• 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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• 2008.10a
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• pp.26-28
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• 2008

Soil moisture plays an important role in the land-atmosphere energy balance because it governs the partitioning of energy through latent heat fluxes or evapotranspiration. From the numerous studies, it is evident that the L-band radiometer is a useful and effective tool to measure soil moisture. The objective of the study is to develop and to verify the soil moisture retrieval algorithms for the L-band radiometer system. Through the radiometer-observed brightness temperature, surface emissivity and reflectivity can be derived, and, hence, soil moisture. We collect field and L-band airborne radiometer data from washita92, SGP97 and SGP99 experiments to assist the development of the retrieval algorithms. Upon launching the satellite L-band radiometer such as ESA-sponsored SMOS (Soil Moisture and Ocean Salinity) mission, the developed algorithms may be used to study and monitor globe soil moisture change.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.373-377
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• 2006

Seasonal threshold values for fog detection over the ten airport areas in the Korean Peninsula have been derived, using the satellite-observed data of polar-orbit (Aqua/Terra MODIS) and geostationary (GOES-9) during two years. The values are obtained from reflectance at $0.65{\mu}m\;(R_{0.65})$ and the difference in brightness temperature between $3.7{\mu}m\;and\;11{\mu}m\;(T_{3.7-11})$. In order to examine the discrepancy between the threshold values of two kinds of satellites, the following parameters have been analyzed under the condition of daytime/nighttime and fog/clear-sky, utilizing their simultaneous observations over the Seoul Metropolitan Area. The parameters are the brightness temperature at $3.7{\mu}m\;(T_{3.7})$, the temperature at $11{\mu}m\;(T_{11}$, and $T_{3.7-11}$ for day and night. The $R_{0.65}$ data are additionally included in the daytime. The GOES-9 thresholds over the seven airport areas except the Cheongju airport have revealed the accuracy of 50% in the daytime and 70% in the nighttime, based on statistical verification for the independent samples as follows; FAR, POD and CSI. However, the accuracy decreases in the foggy cases with twilight, precipitation, short persistence, or the higher cloud above fog.

• 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.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.251-255
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• 2008

We have developed an electronic aids, called SmartWand, which can help visually impaired people walk safely and tell them an object's color and environmental brightness SmartWand can inform visually impaired people of the dangerous obstacles around which they can't notice by the white cane such as a large panel with supporting poles on the street. Especially we have lmproved the previous version of SmartWand by reflecting the result of user study.

• Proceedings of the KSRS Conference
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• v.1
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• pp.508-511
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• 2006

Generally, stereo pair images are necessary for 3D viewing. In the absence of quality stereo-pair images, it is possible to synthesize a stereo-mate suitable for 3D viewing with a single image and a depth-map. In remote sensing, DEM is usually used as a depth-map. In this paper, LiDAR data was used instead of DEM to make a stereo pair from a single aerial photo. Each LiDAR point was assigned a brightness value from the original single image by registration of the image and LiDAR data. And then, imaginary exposure station and image plane were assumed. Finally, LiDAR points with already-assigned brightness values were back-projected to the imaginary plane for synthesis of a stereo-mate. The imaginary exposure station and image plane were determined to have only a horizontal shift from the original image's exposure station and plane. As a result, the stereo-mate synthesized in this paper fulfilled epipolar geometry and yielded easily-perceivable 3D viewing effect together with the original image. The 3D viewing effect was tested with anaglyph at the end.

