• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.587-596
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• 2014

Soil moisture is one of the most important interests in hydrological response and the interaction between the land surface and atmosphere. Estimation of Antecedent Wetness Conditions (AWC) which is soil moisture condition prior to a rainfall in the basin should be considered for rainfall-runoff prediction. In this study, Soil Wetness Index (SWI), Antecedent Precipitation Index ($API_5$), remotely sensed Soil Moisture ($SM_{rs}$), and 5 days ground Soil Moisture ($SM_{g5}$) were selected to estimate the AWC at four study area in the Korean Peninsula. The remotely sensed soil moisture data were taken from the AMSR-E soil moisture archive. The maximum potential retention ($S_{obs}$) was obtained from direct runoff and rainfall using Soil Conservation Service-Curve Number (SCS-CN) method by rainfall data of 2011 for each study area. Results showed the great correlations between the maximum potential retention and SWI with a mean correlation coefficient which is equal to -0.73. The results of time length representing the time scale of soil moisture showed a gap from region to region. It was due to the differences of soil types and the characteristics of study area. Since the remotely sensed soil moisture has been proved as reasonable hydrological variables to predict a wetness in the basin, it should be continuously monitored.

• Korean Journal of Soil Science and Fertilizer
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• v.33 no.5
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• pp.311-317
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• 2000

Acid sulfate soil and potential acid sulfate soil material are worldwide in distribution and are problematic in agriculture and environment due to their present and potential acidity developed by the oxidation of sulfides. Most of them are sedimentary origin and a few cases are reported as volcanic or metamorphic origin. We report a potential acid sulfate soil material originated from volcanic activity during Mesozoic. A profile of Bongsan series-weathered nonpyritic andesite-hydrothermally altered pyrite rich andesite was studied with field examination, chemistry, and mineralogy. Once, the pyrite rich andesite was exposed to atmosphere by excavation and leveling works for a residential area and the lay out site had subsequent acidification problem of soil and surface water. The parent material and soil profile of Bongsan series had no signs of presence of pyrite and acid sulfate weathering such as yellow mottles. However, the hydrothermally altered andesite substrata contained significant amount of pyrite showing characteristics of hydrothermal origin such as cubic and pyritohedron morphology and occurrence along cracks.

• Resources Recycling
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• v.15 no.4 s.72
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• pp.44-51
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• 2006

Most electric arc furnace dust (EAFD) treatment processes to recover zinc from EAFD employ carbon as a reducing agent for the zinc oxide in the EAFD. In the present work, the reduction reaction of zinc oxide with carbon in the present of iron oxide was kinetically studied. The experiments were carried out at temperatures between 1173 K and 1373 K under nitrogen atmosphere using a weight-loss technique. From the experimental results, it was concluded that adding the proper amount of iron oxide to the reactant accelerates the reaction rate of zinc oxide with carbon. This is because iron oxide in the reduction reaction of zinc oxide with carbon promotes the carbon gasification reaction. The spherical shrinking core model for a surface chemical reaction control was found to be useful in describing kinetics of the reaction over the entire temperature range. The reaction has an activation energy of 53 kcal/mol (224 kJ/mol) for ZnO-C reaction system, an activation energy of 42 kcal/mol (175 kJ/mol) for $ZnO-Fe_{2}O_{3}-C$ reaction system, and an activation energy of 44 kcal/mol (184 kJ/mol) for ZnO-mill scale-C reaction system.

• Resources Recycling
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• v.13 no.5
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• pp.45-50
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• 2004

To investigate the characteristics of phases formed in iron carbides, super iron carbide was synthesized from hematite fines with $CO-H_2$ gas mixture after reduction under $H_2$ gas at $600^{\circ}C$. Before carburization, the surface of iron powder reduced was pre-treated in the atmosphere of 0.05 vol% $NH_3$-Ar. The synthesized iron carbides were comprehensively explored by C/S analyzer(Low C/S determinator), M$\"{o}$ssbauer spectroscopy, X-ray diffraction patterns(XRD), scanning electron microscopy(SEM), transmission electron microscopy(TEM), and Raman spectroscopy at various reaction time of 5, 10, 15, 20, 25, 30, and 35 min, respectively. By adding a small amount of $NH_3$ gas, the super iron carbides containing 10 wt% carbon were synthesized, and its addition stabilized iron carbides. It was found that the $NH_3$ treatment played a major role in the formation of iron carbide without decomposition($Fe_3C{\to}$3Fe+C) of iron carbides and precipitation of free carbon. It also succeed to synthesize super iron carbide, $Fe_5C_2$, as a stable single phase without involving Fe and $Fe_3C$ phases.

