• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.3
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• pp.535-542
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• 1994

Remote sensing technique is based on the estimation of land surface characteristics from the measurement of the emitted radiation from the earth. The hydrologically related parameters studied using this approach include surface temperature, evapotranspiration, soil moisture, precipitation and snow. This study introduces a method for estimating moisture content of a bare soil from the observed and simulated brightness temperature. In a bare soil, microwave emission depends on moisture content, soil temperature, and surface roughness. The method is based on a radiative transfer model with some modifications of Fresnel reflection coefficient to take into account the effect of surface roughness. One smooth bare field and two fields with different surface roughness are prepared for the study. The results indicate that the effect of surface roughness is to increase the soil's brightness temperature and to reduce the slope of regression between brightness temperature and moisture contents.

• 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.11 no.1
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• pp.31-45
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• 1995

The values of brightness temperature difference (BTD) between 11um and 12um infrared channels may reflect amounts of low-level water vapor and cloud types due to the different absorptivity for water vapor between two channels. A simple method of classifying cloud types at night was proposed. Two-dimensional histograms of brightness temperature of the 11um channel and the BTD between the split window data over subareas around characteristic clouds such as Cb(cumulonimbus), Ci(cirrus), and Sc(stratocumulus) was constructed. Cb, Ci and Sc can be classified by seleting appropriate thresholds in the two-dimensional histograms. And we can see amounts of low-level water vapor in clear area as well as cloud types in cloudy area in the BTD image. The map of cloud types and low-level water vapor generated by this method was compared with 850hPa and 1000hPa relative humidity(%) of numerical analysis data and nephanalysis chart. The comparisons showed reasonable agreement.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2010.06a
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• pp.9-9
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• 2010

In this paper, High Brightness LED driver IC using new current sensing circuit is proposed. This LED driver IC can provide a constant current with high current precision over a wide input voltage range. The proposed current-sensing circuit is composed of a cascode current sensor and a current comparator with only one reference voltage. This IC minimizes the voltage stress of the MOSFET from the maximum input voltage and has low power consumption and chip area by using simple-structured comparator and minimum bias current. The LED current ripple of the designed IC is in ${\pm}5%$ and a tolerance of the average LED current is lower than 2.43%. This shows much improved feature than the previous method. Also, protections for input voltage and operating temperature are designed to improve the reliability of the designed IC. Designed LED driver IC uses $1{\mu}m$ X-Fab. BiCMOS process parameters and electrical characteristics and functioning are verified by spectre(Cadence) simulation.

• Korean Journal of Remote Sensing
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• v.28 no.2
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• pp.181-189
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• 2012

Recently, interest in potential for estimating water quality using high resolution satellite images is increasing. However, low SNR(Signal to Noise Ratio) over inland water and radiometric errors such as non-linearity of brightness value of high resolution satellite images often lead to accuracy degradation in water quality estimation. Therefore radiometric correction should be carried out to estimate water quality for high resolution satellite images. For KOMPSAT-2 images parameters for brightness value-radiance conversion are not available and precise radiometric correction is difficult. To exploit KOMPSAT-2 images for water quality monitoring, it is necessary to investigate non-linearity of brightness value and noise over inland water. In this paper, we performed brightness value comparison between KOMPSAT-2 images and IKONOS/GeoEye-1, which are known to show the linearity. We used the images obtained over the same area and on the same date for comparison. As a result, we showed that although KOMPSAT-2 images are more noisy;the trend of brightness value and pattern of noise are almost similar to reference images. The results showed that appropriate target area to minimize the impact of noise was $5{\times}5$. Non-linearity of brightness value between KOMPSAT-2 and reference images was not observed. Therefore we could conclude that KOMPSAT-2 may be used for estimation of water quality parameters such as concentration of chlorophyll.

• Korean Journal of Remote Sensing
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• v.31 no.6
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• pp.583-598
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• 2015

This paper presents derivation of background temperature from geostationary satellite and its validation based on ground measurements and Geographic Information System (GIS) for future use in weather and surface heat variability. This study only focuses on daily and monthly brightness temperature in 2012. From the analysis of COMS Meteorological Data Processing System (CMDPS) data, we have found an error in cloud distribution of model, which used as a background temperature field, and in examining the spatial homogeneity. Excessive cloudy pixels were reconstructed by statistical reanalysis based on consistency of temperature measurement. The derived Brightness temperature has correlation of 0.95, bias of 0.66 K and RMSE of 4.88 K with ground station measurements. The relation between brightness temperature and both elevation and vegetated land cover were highly anti-correlated during warm season and daytime, but marginally correlated during cold season and nighttime. This result suggests that time varying emissivity data is required to derive land surface temperature.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1340-1342
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• 2003

In microwave remote sensing, the Fresnel reflectance formula is widely used in the sea surface emissivity modeling. As an essential contribution to microwave remote sensing, a new formula on the Fresnel reflectance has been derived based on our understanding of the complex index of refraction and continuity condition of E-M waves at the interface between two mediums. The proposed formula can be used to obtain the emissivity of sea surface, which is useful to retrieve sea surface temperature, sea surface salinity and the brightness temperature. Considering Bragg-resonant scatter, it is useful for the calculation of the normalized radar cross-section, and the retrieval of sea surface wind either.

• Journal of the Ergonomics Society of Korea
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• v.18 no.2
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• pp.91-102
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• 1999

There are various kinds of good feelings in indoor environment such as comfort, pleasure, delight, refreshment, geniality, etc. Each feeling is interrelated with other complex elements of senses such as warmth, coldness, calmness, clearness, brightness, etc. In this paper, we described what is good feeling in indoor environment, and developed elements of good feelings using Emotion & Sensibility engineering approach. Resultant elements of good feelings were "comfort," "refreshment," and "freshness." Secondary, we investigated the relationships of these elements with certain elements of senses. "Comfort" is related with "warmth, calmness, brightness, and very clearness in indoor air." "Refreshment" and "freshness" are related with "coldness, moderately calmness, very brightness, and very clearness in indoor air." The relationships were formulated as a fuzzy model. By applying human intuition to this model, we could determine physical ranges of "comfort, refreshment, and freshness."

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.19-28
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• 2005

Passive microwave remote sensing technique have shown great potential for mon monitoring regional/global surface soil moisture. Given a single measurement at dual polarization/single frequency/single view angle, a strategic approach to artificially generating multiple microwave brightness temperatures is presented. And then the statistically generated microwave brightness temperature data are applied to the inverse algorithm, which mainly relies on a physically based microwave emission model and an advanced single-criterion multi-parameter optimization technique, to simultaneously retrieve soil moisture and vegetation characteristics. . The procedure is tested with dual polarized Tropical Rainfall Measurement Mission Microwave Imager (TRMM/TMI) over two different cover sites in Oklahoma and Beltsville field experimental data. The retrieval results are analyzed and show excellent performance.