air by anthropogenic heat emitted from fuel oil combustion and so forth.

• Atmosphere
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• v.28 no.3
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• pp.317-324
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• 2018

In this study, we review the ground-based whole-sky camera (WSC), which is developed to continuously capture day and night cloud images using the illumination data from a precision Lightmeter with a high temporal resolution. The WSC is combined with a precision Lightmeter developed in IYA (International Year of Astronomy) for analysis of an artificial light pollution at night and a DSLR camera equipped with a fish-eye lens widely applied in observational astronomy. The WSC is designed to adjust the shutter speed and ISO of the equipped camera according to illumination data in order to stably capture cloud images. And Raspberry Pi is applied to control automatically the related process of taking cloud and sky images every minute under various conditions depending on illumination data from Lightmeter for 24 hours. In addition, it is utilized to post-process and store the cloud images and to upload the data to web page in real time. Finally, we check the technical possibility of the method to observe the cloud distribution (cover, type, height) quantitatively and objectively by the optical system, through analysis of the captured cloud images from the developed device.

• Korean Journal of Remote Sensing
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• v.25 no.2
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• pp.193-203
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• 2009

Snow cover is one of the important parameters since it determines surface energy balance and its variation. To classify snow and cloud from satellite data is very important process when inferring land surface information. Generally, misclassified cloud and snow pixel can lead directly to error factor for retrieval of surface products from satellite data. Therefore, in this study, we perform algorithm for detecting snow cover area with remote sensing data. We just utilize visible reflectance, and infrared channels rather than using NDSI (Normalized Difference Snow Index) which is one of optimized methods to detect snow cover. Because COMS MI (Meteorological Imager) channels doesn't include near infra-red, which is used to produce NDSI. Detecting snow cover with visible channel is well performed over clear sky area, but it is difficult to discriminate snow cover from mixed cloudy pixels. To improve those detecting abilities, brightness temperature difference (BTD) between 11 and 3.7 is used for snow detection. BTD method shows improved results than using only visible channel.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1385-1394
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• 2022

This study was to analyze the change in albedo by level-2 land cover map for 20 years(2002-2021) using MODerate resolution Imaging Spectroradiometer (MODIS) data. Also, the difference from the MODIS data was analyzed using the 10-year (2012-2021) data of Visible Infrared Imaging Radiometer Suite (VIIRS). For the albedo data of MODIS and VIIRS, daily albedo data, MCD43A3 and VNP43IA, of 500 m spatial resolution of sinusoidal tile grid produced by Bidirectional Reflectance Distribution Function (BRDF) model were prepared for the South Korea range. Reprojection was performed using the code written based on Python 3.9, and the nearest neighbor was applied as the resampling method. White sky albedo and black sky albedo of shortwave were used for analysis. As a result of 20-year albedo analysis using MODIS data, the albedo tends to rise in all land use. Compared to the 2000s (2002-2011), the average albedo of the 2010s (2012-2021) showed the most significant increase of 0.0027 in the forest area, followed by the grass increase of 0.0024. As a result of comparing the albedo of VIIRS and MODIS, it was found that the albedo of VIIRS was larger from 0.001 to 0.1, which was considered to be due to differences in the surface reflectivity according to the time of image capture and sensor characteristics.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.1
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• pp.19-26
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• 2017

Surface air temperature ($T_{air}$) is a key variable for the meteorology and climatology, and is a fundamental factor of the terrestrial ecosystem functions. Satellite remote sensing from the Moderate Resolution Imaging Spectroradiometer (MODIS) provides an opportunity to monitor the $T_{air}$. However, the several problems such as frequent cloud cover and mountainous region can result in substantial retrieval error and signal loss in MODIS $T_{air}$. In this study, satellite-based $T_{air}$ was estimated under both clear and cloudy sky conditions in Gangwon Province using Aqua MODIS07 temperature profile product (MYD07_L2) and GCOM-W1 Advanced Microwave Scanning Radiometer 2 (AMSR2) brightness temperature ($T_b$) at 37 GHz frequency, and was compared with the measurements from the Automated Mountain Meteorology Stations (AMOS). The application of ambient temperature lapse rate was performed to improve the retrieval accuracy in mountainous region, which showed the improvement of estimation accuracy approximately 4% of RMSE. A simple pixel-wise regression method combining synergetic information from MYD07_L2 $T_{air}$ and AMSR2 $T_b$ was applied to estimate surface $T_{air}$ for all sky conditions. The $T_{air}$ retrievals showed favorable agreement in comparison with AMOS data (r=0.80, RMSE=7.9K), though the underestimation was appeared in winter season. Substantial $T_{air}$ retrievals were estimated 61.4% (n=2,657) for cloudy sky conditions. The results presented in this study indicate that the satellite remote sensing can produce the surface $T_{air}$ at the complex mountainous region for all sky conditions.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.26-49
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• 2018

The purpose of this study was to verify the reliability of the solar radiation model and discuss its applicability to the urban area of Seoul for summer heat stress mitigation. We extended the study area closer to the city scale and enhanced the spatial resolution sufficiently to determine pedestrian-level urban radiance. The domain was a $4km^2$ residential area with high-rise building sites. Radiance modelling (SOLWEIG) was performed with LiDAR (Light Detection and Ranging)-based detailed geomorphological land cover shape. The radiance model was evaluated using surface energy balance (SEB) observations. The model showed the highest accuracy on a clear day in summer. When the mean radiation temperature (MRT) was simulated, the highest value was for a low-rise building area and road surface with a low shadow effect. On the other hand, for high-rise buildings and vegetated areas, the effect of shadows was large and showed a relatively low value of mean radiation temperature. The method proposed in this study exhibits high reliability for the management of heat stress in urban areas at pedestrian height. It is applicable for many urban micro-climate management functions related to natural and artificial urban settings; for example, when a new urban infrastructure is planned.