• The Korean Journal of Nuclear Medicine
• /
• v.34 no.4
• /
• pp.322-335
• /
• 2000

Purpose: For quantitative estimation of cerebrovascular reserve (CVR), we estimated the cerebral blood flow (CBF) using Lassen's nonlinearity correction algorithm and Tc-99m HMPAO brain SPECT images acquired with consecutive acquisition protocol. Using the values of CBF in basal and acetaBolamide (ACZ) stress states, CBF increase was calculated. Materials and Methods: In 9 normal subjects (age; $72{\pm}4$ years), brain SPECT was performed at basal and ACZ stress states consecutively after injection of 555 MBq and 1,110 MBq of Tc-99m HMPAO, respectively. Cerebellum was automatically extracted as reference region on basal SPECT image using threshold method. Assuming basal CBF of cerebellum as 55 ml/100g/min, CBF was calculated lot every pixel at basal states using Lassen's algorithm. Cerebellar blood flow at stress was estimated comparing counts of cerebellum at rest and ACZ stress and Lassen's algorithm. CBF of every pixel at ACZ stress state was calculated using Lassen's algorithm and ACZ cerebellar count. CVR was calculated by subtracting basal CBF from ACZ stress CBF for every pixel. The percent CVR was calculated by dividing CVR by basal CBF. The CBF and percentage CVR parametric images were generated. Results: The CBF and percentage CVR parametric images were obtained successfully in all the subjects. Global mean CBF were $49.6{\pm}5.5ml/100g/min\;and\;64.4{\pm}10.2ml/100g/min$ at basal and ACZ stress states, respectively. The increase of CBF at ACZ stress state was $14.7{\pm}9.6ml/100g/min$. The global mean percent CVR was 30.7% and was higher than the 13.8% calculated using count images. Conclusion: The blood flow at basal and ACZ stress states and cerebrovascular reserve were estimated using basal/ACZ Tc-99m-HMPAO SPECT images and Lassen's algorithm. Using these values, parametric images for blood flow and cerebrovascular reserve were generated.

• Journal of the Korean earth science society
• /
• v.43 no.5
• /
• pp.604-617
• /
• 2022

Sea surface temperature (SST) is a key variable that can be used to understand ocean-atmosphere phenomena and predict climate change. Satellite microwave remote sensing enables the measurement of SST despite the presence of clouds and precipitation in the sensor path. Therefore, considering the high utilization of microwave SST, it is necessary to continuously verify its accuracy and analyze its error characteristics. In this study, the validation of the microwave global precision measurement (GPM)/GPM microwave imager (GMI) SST around the Northwest Pacific and Korean Peninsula was conducted using surface drifter temperature data for approximately eight years from March 2014 to December 2021. The GMI SST showed a bias of 0.09K and an average root mean square error of 0.97K compared to the actual SST, which was slightly higher than that observed in previous studies. In addition, the error characteristics of the GMI SST were related to environmental factors, such as latitude, distance from the coast, sea wind, and water vapor volume. Errors tended to increase in areas close to coastal areas within 300 km of land and in high-latitude areas. In addition, relatively high errors were found in the range of weak wind speeds (<6 m s^-1) during the day and strong wind speeds (>10 m s^-1) at night. Atmospheric water vapor contributed to high SST differences in very low ranges of <30 mm and in very high ranges of >60 mm. These errors are consistent with those observed in previous studies, in which GMI data were less accurate at low SST and were estimated to be due to differences in land and ocean radiation, wind-induced changes in sea surface roughness, and absorption of water vapor into the microwave atmosphere. These results suggest that the characteristics of the GMI SST differences should be clarified for more extensive use of microwave satellite SST calculations in the seas around the Korean Peninsula, including a part of the Northwest Pacific.

