• Korean Journal of Remote Sensing
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• v.34 no.1
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• pp.1-15
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• 2018

Passive microwave sea surface temperatures (SST) were validated in the Northwest Pacific using a total of 102,294 collocated matchup data between Global Precipitation Measurement (GPM) / GPM Microwave Sensor(GMI) data and oceanic in-situ temperature measurements from March 2014 to December 2016. A root-mean-square (RMS) error and a bias error of the GMI SST measurements were evaluated to $0.93^{\circ}C$ and $0.05^{\circ}C$, respectively. The SST differences between GMI and in-situ measurements were caused by various factors such as wind speed, columnar atmospheric water vapor, land contamination near coastline or islands. The GMI SSTs were found to be higher than the in-situ temperature measurements at low wind speed (<6 m/s) during the daytime. As the wind speed increased at night, SST errors showed positive bias. In addition, other factors, coming from atmospheric water vapor, sensitivity degradation at a low temperature range, and land contamination, also contributed to the errors. One of remarkable characteristics of the errors was their latitudinal dependence with large errors at high latitudes above $30^{\circ}N$. Seasonal characteristics revealed that the errors were most frequently observed in winter with a significant positive deviation. This implies that SST errors tend to be large under conditions of high wind speeds and low SSTs. Understanding of microwave SST errors in this study is anticipated to compensate less temporal capability of Infrared SSTs and to contribute to increase a satellite observation rate with time, especially in SST composite process.

• Economic and Environmental Geology
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• v.28 no.1
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• pp.9-17
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• 1995

The Kamkye Cu-Pb-Zn-Au-Ag deposits occur as quartz veins that filled fault-related fractures of NW system developed in the Cretaceous Gyeongsang basin. Three major stages of mineral deposition are recognized: (1) the stage I associated with wall rock alteration, such as sericite, chlorite, epidote and pyrite, (2) the early stage II of base-metal mineralization such as pyrite, hematite, and small amounts of sphalerite and chalcopyrite. and the middle to late stage II of Cu-As-Sb-Au-Ag-S mineralization, such as sphalerite, chalcopyrite, galena with tetrahedrite, tennantite, pearceite, Pb-Bi-Cu-S system, argentite and electrum. (3) the stage III of supergene mineralization, such as covellite, chalcocite and malachite. K-Ar dating of alteration sericite is a late Cretaceous ($74.0{\pm}1.6Ma$) and it may be associated with granitic activity of nearby biotite granite and quartz porphyry. Fluid inclusion data suggest a complex history of boiling, cooling and dilution of ore fluids. Stage II mineralization occurred at temperatures between 370 to $220^{\circ}C$ from fluids with salinities of 8.4 to 0.9 wt.% NaCl. Early stage II($320^{\circ}C$, 2.0 wt.% NaCl) may be boiled due to repeated fracturing which opened up the hydrothermal system to the land surface, and which resulted in a base-metal sulfide. Whilst the fractures were opened to the surface, mixing of middle-late stage II ore fluids with meteoric waters resulted in deposition of Cu-As-Sb-Au-Ag minerals from low temperature fluids(${\leq}290^{\circ}C$). Boiling of ore fluids may be occured at a pressure of 112 bar and a depth of 412 m. Equilibrium thermodynamic interpretation of sphalerite-tetraherite assemblages in middle stage II indicates that the ore-forming fluid had log fugacities of $S_2$ of -6.6~-9.4 atm.

• Atmosphere
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• v.22 no.2
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• pp.137-147
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• 2012

The technique of Brightness Temperature Difference (BTD) between 11 and $12{\mu}m$ separates yellow sand dust from clouds according to the difference in absorptive characteristics between the channels. However, this method causes consistent false alarms in many cases, especially over the desert. In order to reduce these false alarms, we should eliminate the background noise originated from surface. We adopted the Background BTD (BBTD), which stands for surface characteristics on clear sky condition without any dust or cloud. We took an average of brightness temperatures of 11 and $12{\mu}m$ channels during the previous 15 days from a target date and then calculated BTD of averaged ones to obtain decontaminated pixels from dust. After defining the BBTD, we subtracted this index from BTD for the Yellow Sand Index (YSI). In the previous study, this method was already verified using the geostationary satellite, MTSAT. In this study, we applied this to the polar orbiting satellite, MODIS, to detect yellow sand dust over Northeast Asia. Products of yellow sand dust from OMI and MTSAT were used to verify MODIS YSI. The coefficient of determination between MODIS YSI and MTSAT YSI was 0.61, and MODIS YSI and OMI AI was also 0.61. As a result of comparing two products, significantly enhanced signals of dust aerosols were detected by removing the false alarms over the desert. Furthermore, the discontinuity between land and ocean on BTD was removed. This was even effective on the case of fall. This study illustrates that the proposed algorithm can provide the reliable distribution of dust aerosols over the desert even at night.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.481-493
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• 2023

