• Korean Journal of Remote Sensing
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• v.14 no.1
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• pp.53-68
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• 1998

Observation of hydrometeors' behavior in the atmosphere is important to understand weather and climate. By conventional observations, we can get the distribution of water vapor at limited number of points on the earth. In this study, the precipitable water has been estimated from the split window channel data on GMS-5 based upon the technique developed by Chesters et al.(1983). To retrieve the precipitable water, water vapor absorption parameter depending on filter function of sensor has been derived using the regression analysis between the split window channel data and the radiosonde data observed at Osan, Pohang, Kwangiu and Cheju staions for 4 months. The air temperature of 700 hPa from the Global Spectral Model of Korea Meteorological Administration (GSM/KMA) has been used as mean air temperature for single layer radiation model. The retrieved precipitable water for the period from August 1996 through December 1996 are compared to radiosonde data. It is shown that the root mean square differences between radiosonde observations and the GMS-5 retrievals range from 0.65 g/$cm^2$ to 1.09 g/$cm^2$ with correlation coefficient of 0.46 on hourly basis. The monthly distribution of precipitable water from GMS-5 shows almost good representation in large scale. Precipitable water is produced 4 times a day at Korea Meteorological Administration in the form of grid point data with 0.5 degree lat./lon. resolution. The data can be used in the objective analysis for numerical weather prediction and to increase the accuracy of humidity analysis especially under clear sky condition. And also, the data is a useful complement to existing data set for climatological research. But it is necessary to get higher correlation between radiosonde observations and the GMS-5 retrievals for operational applications.

• Korean Journal of Soil Science and Fertilizer
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• v.39 no.6
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• pp.329-333
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• 2006

Most of volcanic ash soils in South Korea are distributed in Jeju province which is an island placed on southern part of Korea and has steep slope mountain area. There are many soils containing high contents of organic matter (OM) derived from volcanic ash in Jejudo, also. Therefore, irrigation and drainage in volcanic ash soil different with general soil which has low OM content have to be applied with another management way, but studies searching appropriate methods for them are set on insufficient situation because the area of volcanic ash soil in South Korea is only 1.3% (130,000ha). This study was conducted for analysis of soil water content and irrigation quantity appropriate for crops cultivated in volcanic ash soil with high OM content. Although soils with different soil color have the same soil texture, soil water characteristics curve by soil color showed the difference of water retention capability by OM content. But, this characteristics classified with soil color could be unified by scaling technique with similitude analysis method which get dimensionless water content using a present water content, a residual water content and saturated water content (or water content at 10kPa). A relation of gravimetric soil water content (GSWC) and dimensionless water content by the results showed a form of power function. The dimensionless water content (DWC) express a relative saturation degree of present water content. This was also expressed by van Genuchten model which describe the relation between relative saturation degrees and matric potentials. These results on soil water characteristics curve (SWCC) of volcanic ash soil will be the basic of irrigation plan in area having high organic contents into soil.

• Journal of Life Science
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• v.31 no.9
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• pp.840-848
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• 2021

This study was conducted to estimate annual trends and the environmental effects in the racing records of Jeju horses. The Korean Racing Authority (KRA) collected 48,645 observations for 2,167 Jeju horses from 2002 to 2019. Racing records were preprocessed to eliminate errors that occur during the data collection. Racing times were adjusted for comparison between race distances. A stepwise Akaike information criterion (AIC) variable selection method was applied to select appropriate environment variables affecting racing records. The annual improvement of the race time was -0.242 seconds. The model with the lowest AIC value was established when variables were selected in the following order: year, budam classification, jockey ranking, trainer ranking, track condition, weather, age, and gender. The most suitable model was constructed when the jockey ranking and age variables were considered as random effects. Our findings have potential for application as basic data when building models for evaluating genetic abilities of Jeju horses.

• Korea Real Estate Review
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• v.28 no.1
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• pp.79-90
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• 2018

The purpose of this study was to estimate the pricing factors of residential lands in new cities by estimating the pricing model of residential lands. For this purpose, hedonic equations for each quantile of the conditional distribution of land prices were estimated using quantile regression methods and the sale price date of Jangyu New Town in Gimhae. In this study, a quantile regression method that models the relation between a set of explanatory variables and each quantile of land price was adopted. As a result, the differences in the effects of the characteristics by price quantile were confirmed. The number of years that elapsed after the completion of land construction is the quadratic effect in the model because its impact may give rise to a non-linear price pattern. Age appears to decrease the price until certain years after the construction, and increases the price afterward. In the estimation of the quantile regression, land age appears to have a statistically significant impact on land price at the traditional level, and the turning point appears to be shorter for the low quantiles than for the higher quantiles. The positive effects of the use of land for commercial and residential purposes were found to be the biggest. Land demand is preferred if there are more than two roads on the ground. In this case, the amount of sunshine will improve. It appears that the shape of a square wave is preferred to a free-looking land. This is because the square land is favorable for development. The variables of the land used for commercial and residential purposes have a greater impact on low-priced residential lands. This is because such lands tend to be mostly used for rental housing and have different characteristics from residential houses. Residential land prices have different characteristics depending on the price level, and it is necessary to consider this in the evaluation of the collateral value and the drafting of real estate policy.