• Proceedings of the KSRS Conference
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• v.2
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• pp.1007-1010
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• 2006

This study investigates the spatial structure of the total cloud liquid water content Q fields over the Northwest Pacific Ocean during winter monsoon. The distributions of Q have been estimated from the brightness temperatures of the ocean - atmosphere system $T_B(f)$, where f is frequency, measured by AQUA AMSR-E in January -March 2003. Marine strati (St) and stratocumuli (Sc) are typical for winter monsoon season. They were analysed using mainly high-frequency channel at f = 36.5 GHz, vertical polarisation. $T_B$ data were accompanied by the data on near surface wind speed, air temperature and humidity from the nearest meteorological stations. Tow one-dimensional spectra were computed for downwind and crosswind sections of Q fields. The AMSR-E antenna field of view (14-8 km) and the cloud field sizes (100-1000 km) restricted the spatial scales. The results of case study Jan 31 2003 are presented. Scale-invariant spectrum is typical. In the cases of extended St levels a spectral slope equals about -1.7, conforming to classical -5/3 of turbulence theory. For Sc cases the absolute magnitude of spectral slope is rather higher, as a rule. The value is about -2. In the case when cloud streets are presented, a strait line form of spectrum is less reliable with a slope being rather lower (about -1.4).

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.604-609
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• 2002

The passive microwave remote sensing has progressed considerably in recent years. Important earth surface parameters are detected and monitored by airborne and space born radiometers. However the spatial resolution of real aperture measurements is constrained by the antenna aperture size available on orbiting platforms and on the ground. The inverse problem technique is researched in order to improve the spatial resolution of microwave scanning radiometer. We solve a two-dimensional (surface) temperature-imaging problem with a major intention to develop high-resolution methods. In this paper, the scenario for estimation of both radiometer point spread function (PSF) and target configuration is explained. The PSF of the radiometer is assumed to be unknown and estimated from the observations. The configuration and brightness temperature of targets are also estimated. To do this, we deal with the parametric modeling of observation scenario. The performance of developed algorithms is illustrated on two-dimensional experimental data obtained by the water vapor radiometer.

• Korean Journal of Remote Sensing
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• v.9 no.1
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• pp.1-19
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• 1993

A simple bispectral threshold technique which reflects the temporal and spatial characteristics of the analysis area has been developed to classify the cloud type and estimate the cloud cover from GMS/S-VISSR(Stretched Visible and Infrared Spin Scan Radiometer) imagery. In this research, we divided the analysis area into land and sea to consider their different optical properties and used the same time observation data to exclude the solar zenith angle effects included in the raw data. Statistical clear sky radiance(CSRs) was constructed using maximum brightness temperature and minimum albedo from the S-VISSR imagery data during consecutive two weeks. The CSR used in the cloud anaysis was updated on the daily basis by using CSRs, the standard deviation of CSRs and present raw data to reflect the daily variation of temperature. Thresholds were applied to classify the cloud type and estimate the cloud cover from GMS/S-VISST imagery. We used a different thresholds according to the earth surface type and the thresholds were enough to resolve the spatial variation of brightness temperature and the noise in raw data. To classify the ambiguous pixels, we used the time series of 2-D histogram and local standard deviation, and the results showed a little improvements. Visual comparisons among the present research results, KMA's manual analysis and observed sea level charts showed a good agreement in quality.

• Korean Journal of Remote Sensing
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• v.15 no.3
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• pp.239-251
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• 1999

The elimination process of cloud-contaminated pixels is one of important steps before obtaining the accurate parameters of land and ocean surface from AVHRR imagery. We developed a 6step threshold method to detect the cloud-contaminated pixels from NOAA-14/AVHRR datime imagery over land using different combination of channels. This algorithm has two phases : the first is to make a cloud-free characteristic data of land surface using compositing techniques from channel 1 and 5 imagery and a dynamic threshold of brightness temperature, and the second is to identify the each pixel as a cloud-free or cloudy one through 4-step threshold tests. The merits of this method are its simplicity in input data and automation in determining threshold values. The threshold of infrared data is calculated through the combination of brightness temperature of land surface obtained from AVHRR imagery, spatial variance of them and temporal variance of observed land surface temperature. The method detected the could-comtaminated pixels successfully embedded inthe NOAA-14/AVHRR daytime imagery for the August 1 to November 30, 1996 and March 1 to July 30, 1997. This method was evaluated through the comparison with ground-based cloud observations and with the enhanced visible and infrared imagery.