In high-density urban areas, the urban heat island effect increases urban temperatures, leading to negative impacts such as worsened air pollution, increased cooling energy consumption, and increased greenhouse gas emissions. In urban environments where it is difficult to secure additional green spaces, rooftop greening is an efficient greenhouse gas reduction strategy. In this study, we not only analyzed the current status of the urban heat island effect but also utilized high-resolution satellite data and spatial information to estimate the available rooftop greening area within the study area. We evaluated the mitigation effect of the urban heat island phenomenon and carbon sequestration capacity through temperature predictions resulting from rooftop greening. To achieve this, we utilized WorldView-2 satellite data to classify land cover in the urban heat island areas of Busan city. We developed a prediction model for temperature changes before and after rooftop greening using machine learning techniques. To assess the degree of urban heat island mitigation due to changes in rooftop greening areas, we constructed a temperature change prediction model with temperature as the dependent variable using the random forest technique. In this process, we built a multiple regression model to derive high-resolution land surface temperatures for training data using Google Earth Engine, combining Landsat-8 and Sentinel-2 satellite data. Additionally, we evaluated carbon sequestration based on rooftop greening areas using a carbon absorption capacity per plant. The results of this study suggest that the developed satellite-based urban heat island assessment and temperature change prediction technology using Random Forest models can be applied to urban heat island-vulnerable areas with potential for expansion.

• Journal of the Korean Recycled Construction Resources Institute
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• v.9 no.4
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• pp.506-513
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• 2021

The durability and safety of reinforced concrete structures significantly depend on the reinforcement conditions, concrete cover thickness, cracks, and concrete strength. There are two ways to accurately determine the information on reinforcing bars embedded in concrete - the local destructive method and the non-destructive rebar detection test. In general, the non-destructive rebar detection tests, such as the electromagnetic wave radar method, electromagnetic induction method, and radiation method, are adopted to avoid damage to the structural elements. The moisture content and temperature of concrete affect the dielectric constant, which is the electrical property of concrete, and cause interference in the non-destructive rebar detection test results. Therefore, in this study, the effects of the electromagnetic wave radar method and electromagnetic induction method have been analyzed according to the temperature and surface moisture content of concrete. Due to the technological advancement and development of equipment, the average error rate was less than 5% in the specimens at 24℃, irrespective of their operating principles. Among the tested methods, the electromagnetic induction method showed very high accuracy. The electromagnetic wave radar method indicated a relatively small error rate in the dry state than in the wet state, and exhibited a relatively high error rate at high temperatures. It was confirmed that the error could be reduced by applying the electromagnetic wave radar method when the temperature of the probe was low and in a dry state, and by using the electromagnetic induction method when the probe was in a wet state or at a high temperature.

• The Korean Journal of Quaternary Research
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• v.20 no.1 s.26
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• pp.51-66
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• 2006

The climate of the last glacial maximum (LGM) in northeast Asia is simulated with an atmospheric general circulation model of NCAR CCM3 at spectral truncation of T170, corresponding to a grid cell size of roughly 75 km. Modern climate is simulated by a prescribed sea surface temperature and sea ice provided from NCAR, and contemporary atmospheric CO2, topography, and orbital parameters, while LGM simulation was forced with the reconstructed CLIMAP sea surface temperatures, sea ice distribution, ice sheet topography, reduced $CO_2$, and orbital parameters. Under LGM conditions, surface temperature is markedly reduced in winter by more than $18^{\circ}C$ in the Korean west sea and continental margin of the Korean east sea, where the ocean exposed to land in the LGM, whereas in these areas surface temperature is warmer than present in summer by up to $2^{\circ}C$. This is due to the difference in heat capacity between ocean and land. Overall, in the LGM surface is cooled by $4{\sim}6^{\circ}C$ in northeast Asia land and by $7.1^{\circ}C$ in the entire area. An analysis of surface heat fluxes show that the surface cooling is due to the increase in outgoing longwave radiation associated with the reduced $CO_2$ concentration. The reduction in surface temperature leads to a weakening of the hydrological cycle. In winter, precipitation decreases largely in the southeastern part of Asia by about $1{\sim}4\;mm/day$, while in summer a larger reduction is found over China. Overall, annual-mean precipitation decreases by about 50% in the LGM. In northeast Asia, evaporation is also overall reduced in the LGM, but the reduction of precipitation is larger, eventually leading to a drier climate. The drier LGM climate simulated in this study is consistent with proxy evidence compiled in other areas. Overall, the high-resolution model captures the climate features reasonably well under global domain.