• Korean Journal of Heritage: History & Science
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• v.51 no.2
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• pp.138-153
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• 2018

The purpose of this study was to analyze , which was made in the late Joseon Dynasty to specify the vegetation landscape of the Donhwamun Gate area in Changdeokgung Palace. The study results can be summarized as below. First, based on "Jieziyuan Huazhuan(芥子園畵傳)", the introductory book of tree expression delivered from China in the 17th century, allowed the classification criteria of the trees described in the picture to be established and helped identify their types. As a result of the classification, there were 10 species and 50 trees in the Donhwamun Gate area of . Second, it was possible to measure the real size of the trees described in the picture through the elevated drawing scale of . The height of the trees ranged from a minimum of 4.37 m to a maximum of 22.37 m. According to the measurement results, compared to the old trees currently living in Changdeokgung Palace, the trees described in the picture were found to be produced in almost actual size without exaggeration. Thus, the measured height of the trees turned out to be appropriate as baseline data for reproduction of the vegetation landscape. Third, through the Rubber Sheeting Transformation of , it was possible to make a ground plan for the planting of on the current digital topographic map. In particular, as the transformed area of was departmentalized and control points were added, the precision of transformation improved. It was possible to grasp the changed position of planting as well as the change in planting density through a ground plan of planting of . Lastly, it was possible to produce a three-dimensional vegetation landscape model by using the information of the shape of the trees and the ground plan for the planting of . Based on the three-dimensional model, it was easy to examine the characteristics of the three-dimensional view of the current vegetation via the view axis, skyline, and openness to and cover from the adjacent regions at the level of the eyes. This study is differentiated from others in that it verified the realism of and suggested the possibility of ascertaining the original form of the vegetation landscape described in the painting.

• International Area Studies Review
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• v.21 no.4
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• pp.41-63
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• 2017

FDI can either be absorbed in the production cycle with domestic investment and create an inducement effect or it can remain as an exogenous factor and increase the volatility of GDP. The purpose of this paper is to research these different impacts that FDI could have. For that, the endogenous growth theory was employed. The statistic method used are the panel model for sectoral analysis, and GARCH model and VAR for time series analysis. Myanmar was selected as this paper's research subject because it is one of countries which had a colossal amount of FDI inflow recently. The panel analysis did not confirm the causality between sectoral FDI and sectoral GDP. The reason for this could be in the lack of data, since sectoral data exists yearly only during 2006-2016. Therefore this study conducted the times series analysis. According to the results, during 2006 until 2010, it showed signs of GARCH but the effect of FDI on GDP was nonexistent, which means FDI was not integrated into the domestic production cycle but stayed in residual terms. During 2011 to 2016, FDI seemed to affect the growth of Myanmar's GDP. The estimation confirmed the existence of GARCH and the Granzer causality test confirmed that FDI influenced the GARCH, which signified FDI increased the volatility of GDP. The VAR analysis showed responses of GDP to FDI was small(about 0.0007). This research assumes that FDI can be divided in two parts: one part which can be assimilated in the domestic production cycle and the other where it stays outside of the production cycle. The former creates production inducement effect and the latter only increases the volatility of GDP. According to this study, the latter outweighs the former impact in Myanmar.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.5
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• pp.431-449
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• 2022

As many tunnels generally have been constructed, various experiences and techniques have been accumulated for tunnel design as well as tunnel construction. Hence, there are not a few cases that, for some usual tunnel design works, it is sufficient to perform the design by only modifying or supplementing previous similar design cases unless a tunnel has a unique structure or in geological conditions. In particular, for a tunnel blast design, it is reasonable to refer to previous similar design cases because the blast design in the stage of design is a preliminary design, considering that it is general to perform additional blast design through test blasts prior to the start of tunnel excavation. Meanwhile, entering the industry 4.0 era, artificial intelligence (AI) of which availability is surging across whole industry sector is broadly utilized to tunnel and blasting. For a drill and blast tunnel, AI is mainly applied for the estimation of blast vibration and rock mass classification, etc. however, there are few cases where it is applied to blast pattern design. Thus, this study attempts to automate tunnel blast design by means of machine learning, a branch of artificial intelligence. For this, the data related to a blast design was collected from 25 tunnel design reports for learning as well as 2 additional reports for the test, and from which 4 design parameters, i.e., rock mass class, road type and cross sectional area of upper section as well as bench section as input data as well as16 design elements, i.e., blast cut type, specific charge, the number of drill holes, and spacing and burden for each blast hole group, etc. as output. Based on this design data, three machine learning models, i.e., XGBoost, ANN, SVM, were tested and XGBoost was chosen as the best model and the results show a generally similar trend to an actual design when assumed design parameters were input. It is not enough yet to perform the whole blast design using the results from this study, however, it is planned that additional studies will be carried out to make it possible to put it to practical use after collecting more sufficient blast design data and supplementing detailed machine learning processes.