• Korean Journal of Remote Sensing
• /
• v.33 no.5_2
• /
• pp.721-732
• /
• 2017

With the increasing socio-economic importance of rice as a global staple food, several models have been developed for rice yield estimation by combining remote sensing data with carbon cycle modelling. In this study, we aimed to estimate rice yield in Korea using such an integrative model using satellite remote sensing data in combination with a biophysical crop growth model. Specifically, daily meteorological inputs derived from MODIS (Moderate Resolution imaging Spectroradiometer) and radar satellite products were used to run a light use efficiency based crop growth model, which is based on the MODIS gross primary production (GPP) algorithm. The modelled biomass was converted to rice yield using a harvest index model. We estimated rice yield from 2003 to 2014 at the county level and evaluated the modelled yield using the official rice yield and rice straw biomass statistics of Statistics Korea (KOSTAT). The estimated rice biomass, yield, and harvest index and their spatial distributions were investigated. Annual mean rice yield at the national level showed a good agreement with the yield statistics with the yield statistics, a mean error (ME) of +0.56% and a mean absolute error (MAE) of 5.73%. The estimated county level yield resulted in small ME (+0.10~+2.00%) and MAE (2.10~11.62%),respectively. Compared to the county-level yield statistics, the rice yield was over estimated in the counties in Gangwon province and under estimated in the urban and coastal counties in the south of Chungcheong province. Compared to the rice straw statistics, the estimated rice biomass showed similar error patterns with the yield estimates. The subpixel heterogeneity of the 1 km MODIS FPAR(Fraction of absorbed Photosynthetically Active Radiation) may have attributed to these errors. In addition, the growth and harvest index models can be further developed to take account of annually varying growth conditions and growth timings.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.17 no.2
• /
• pp.108-125
• /
• 2015

The agro-climatic index is one of the ways to assess the climate resources of particular agricultural areas on the prospect of agricultural production; it can be a key indicator of agricultural productivity by providing the basic information required for the implementation of different and various farming techniques and practicalities to estimate the growth and yield of crops from the climate resources such as air temperature, solar radiation, and precipitation. However, the agro-climate index can always be changed since the index is not the absolute. Recently, many studies which consider uncertainty of future climate change have been actively conducted using multi-model ensemble (MME) approach by developing and improving dynamic and statistical downscaling of Global Climate Model (GCM) output. In this study, the agro-climatic index of Korean Peninsula, such as growing degree day based on $5^{\circ}C$, plant period based on $5^{\circ}C$, crop period based on $10^{\circ}C$, and frost free day were calculated for assessment of the spatio-temporal variations and uncertainties of the indices according to climate change; the downscaled historical (1976-2005) and near future (2011-2040) RCP climate sceneries of AR5 were applied to the calculation of the index. The result showed four agro-climatic indices calculated by nine individual GCMs as well as MME agreed with agro-climatic indices which were calculated by the observed data. It was confirmed that MME, as well as each individual GCM emulated well on past climate in the four major Rivers of South Korea (Han, Nakdong, Geum, and Seumjin and Yeoungsan). However, spatial downscaling still needs further improvement since the agro-climatic indices of some individual GCMs showed different variations with the observed indices at the change of spatial distribution of the four Rivers. The four agro-climatic indices of the Korean Peninsula were expected to increase in nine individual GCMs and MME in future climate scenarios. The differences and uncertainties of the agro-climatic indices have not been reduced on the unlimited coupling of multi-model ensembles. Further research is still required although the differences started to improve when combining of three or four individual GCMs in the study. The agro-climatic indices which were derived and evaluated in the study will be the baseline for the assessment of agro-climatic abnormal indices and agro-productivity indices of the next research work.

• Journal of the Korean Society for Marine Environment & Energy
• /
• v.11 no.3
• /
• pp.138-149
• /
• 2008

Rapid accumulation of carbon dioxide in the atmosphere for the past century leads to acidify the surface ocean and contributes to the global warming as it forms acid in the ocean and it is a green house gas. In order to curb the green house gas emissions, in particular carbon dioxide, various multilateral agreements and programs have been established including UN Convention of Climate Change and its Kyoto Protocol for the last decades. Also a number of geo-engineering projects to manipulate the radiation balance of the earth have been proposed both from the science and industrial community worldwide. One of them is ocean fertilization to sequester carbon dioxide from the atmosphere through the photosynthesis of phytoplankton in the sea. Deliberate fertilization of the ocean with iron or nitrogen to large areas of the ocean has been proposed by commercial sector recently. Unfortunately the environmental consequences of the large scale ocean iron fertilization are not known and the current scientific information is still not sufcient to predict. In 2007, the joint meeting of parties of the Convention on the Prevention of Marine Pollution by Dumping of Wastes and Other Matter, 1972 and 1996 Protocol (London Convention/Protocol) has started considering the purposes and circumstances of proposed large-scale ocean iron fertilization operations and examined whether these activities are compatible with the aims of the Convention and Protocol and explore the need, and the potential mechanisms for regulation of such operations. The aim of this paper is to review the current development on the commercial ocean fertilization activities and management regimes in the potential ocean fertilization activities in the territorial sea, exclusive economic zone, and high seas, respectively, and further to have a view on the emerging international management regime to be London Convention/Protocol in conjunction with a support from the United Nations General Assembly through The United Nations Open-ended Informal Consultative Process on Oceans and the Law of the Sea.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.5 no.2
• /
• pp.1-15
• /
• 2002

