• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.149-152
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• 2007

The detection of yellow sand dust using satellite has been utilized from various bands from ultraviolet to infrared channels. Among them, Infrared channels have an advantage of detecting aerosols over high reflecting surface as well as during nighttime. Especially, brightness temperature difference between 11 and 12{\mu}m(BTD) was often used to distinguish between water cloud and yellow sand, because Ice and liquid water particles preferentially absorb longer wavelengths while aerosol particles preferentially absorb shorter wavelengths. We have found that the BTD significantly depends on surface temperature, emissivity, and zenith angle and thereby the threshold of BTD. In order to overcome these problems, we have constructed the background brightness temperature threshold of BTD and then subtracted it from BTD. Along with this, we utilized high temporal coverage of geostationary satellite, MTSAT-1R, to verify the reliability of the retrieved signal in conjunction with forecasted wind information. The statistical score test illustrated that this newly developed algorithm showed a promising result for detecting mineral dust by reducing the errors in the current BTD method.

• 보존과학연구
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• s.31
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• pp.59-68
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• 2010

Cultural heritages are damaged by surrounding several environmental factors. Main factors are temperature, humidity, light, atmosphere and indoor pollutant, organism, etc. Therefore, to prevent damage of cultural heritage from such environmental factor, conservation environment monitoring becomes more important. Indicator is one of the simple method for environment monitoring. It can be used without expensive and complex equipments. However, it should be performed scientific examination for application to cultural heritage. In this study, some Temperature Indicators were chosen and reliability assessment was carried out for application to cultural heritage. Brightness($L^*$) is selected for reliability assessment factor. As a result of lab test, Temperature Indicators were not influenced greatly in humidity change. When they were exposed to setting temperature, the color was changed in setting temperature area and ${\pm}2^{\circ}C$ part of setting temperature. Especially brightness value was high in setting temperature area. Also, Temperature Indicators were stabilized after about 16 minutes when were exposed to temperature difference of $10^{\circ}C$ and when temperature difference with exposure environment is smaller, stabilization time shortened. Therefore, it is a possible to confirm that selected Temperature Indicator is reliable product through measurement of color difference value and naked eye observation.

• Proceedings of the KSRS Conference
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• v.2
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• pp.794-796
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• 2006

This study investigated the Brightness Temperature Difference threshold as criterion between aerosols and clouds in conjunction with radiative transfer model. Surface temperature is caused by a significant error over 50% in the BTD threshold. In addition, The BTD threshold contains the uncertainties about 20% due to the surface emissivity and 8% due to the satellite zenith angle. Therefore, we have composed the Look-up table for BTD between 11㎛and 12㎛ according to satellite zenith angle, surface temperature, and surface emissivity. The modified BTD show the enhanced signal, especially over bright surface such as desert in China. However, a weak aerosol signal over Ocean remains in the modified BTD.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.370-373
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• 2005

We have developed Hybrid algorithm for yellow sand detection. Hybrid algorithm is composed of three methods using infrared bands. The first method used the differential absorption in brightness temperature difference between $11\mu m\;and\;12\mu m$ (BID _1), through which help distinguish the yellow sand from various meteorological clouds. The second method uses the brightness temperature difference between $3.7\mu m\;and\;11\mu m$ (BID_2). The technique would be most sensitive to dust loading during the day when the BID _2 is enhanced by reflection of $3.7\mu m$ solar radiation. The third one is a newly developed algorithm from our research, the so-called surface temperature variation method (STY). We have applied the three methods to MODIS for derivation of the yellow sand dust and in conjunction with the Principle Component Analysis (PCA), a form of eigenvector statistical analysis. PCI shows better results for yellow sand detection in comparison with the results from individual method. The comparison between PCI and MODIS aerosols optical depth (AOD) shows remarkable good correlations during daytime and relatively good correlations over the land.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.403-406
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• 2006

An algorithm for detection of yellow sand aerosols has been developed with infrared bands. This algorithm is a hybrid algorithm that has used two methods combined. The first method used the differential absorption in brightness temperature difference between $11{\mu}m\;and\;12{\mu}m\;(BTD1)$. The radiation at $11{\mu}m$ is absorbed more than at $12{\mu}m$ when yellow sand is loaded in the atmosphere, whereas it will be the other way around when cloud is present. The second method uses the brightness temperature difference between $3.7{\mu}m\;and\;11{\mu}m(BTD2)$. This technique is sensitive to dust loading, which the BTD2 is enhanced by reflection of $3.7{\mu}m$ solar radiation. First the Principle Component Analysis (PCA), a form of eigenvector statistical analysis from the two methods, is performed and the aerosol pixel with the lowest 10% of the eigenvalue is eliminated. Then the aerosol index (AI) from the combination of BTD 1 and 2 is derived. We applied this method to Multi-functional Transport Satellite-l Replacement (MTSAT-1R) data and obtained that the derived AI showed remarkably good agreements with Ozone Mapping Instrument (OMI) AI and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.282-285
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• 2007