• Journal of Korea Port Economic Association
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• v.38 no.3
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• pp.105-131
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• 2022

Even after the improvement in 2019, UNCTAD's Liner Shipping Connectivity Index (LSCI), which evaluates the performance of the global container port market, has limited use. In particular, since the liner shipping connectivity index evaluates the performance based only on the distance of the relationship, the performance index combining the port attractiveness of calling would be more efficient. This study used the modified Huff model, the hub-authority algorithm and the eigenvector centrality of social network analysis, and correlation analysis for 2007, 2017, and 2019 data of Ocean-Commerce, Japan. The findings are as follows: Firstly, the port attractiveness of calling and the overall performance of the port did not always match. However, according to the analysis of the attractiveness of a port calling, Busan remained within the top 10. Still, the attractiveness among other Korean ports improved slowly from the low level during the study period. Secondly, Global container ports are generally specialized for long-term specialized inbound and outbound ports by the route and grow while maintaining professionalism throughout the entire period. The Korean ports continue to change roles from analysis period to period. Lastly, the volume of cargo by period and the extended port connectivity index (EPCI) presented in this study showed a correlation from 0.77 to 0.85. Even though the Atlantic data is excluded from the analysis and the ship's operable capacity is used instead of the port throughput volume, it shows a high correlation. The study result would help evaluate and analyze global ports. According to the study, Korean ports need a long-term strategy to improve performance while maintaining professionalism. In order to maintain and develop the port's desirable role, it is necessary to utilize cooperation and partnerships with the complimentary port and attract shipping companies' services calling to the complementary port. Although this study carried out a complex analysis using a lot of data and methodologies for an extended period, it is necessary to conduct a study covering ports around the world, a long-term panel analysis, and a scientific parameter estimation study of the attractiveness analysis.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.655-667
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• 2023

Algal bloom outbreaks are frequently reported around the world, and serious water pollution problems arise every year in Korea. It is necessary to protect the aquatic ecosystem through continuous management and rapid response. Many studies using satellite images are being conducted to estimate the concentration of chlorophyll-a (Chl-a), an indicator of algal bloom occurrence. However, machine learning models have recently been used because it is difficult to accurately calculate Chl-a due to the spectral characteristics and atmospheric correction errors that change depending on the water system. It is necessary to consider the factors affecting algal bloom as well as the satellite spectral index. Therefore, this study constructed a dataset by considering water quality, hydrological and meteorological factors, and sentinel-2 images in combination. Representative ensemble models random forest and extreme gradient boosting (XGBoost) were used to predict the concentration of Chl-a in eight weirs located on the Nakdong river over the past five years. R-squared score (R²), root mean square errors (RMSE), and mean absolute errors (MAE) were used as model evaluation indicators, and it was confirmed that R² of XGBoost was 0.80, RMSE was 6.612, and MAE was 4.457. Shapley additive expansion analysis showed that water quality factors, suspended solids, biochemical oxygen demand, dissolved oxygen, and the band ratio using red edge bands were of high importance in both models. Various input data were confirmed to help improve model performance, and it seems that it can be applied to domestic and international algal bloom detection.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.933-948
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• 2023

Atmospheric aerosols not only have adverse effects on human health but also exert direct and indirect impacts on the climate system. Consequently, it is imperative to comprehend the characteristics and spatiotemporal distribution of aerosols. Numerous research endeavors have been undertaken to monitor aerosols, predominantly through the retrieval of aerosol optical depth (AOD) via satellite-based observations. Nonetheless, this approach primarily relies on a look-up table-based inversion algorithm, characterized by computationally intensive operations and associated uncertainties. In this study, a novel high-resolution AOD direct retrieval algorithm, leveraging machine learning, was developed using top-of-atmosphere reflectance data derived from the Geostationary Ocean Color Imager-II (GOCI-II), in conjunction with their differences from the past 30-day minimum reflectance, and meteorological variables from numerical models. The Light Gradient Boosting Machine (LGBM) technique was harnessed, and the resultant estimates underwent rigorous validation encompassing random, temporal, and spatial N-fold cross-validation (CV) using ground-based observation data from Aerosol Robotic Network (AERONET) AOD. The three CV results consistently demonstrated robust performance, yielding R²=0.70-0.80, RMSE=0.08-0.09, and within the expected error (EE) of 75.2-85.1%. The Shapley Additive exPlanations(SHAP) analysis confirmed the substantial influence of reflectance-related variables on AOD estimation. A comprehensive examination of the spatiotemporal distribution of AOD in Seoul and Ulsan revealed that the developed LGBM model yielded results that are in close concordance with AERONET AOD over time, thereby confirming its suitability for AOD retrieval at high spatiotemporal resolution (i.e., hourly, 250 m). Furthermore, upon comparing data coverage, it was ascertained that the LGBM model enhanced data retrieval frequency by approximately 8.8% in comparison to the GOCI-II L2 AOD products, ameliorating issues associated with excessive masking over very illuminated surfaces that are often encountered in physics-based AOD retrieval processes.