• The Korean Journal of Quaternary Research
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• v.16 no.2
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• pp.1-8
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• 2002

In this paper, the writer attempts to clarify causes by general man and weather factor on forest fire occurrence in Kosong-Area, 1995-2001. The major results are summarized as follows: The forest fire at Kojin-ri, Sonyusil-ri and Majwa-ri occurred at the same area over 3 times and that Hakya-ri, Songdae-ri and Inhung-ri, at the adjoining land over 3times. In the total 46 times of forest fire, fire frequence was greatest in March(11 time) and April(11 time) followed by November(7 time), January(6 time), February(6 time). December(3 time), October(2 time). Hours on frequent forest fire are from 11:00 till 18:00. Number for forest fire occurrence by causes was greatest in military training followed by burning paddy fields, debris burning, burning agricultural debris, visiting a grave, cigarette and arson. Frequent forest fire in Kosong-Area coincide not only with above normal temperatures, but also with below normal relative humidity. When the strong winds appear at Kosong-Area, the properties of daily surface chart re the south high and north low pressure pattern in the Far East Asia.

• Journal of Welding and Joining
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• v.23 no.3
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• pp.61-67
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• 2005

Since lead (Pb)-free solders for electronics have higher melting points than that of eutectic Sn-Pb solder, they need higher soldering temperatures. In order to decrease the soldering temperature we tried to coat Sn-Bi layer on $Sn-3.5\%Ag$ solder by electroplating, which applies the mechanism of transient liquid phase bonding to soldering. During heating Bi will diffuse into the $Sn-3.5\%Ag$ solder and this results in decreasing soldering temperature. As bonding samples, the 1608 capacitor electroplated with Sn, and PCB, its surface was finished with electroless-plated Ni/Au, were selected. The $Sn-95.7\%Bi$ coated Sn-3.5Ag was supplied as a solder between the capacitor and PCB land. The samples were reflowed at $220^{\circ}C$, which was lower than that of normal reflow temperature, $240\~250^{\circ}C$, for the Pb-free. As experimental result, the joint of $Sn-95.7\%Bi$ coated Sn-3.5Ag showed high shear strength. In the as-reflowed state, the shear strength of the coated solder showed 58.8N, whereas those of commercial ones were 37.2N (Sn-37Pb), 31.4N (Sn-3Ag-0.5Cu), and 40.2N (Sn-8Zn-3Bi). After thermal shock of 1000 cycles between $-40^{\circ}C$ and $+125^{\circ}C$, shear strength of the coated solder showed 56.8N, whereas the previous commercial solders were in the range of 32.3N and 45.1N. As the microstructures, in the solder $Ag_3Sn$ intermetallic compound (IMC), and along the bonded interface $Ni_3Sn_4$ IMC were observed.

• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.1
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• pp.49-60
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• 2004

Northern Gyeonggi Province(NGP), consisting of 3 counties, is the northernmost region in South Korea adjacent to the de-militarized zone with North Korea. To supplement insufficient spatial coverage of official climate data and climate atlases based on those data, high-resolution digital climate models(DCM) were prepared to support weather- related activities of residents in NGP Monthly climate data from 51 synoptic stations across both North and South Korea were collected for 1981-2000. A digital elevation model(DEM) for this region with 30m cell spacing was used with the climate data for spatially interpolating daily maximum and minimum temperatures, solar irradiance, and precipitation based on relevant topoclimatological models. For daily minimum temperature, a spatial interpolation scheme accommodating the potential influences of cold air accumulation and the temperature inversion was used. For daily maximum temperature estimation, a spatial interpolation model loaded with the overheating index was used. Daily solar irradiances over sloping surfaces were estimated from nearby synoptic station data weighted by potential relative radiation, which is the hourly sum of relative solar intensity. Precipitation was assumed to increase with the difference between virtual terrain elevation and the DEM multiplied by an observed rate. Validations were carried out by installing an observation network specifically for making comparisons with the spatially estimated temperature pattern. Freezing risk in January was estimated for major fruit tree species based on the DCMs under the recurrence intervals of 10, 30, and 100 years, respectively. Frost risks at bud-burst and blossom of tree flowers were also estimated for the same resolution as the DCMs.

• Spatial Information Research
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• v.18 no.4
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• pp.1-11
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• 2010

Unlike the previous studies which have focused on 2-dimensional urban characteristics, this paper presents statistical models explaining urban heat island(UHI) effect by 3-dimensional urban morphologic information and addresses its policy implications. 3~dimensional informations of Columbus, Ohio arc captured from LiDAR data and building boundary informations are extracted from a building digital map, Finally NDV[ and temperature data are calculated by manipulating band 3, band 4, and thermal hand of LandSat images. Through complicated data processing, 6 independent variables(building surface area, building volume, height to width ratio, porosity, plan surface area) are introduced in simple and multiple linear regression models. The regression models are specified by Box-Tidwell method, finding the power to which the independent variable needs to raised to be in a linearity. Porosity, NDVI, and building surface area are carefully chosen as explanatory variables in the final multiple regression model, which explaining about 57% of the variability in temperatures. On reducing UHI, various implications of the results give guidelines to policy-making in open space, roof garden, and vertical garden management.