Satellite observed brightness temperature simulation using a radiative transfer model (here after, RTM) is useful for various fields, for example sensor design and channel selection by using theoretically calculated radiance data, development of satellite data processing algorithm and algorithm parameter determination before launch. This study is focused on elaborating the simulation procedure, and analyzing of difference between observed and modelled clear sky brightness temperatures. For the CMDPS (COMS Meteorological Data Processing System) development, the simulated clear sky brightness temperatures are used to determine whether the corresponding pixels are cloud-contaminated in cloud mask algorithm as a reference data. Also it provides important information for calibrating satellite observed radiances. Meanwhile, simulated brightness temperatures of COMS channels plan to be used for assessing the CMDPS performance test. For these applications, the RTM requires fast calculation and high accuracy. The simulated clear sky brightness temperatures are compared with those of MTSAT-1R observation to assess the model performance and the quality of the observation. The results show that there is good agreement in the ocean mostly, while in the land disagreement is partially found due to surface characteristics such as land surface temperature, surface vegetation, terrain effect, and so on.

• Korean Journal of Remote Sensing
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• v.20 no.1
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• pp.47-55
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• 2004

We have constructed a level-1 processor to generate brightness temperatures using the direct-broadcast data from the passive microwave radiometer onboard Aqua satellite. Although 50-minute half-orbit data, called a granule, are being routinely produced by global data centers, to our knowledge, this is the first attempt to process 10-minute long direct-broadcast (DB) data. We found that the processor designed for a granule needs modification to apply to the DB data. The modification includes the correction to path number, the selection of land mask and the manipulation of dummy scans. Pixel-to-pixel comparison with a reference indicates the difference in brightness temperature of about 0.2 K rms and less than 0.05 K mean. The difference comes from the different length of data between 50-minute granule and about 10-minute DB data. In detail, due to the short data length, DB data do not always have correct cold sky mirror count. The DB processing system is automated to enable the near-real time generation of brightness temperatures within 5 minutes after downlink. Through this work, we would be able to enhance the use of AMSR-E data, thus serving the objective of direct-broadcast.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1997.11a
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• pp.140-145
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• 1997

A stuey to investigate the perception characteristics of color and brightness was conducted in a combined PC and TV monitor, The objective of this study is to suggest user's favorite color temperature in PC mode and user's favorite contrast in TV mode. Investigated factors were monitor coating(coatiog vs. non-coation)and screen brightness (30fL vs. 35fL)in first experiment and monitor coating and pucture movement(static vs. dynamic) in second experiment. The first experiment was conducted in TV mode. Twenty-three subjects (male 12, female 11) perticipated in this experiment. In first experiment, average color temperatures were about 8000K in all experimental conditions. In addition, there was significant difference between coating and non-coating screen at 0.1 level. In second experiment, average contrasts were obtained in all esperimental conditions. There was significant difference between coating and ndn-coating screen at 0.05 level, In addition, there was significant difference between static picture and dynamic picture at 0.1 level

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.462-467
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• 1999

In this paper, very high performance millimeter-wave radiometer of 92 GHz is presented. Radiometer system design, brightness temperature measurement and calibration methods are described. The architecture of radiometer including data acquisition, storage and digital signal processing using a notebook computer are explained and some experimental data in the laboratory are introduced. The system noise figure and total gain of implemented radiometer are 12 dB and 56 dB, respectively. The system stability is evaluated from the experiment. The difference of the detector output voltage for two targets, whose brightness temperature are 80 K and 300K, is 4 mV. The mechanical scanning method is considered to get a brightness temperature Image of the earth surface scene.

• Journal of the Korean Society of Industry Convergence
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• v.15 no.3
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• pp.87-94
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• 2012

Kruithof demonstrated the preferred combination of illuminance levels and color temperatures. However, as Benett pointed out, difference of themal variables in such preference may be expected. The purpose of this study is to clarify the combined effects of lighting conditions(illuminance, color temperature), operative temperature on the human physiological and psychological responses. In order to observe operative temperature change in preference of color temperatures for three illumination levels, three subjects were exposed to two different conditions of color temperatures of 2,850K, 4,200K and 6,850K combined with operative temperatures(OT) of $25{\sim}31^{\circ}C$ at 100~1000lx. Thermal sensation vote and comfortable sensation vote, brightness perception vote were reported in each experiment conditions. The following results were obtained : 1) When illuminace level was at 100lx in operative temperatures of OT $20^{\circ}C$, $25^{\circ}C$, $30^{\circ}C$, Color temperature affect not themal sensation but Warm-cool sensation. 2) Operative temperatures affect not brightness perception vote but visual comfort sensation vote, satisfactive sensation vote, warm-cool sensation vote and themal sensation vote.