• Proceedings of the Korean Society of Medical Physics Conference
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• 2005.04a
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• pp.59-63
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• 2005

Respiration motion causes movement of internal structures in the thorax and abdomen, making accurate delivery of radiation therapy to tumors in those areas a challenge. Accounting for such motion during treatment, therefore, has the potential to reduce margins drawn around the clinical target volume (CTV), resulting in a lower dose to normal tissues (e.g., lung and liver) and thus a lower risk of treatment induced complications. Among the techniques that explicitly account for intrafraction motion are breath-hold, respiration gating, and 4D or tumor-tracking techniques. Respiration gating methods periodically turn the beam on when the patient's respiration signal is in a certain part of the respiratory cycle (generally end-inhale or end-exhale). These techniques require acquisition of some form of respiration motion signal (infrared reflective markers, spirometry, strain gauge, thermistor, video tracking of chest outlines and fluoroscopic tracking of implanted markers are some of the techniques employed to date), which is assumed to be correlated with internal anatomy motion. In preliminary study for the respiratory gating radiation therapy, we performed to measurement of this respiration motion signal. In order to measure the respiratory motion signals of patient, respiration measurement system (RMS) was composed with three sensor (spirometer, thermistor, and belt transducer), 4 channel data acquisition system and mobile computer. For two patients, we performed to evaluation of respiratory cycle and shape with RMS. We observed under this system that respiratory cycle is generally periodic but asymmetric, with the majority of time spent. As expected, RMS traced patient's respiration each other well and be easily handled for application.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.4
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• pp.215-219
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• 2001

Land surface parameterization schemes for atmospheric models as well as decision support tools for ecosystem management require a frequent updating of land cover classification data for regional to global scales. Rice paddies have not been treated independently from other agricultural land classes in many classification systems, despite their atmospheric and ecological significance. A simple but improved method over conventional land cover classification schemes for rice paddy is suggested. Normalized difference vegetation index (NDVI) was calculated for the land area of South Korea at a 1km by 1 km resolution from the visible and the near-infrared channel reflectances of NOAA-AVHRR (Advanced Very High Resolution Radiometer). Monthly composite images of daily maximum NDVI were prepared for May and August, and used to classify 4 major land cover classes : urban, farmland, forests and water body. Among the pixels classified as "forests" in August, those classified as "water body" in May were assigned a "rice paddy" class. The distribution pattern of "rice paddy" pixels was very similar to the reported rice acreage of 1,455 Myons, which is the smallest administrative land unit in Korea. The correlation coefficient between the estimated and the reported acreage of Myons was 0.7, while 0.5 was calculated from the USGS classification.calculated from the USGS classification.

• Korean Journal of Remote Sensing
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• v.9 no.2
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• pp.51-69
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• 1993

Precipitable Water(PW) are retrieved over the tropical and subtropical Pacific Ocean from TOVS infrared and microwave channel brightness temperature and OLR observations by means of stepwise linear regression. The retrieved TOVS PW fields generated by PW$_{sfc}$(71.1 % of the variance and 0.62 g cm$^{-2}$ standard error over the surface) and PW$_{700500}$(71.7 % and 0.17 g cm$^{-2}$ over the 700 - 500 hPa layer) revealed more evolving synoptic signals over the tropical and subtropical Pacific Ocean. The PW$_{sfc}$ dose not show significantly the TP feature because of the representation of the lower PW for high-level clouds not associated with deep convection. There exists some elusion to trace the TP on the PW$_{sfc}$ field if any supplementary information does not provide. But ECMWF analysis has a general tendency of drying the subtropics and moistening the ITCZ (InterTropical Convergence Zone) and SPCZ(South Pacific Convergence Zone). However, although ECMWF analysis is fairly successful in capturing mean patterms, it is unsuccessful in following active synoptic signal like a tropical plume. Similarly, SMMR-PW does not represent the TP well which consists of the highand middle-level clouds, but PW$_{sfc}$ shows underestimated moistness of TP and does not depict significant signal of TP. In the PW field derived from microwave observations, the TP can not be recognized well. Furthermore, the signature of PW$_{sfc}$ was different from OLR for the TP, which implies the presence of high- and middle-layer thin clouds, but in a closer agreement for deep and active convection areas which contain thick middle- and lower-layer clouds; though OLR represented the cloudiness in the tropics well. In synoptically active regions, it differed from OLR analysis, primarily bacause of actual differences in water vapor and cloud features. The signature of PW$_{sfc}$ was different from OLR for the TP.

• Korean Journal of Remote Sensing
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• v.28 no.1
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• pp.69-77
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• 2012

Surface insolation is one of the major indicators for climate research over the Earth system. For the climate research, long-term data and wide range of spatial coverage from the data observed by two or more of satellites of the same orbit are needed. It is important to improve the continuity and consistency of the derived products, such as surface insolation, from different satellites. In this study, surface insolations based on Geostationary Operational Environmental Satellite (GOES-9) and Multi-functional Transport Satellites (MTSAT-1R) were compared during overlap period using physical model of insolation to find ways to improve the consistency and continuity between two satellites through comparison of each channel data and ground observation data. The thermal infrared brightness temperature of two satellites show a relatively good agreement between two satellites : rootmean square error (RMSE)=5.595 Kelvin; Bias=2.065 Kelvin. Whereas, visible channels shown a quite different values, but it distributed similar tendency. And the surface insolations from two satellites are different from the ground observation data. To improve the quality of retrieved insolations, we have reproduced surface insolation of each satellite through adjustment of the Cloud Factor, and the Cloud Factor for GOES-9 satellite is modified based on the analysis result of difference channel data. As a result, the insolations estimated from GOES-9 for cloudy conditions show good agreement with MTSAT-1R and ground observation : RMSE=$83.439W\;m^{-2}$ Bias=$27.296W\;m^{-2}$. The result improved accuracy confirms that the modification of Cloud Factor for GOES-9 can improve the continuity and consistency of the insolations derived from two or more satellites.