Atmospheric aerosols interact with sunlight and affect the global radiation balance that can cause climate change through direct and indirect radiative forcing. Because of the spatial and temporal uncertainty of aerosols in atmosphere, aerosol characteristics are not considered through GCMs (General Circulation Model). Therefor it is important physical and optical characteristics should be evaluated to assess climate change and radiative effect by atmospheric aerosols. In this study GMS-5 satellite data and surface measurement data were analyzed using a radiative transfer model for the Yellow Sand event of April 7~8, 2000 in order to investigate the atmospheric radiative effects of Yellow Sand aerosols, MODTRAN3 simulation results enable to inform the relation between satellite channel albedo and aerosol optical thickness(AOT). From this relation AOT was retreived from GMS-5 visible channel. The variance observations of satellite images enable remote sensing of the Yellow Sand particles. Back trajectory analysis was performed to track the air mass from the Gobi desert passing through Korean peninsular with high AOT value measured by ground based measurement. The comparison GMS-5 AOT to ground measured RSR aerosol optical depth(AOD) show that for Yellow Sand aerosols, the albedo measured over ocean surfaces can be used to obtain the aerosol optical thickness using appropriate aerosol model within an error of about 10%. In addition, LIDAR network measurements and backward trajectory model showed characteristics and appearance of Yellow Sand during Yellow Sand events. These data will be good supporting for monitoring of Yellow Sand aerosols.

• Journal of Bio-Environment Control
• /
• v.15 no.4
• /
• pp.296-305
• /
• 2006

The heterogeneity of crop transpiration is important to clearly understand the microclimate mechanisms and to efficiently handle the water resource in greenhouses. A computational fluid dynamic program (Fluent CFD version 6.2) was developed to study the internal climate and crop transpiration distributions of greenhouses. Additionally, the global solar radiation model and a crop heat exchange model were programmed together. Those models programmed using $C^{++}$ software were connected to the CFD main module using the user define function (UDF) technology. For the developed CFD validity, a field experiment was conducted at a $17{\times}6 m^2$ plastic-covered mechanically ventilated single-span greenhouse located at Pusan in Korea. The CFD internal distributions of air temperature, relative humidity, and air velocity at 1m height were validated against the experimental results. The CFD computed results were in close agreement with the measured distributions of the air temperature, relative humidity, and air velocity along the greenhouse. The averaged errors of their CFD computed results were 2.2%,2.1%, and 7.7%, respectively.

• Journal of the Korean earth science society
• /
• v.32 no.3
• /
• pp.276-293
• /
• 2011

In this study a modeling system consisting of Weather Research and Forecasting (WRF), Sparse Matrix Operator Kernel Emissions (SMOKE), the Community Multiscale Air Quality (CMAQ) model, and the CMAQ-Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution (MADRID) model has been applied to estimate enhancements of $PM_{10}$ during Asian dust events in Korea. In particular, 5 experimental formulas were applied to the WRF-SMOKE-CMAQ (MADRID) model to estimate Asian dust emissions from source locations for major Asian dust events in China and Mongolia: the US Environmental Protection Agency (EPA) model, the Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model, and the Dust Entrainment and Deposition (DEAD) model, as well as formulas by Park and In (2003), and Wang et al. (2000). According to the weather map, backward trajectory and satellite image analyses, Asian dust is generated by a strong downwind associated with the upper trough from a stagnation wave due to development of the upper jet stream, and transport of Asian dust to Korea shows up behind a surface front related to the cut-off low (known as comma type cloud) in satellite images. In the WRF-SMOKE-CMAQ modeling to estimate the PM10 concentration, Wang et al.'s experimental formula was depicted well in the temporal and spatial distribution of Asian dusts, and the GOCART model was low in mean bias errors and root mean square errors. Also, in the vertical profile analysis of Asian dusts using Wang et al's experimental formula, strong Asian dust with a concentration of more than $800\;{\mu}g/m^3$ for the period of March 31 to April 1, 2007 was transported under the boundary layer (about 1 km high), and weak Asian dust with a concentration of less than $400\;{\mu}g/m^3$ for the period of 16-17 March 2009 was transported above the boundary layer (about 1-3 km high). Furthermore, the difference between the CMAQ model and the CMAQ-MADRID model for the period of March 31 to April 1, 2007, in terms of PM10 concentration, was seen to be large in the East Asia area: the CMAQ-MADRID model showed the concentration to be about $25\;{\mu}g/m^3$ higher than the CMAQ model. In addition, the $PM_{10}$ concentration removed by the cloud liquid phase mechanism within the CMAQ-MADRID model was shown in the maximum $15\;{\mu}g/m^3$ in the Eastern Asia area.