• Korean Journal of Remote Sensing
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• v.24 no.6
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• pp.535-549
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• 2008

Vicarious calibration for the satellite sensor relies on simulated TOA (Top-of-Atmosphere) radiances over various targets. In this study, TOA visible radiance was calculated over ocean targets which are located in five different regions over the Indian and Pacific ocean, and its possible use for the satellite sensor calibration was examined. TOA radiances are simulated with the 6S radiative transfer model for the comparison with MODIS/Terra and SeaWiFS measurements. Geometric angles and sensor characteristics of the reference satellites were taken into account for the simulation. AOT (Aerosol Optical Thickness) from MODIS/Terra, pigment concentrations from Sea WiFS, and ozone amount from OMI measurements were used as inputs to the model. Other atmospheric input parameters such as surface wind and total column water vapor were taken from NCEP/NCAR reanalysis data. The 5-day averaged radiances over all targets show that the percent differences between simulated and observed radiances are within about ${\pm}5%$ in year 2005, indicating that the calculated radiances are in good agreement with satellite measurements. It has also been shown that the algorithm can produce the SeaWiFS radiances within about ${\pm}5%$ uncertainty range. It has been suggested that the algorithm can be used as a tool for calibrating the VIS bands within about 5% uncertainty range.

• Korean Journal of Remote Sensing
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• v.24 no.4
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• pp.309-324
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• 2008

In this study the retrieval algorithms have been developed to retrieve total precipitable water (TPW) from Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) infrared measurements using a physical iterative retrieval method and a split-window technique over East Asia. Retrieved results from these algorithms were validated against Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) over ocean and radiosonde observation over land and were analyzed for investigating the key factors affecting the accuracy of results and physical processes of retrieval methods. Atmospheric profiles from Regional Data Assimilation and Prediction System (RDAPS), which produces analysis and prediction field of atmospheric variables over East Asia, were used as first-guess profiles for the physical retrieval algorithm. We used RTTOV-7 radiative transfer model to calculate the upwelling radiance at the top of the atmosphere. For the split-window technique, regression coefficients were obtained by relating the calculated brightness temperature to the paired radiosonde-estimated TPW. Physically retrieved TPWs were validated against SSM/I and radiosonde observations for 14 cases in August and December 2004 and results showed that the physical method improves the accuracy of TPW with smaller bias in comparison to TPWs of RDAPS data, MODIS products, and TPWs from split-window technique. Although physical iterative retrieval can reduce the bias of first-guess profiles and bring in more accurate TPWs, the retrieved results show the dependency upon initial guess fields. It is thought that the dependency is due to the fact that the water vapor absorption channels used in this study may not reflect moisture features in particular near surface.

• Korean Journal of Remote Sensing
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• v.35 no.5_1
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• pp.625-636
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• 2019

Soil moisture is a representative factor that plays a key role in hydrological cycle. It is involved in the interaction between atmosphere and land surface, and is used in fields such as agriculture and water resources. Advanced Microwave Scanning Radiometer 2 (AMSR2), Advanced SCATterometer (ASCAT), and European Space Agency Climate Change Initiative (ESACCI) data were used to analyze the applicability and uncertainty of satellite soil moisture product in the Korean peninsula. Cumulative distribution function (CDF) matching and triple collocation (TC) analysis were carried out to investigate uncertainty and correction of satellite soil moisture data. Comparisons of pre-calibration satellite soil moisture data with the Automated Agriculture Observing System (AAOS) indicated that ESACCI and ASCAT data reflect the trend of AAOS well. On the other hand, AMSR2 satellite data showed overestimated values during the freezing period. Correction of satellite soil moisture data using CDF matching improved the error and correlation compared to those before correction. Finally, uncertainty analysis of soil moisture was carried out using TC method. Clearly, the uncertainty of the satellite soil moisture, corrected by CDF matching, was diminished in both freezing and thawing periods. Overall, it is expected that using ASCAT and ESACCI rather than AMSR2 soil moisture data will give more accurate soil moisture information when correction is performed on the Korean peninsula.