• Korean Journal of Remote Sensing
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• v.21 no.6
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• pp.445-456
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• 2005

The land surface parameters should be determined with sufficient accuracy, because these play an important role in climate change near the ground. As the surface reflectance presents strong anisotropy, off-nadir viewing results a strong dependency of observations on the Sun - target - sensor geometry. They contribute to the random noise which is produced by surface angular effects. The principal objective of the study is to provide a database of accurate surface reflectance eliminated the angular effects from MODIS 250m reflective channel data over Korea. The MODIS (Moderate Resolution Imaging Spectroradiometer) sensor has provided visible and near infrared channel reflectance at 250m resolution on a daily basis. The successive analytic processing steps were firstly performed on a per-pixel basis to remove cloudy pixels. And for the geometric distortion, the correction process were performed by the nearest neighbor resampling using 2nd-order polynomial obtained from the geolocation information of MODIS Data set. In order to correct the surface anisotropy effects, this paper attempted the semiempirical kernel-driven Bi- directional Reflectance Distribution Function(BRDF) model. The algorithm yields an inversion of the kernel-driven model to the angular components, such as viewing zenith angle, solar zenith angle, viewing azimuth angle, solar azimuth angle from reflectance observed by satellite. First we consider sets of the model observations comprised with a 31-day period to perform the BRDF model. In the next step, Nadir view reflectance normalization is carried out through the modification of the angular components, separated by BRDF model for each spectral band and each pixel. Modeled reflectance values show a good agreement with measured reflectance values and their RMSE(Root Mean Square Error) was totally about 0.01(maximum=0.03). Finally, we provide a normalized surface reflectance database consisted of 36 images for 2001 over Korea.

• Ecology and Resilient Infrastructure
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• v.8 no.1
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• pp.32-43
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• 2021

Multichannel automated chamber systems (MCACs) were developed for the continuous monitoring of soil CO2 efflux in forest ecosystems. The MCACs mainly consisted of four modules: eight soil chambers with lids that automatically open and close, an infrared CO2 analyzer equipped with eight multichannel gas samplers, an electronic controller with time-relay circuits, and a programmable logic datalogger. To examine the stability and reliability of the developed MCACs in the field during all seasons with a high temporal resolution, as well as the effects of temperature and soil water content on soil CO2 efflux rates, we continuously measured the soil CO2 efflux rates and micrometeorological factors at the Nam-san experimental site in a Quercus mongolica forest floor using the MCACs from January to December 2010. The diurnal and seasonal variations in soil CO2 efflux rates markedly followed the patterns of changes in temperature factors. During the entire experimental period, the soil CO2 efflux rates were strongly correlated with the temperature at a soil depth of 5 cm (r2 = 0.92) but were weakly correlated with the soil water content (r2 = 0.27). The annual sensitivity of soil CO2 efflux to temperature (Q10) in this forest ranged from 2.23 to 3.0, which was in agreement with other studies on temperate deciduous forests. The annual mean soil CO2 efflux measured by the MCACs was approximately 11.1 g CO2 m-2 day-1. These results indicate that the MCACs can be used for the continuous long-term measurements of soil CO2 efflux in the field and for simultaneously determining the impacts of micrometeorological factors.

• Journal of the Korean earth science society
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• v.39 no.2
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• pp.119-130
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• 2018

Aerosol Optical Properties (AOPs) are retrieved using the geostationary satellite instruments such as Geostationary Ocean Color Imager (GOCI), Meteorological Imager (MI), and Advanced Himawari Imager (AHI) through Yonsei AErosol Retrieval algorithm (YAER). In this study, the retrieved aerosol optical depths (AOD)s from each instrument were intercompared and validated with the ground-based sunphotometer AErosol Robotic NETwork (AERONET) data. As a result, the four AOD products derived from different instruments showed consistent results over land and ocean. However, AODs from MI and GOCI tend to be overestimated due to cloud contamination. According to the comparison results with AERONET, the percentage within expected errors (EE) are 36.3, 48.4, 56.6, and 68.2% for MI, GOCI, AHI-minimum reflectivity method (MRM), and AHI-estimated surface reflectance from shortwave Infrared (ESR) product, respectively. Since MI AOD is retrieved from a single visible channel, and adopts only one aerosol type by season, EE is relatively lower than other products. On the other hand, the AHI ESR is more accurate than the minimum reflectance method as used by GOCI, MI, and AHI MRM method in May and June when the vegetation is relatively abundant. These results are explained by the RMSE and the EE for each AERONET site. The ESR method result show to be better than the other satellite product in terms of EE for 15 out of 22 sites used for validation, and they are better than the other product for 13 sites in terms of RMSE. In addition, the error in observation time in each product is found by using characteristics of geostationary satellites. The absolute median biases at 00 to 06 Universal Time Coordinated (UTC) are 0.05, 0.09, 0.18, 0.18, 0.14, 0.09, and 0.10. The absolute median bias by observation time has appeared in MI and the only 00 UTC appeared in GOCI.