• The Korean Journal of Nuclear Medicine
• /
• v.31 no.3
• /
• pp.330-338
• /
• 1997

This study investigated the method to adjust acquisition time(a) and injection dose (i) to make the best basal and subtraction images in consecutive SPECT. Image quality was assumed to be mainly affected by signal to noise ratio(S/N). Basal image was subtracted from the second image consecutively acquired at the same position. We calculated S/N ratio in basal SPECT images($S_1/N_1$) and subtraction SPECT images(Ss/Ns) to find a(time) and i(dose) to maximize S/N of both images at the same time. From phantom images, we drew the relation of image counts and a(time) and i(dose) in our system using fanbeam-high-resolution collimated triple head SPECT. Noise by imaging process depended on Poisson distribution. We took maximum tolerable duration of consecutive acquisition as 30 minutes and maximum injectible dose as 1,850MBq(50 mCi)(sum of two injections) per study. Counts of second-acquired image($S_2$), counts($S_s$) and noise($N_s$) of subtraction SPECT were as follows. $C_1$ was the coefficient of measurement with our system. $$S_2=S_1{\cdot}(\frac{30-a}{a})+background{\cdot}(1-\frac{30-a}{a})+C_1{\cdot}(30-a){\cdot}{\epsilon}{\cdot}(50-i)$$ $$Ss=S_2-\{S_1{\cdot}(\frac{30-a}{a})+background{\cdot}(1-\frac{(30-a)}{a})\}$$ $$Ns={\sqrt{N_2^2+N_1^2{\cdot}\frac{(30-a)^2}{a^2}}={\sqrt{S_2+S_1{\cdot}\frac{(30-a)^2}{a^2}}$$ In case of rest/acetazolamide study, effect(${\epsilon}$) of acetazolamide to increase global brain uptake of Tc-99m-HMPAO could be 1.5 or less. Varying ${\epsilon}$ from 1 to 1.5, a(time) and i(dose) pair to maximize both $S_1/N_l$ and Ss/Ns was determined. 15 mCi/17 min and 35mCi/13min was the best a(time) and i(dose) pair for rest/acetazolamide study(when ${\epsilon}$ were 1.2) and came to be used for our clinical routine after this study. We developed simple method to maximize S/N ratios of basal and subtraction SPECT from consecutive acquisition. This method could be applied to ECD/HMPAO and brain activation studies as well as rest/acetazolamide studies.

• Journal of Korea Water Resources Association
• /
• v.39 no.5 s.166
• /
• pp.453-466
• /
• 2006

The objective of this study was to analyze the changes in the hydrological environment in Soyanggang-dam watershed due to climate change results (in yews 2050 and 2100) which were simulated using CCCma CGCM2 based on SRES A2 and B2. The SRES A2 and B2 were used to estimate NDVI values for selected land use using the relation of NDVI-Temperature using linear regression of observed data (in years 1998$\sim$2002). Land use change based on SRES A2 and B2 was estimated every 5- and 10-year period using the CA-Markov technique based on the 1985, 1990, 1995 and 2000 land cover map classified by Landsat TM satellite images. As a result, the trend in land use change in each land class was reflected. When land use changes in years 2050 and 2100 were simulated using the CA-Markov method, the forest class area declined while the urban, bareground and grassland classes increased. When simulation was done further for future scenarios, the transition change converged and no increasing trend was reflected. The impact assessment of evapotranspiration was conducted by comparing the observed data with the computed results based on three cases supposition scenarios of meteorological data (temperature, global radiation and wind speed) using the FAO Penman-Monteith method. The results showed that the runoff was reduced by about 50% compared with the present hydrologic condition when each SRES and periods were compared. If there was no land use change, the runoff would decline further to about 3$\sim$5%.