• Journal of Ecology and Environment
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• v.42 no.4
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• pp.272-277
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• 2018

Background: Studying the ecosystem carbon cycle requires analysis of interrelationships between soil respiration (Rs) and the environment to evaluate the balance. Various methods and instruments have been used to measure Rs. The closed chamber method, which is currently widely used to determine Rs, creates a closed space on the soil surface, measures $CO_2$ concentration in the inner space, and calculates Rs from the increase. Accordingly, the method is divided into automatic or manual chamber methods (ACM and MCM, respectively). However, errors of these methods and differences in instruments are unclear. Therefore, we evaluated the characteristics and difference of Rs values calculated using both methods with actual data. Results: Both methods determined seasonal variation patterns of Rs, reflecting overall changes in soil temperature (Ts). ACM clearly showed detailed changes in Rs, but MCM did not, because such small changes are unknown as Rs values are collected monthly. Additionally, Rs measured using MCM was higher than that using ACM and differed depending on measured plots, but showed similar tendencies with all measurement times and plots. Contrastingly, MCM Rs values in August for plot 4 were very high compared with ACM Rs values because of soil disturbances that easily occur during MCM measurements. Comparing Rs values calculated using monthly means with those calculated using MCM, the ACM calculated values for monthly averages were higher or lower than those of similar measurement times using the MCM. The difference between the ACM and MCM was attributed to greater or lesser differences. These Rs values estimated the carbon released into the atmosphere during measurement periods to be approximately 57% higher with MCM than with ACM, at 5.1 and $7.9C\;ton\;ha^{-1}$, respectively. Conclusion: ACM calculated average values based on various Rs values as high and low for measurement periods, but the MCM produced only specific values for measurement times as representative values. Therefore, MCM may exhibit large errors in selection differences during Rs measurements. Therefore, to reduce this error using MCM, the time and frequency of measurement should be set to obtain Rs under various environmental conditions. Contrastingly, the MCM measurement is obtained during $CO_2$ evaluation in the soil owing to soil disturbance caused by measuring equipment, so close attention should be paid to measurements. This is because the measurement process is disturbed by high $CO_2$ soil concentration, and even small soil disturbances could release high levels into the chamber, causing large Rs errors. Therefore, the MCM should be adequately mastered before using the device to measure Rs.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.16 no.4
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• pp.411-420
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• 2018

This study presents a revised crackling core model for the description of $UO_2$ sphere oxidation in air atmosphere. For close reproduction of the sigmoid behavior exhibited in $UO_2$ to $U_3O_8$ conversion, the fragmentation effect contributing to the increased reactive surface area and the concept of variable grain conversion time were considered in the model development. Under the assumptions of two-step successive reaction of $UO_2{\rightarrow}U_3O_7{\rightarrow}U_3O_8$ and final grain conversion time equivalent to ten times the initial grain conversion time, the revised model showed good agreement with the experimental data measured at 599 - 674 K and a lowest deviation when compared with Nucleation and Growth model and AutoCatalytic Reaction model. The evaluated activation energy at 100% conversion to $U_3O_8$, $57.6kJ{\cdot}mol^{-1}$, was found to be closer to the experimentally extrapolated value than to the value determined in AutoCatalytic Reaction model, $48.6kJ{\cdot}mol^{-1}$.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.158-174
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• 2018

The leaf area index (LAI) is a major factor explaining the photosynthesis of vegetation, evapotranspiration, and energy exchange between the earth surface and atmosphere, and there have been studies on accurate and applicable LAI estimation methods. This study aimed to investigate the relationship between the actual LAI data, UAV image-based vegetation index, canopy height and satellite image (Sentinel-2) LAI and to present an effective LAI estimation method using UAV. As a result, among the six vegetation indices in this study, NDRE ($R^2=0.496$) and CIRE ($R^2=0.443$), which contained red-edge band, showed a high correlation. The application of the canopy height model data to the vegetation index improved the explanatory power of the LAI. In addition, in the case of NDVI, the saturation problem caused by the linear relationship with LAI was addressed. In this study, it was possible to estimate high resolution LAI using UAV images. It is expected that the applicability of such data will be improved if calibration and correction steps are carried out for various vegetation and seasonal images.