• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.107-114
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• 1999

The large-scale distribution of crops Is usually determined by climate. We present the results of a climate-crop prediction based on spatial bio-physical process model approach, implemented in a GIS (Geographic Information System) environment using several regional and global agriculture-environmental databases. The model utilizes daily climate data like temperature, rainfall, solar radiation being generated stocastically by in-built model weather generator to determine the daily biomass and finally the crop yield. Crops are characterized by their specific growing period requirements, photosynthesis, respiration properties and harvesting index properties. Temperature and radiation during the growing period controls the development of each crop. The model simulates geographic/spatial distribution of climate by which a crop-growing belt can also be determined. The model takes both irrigated and non-irrigated area crop productivity into account and the potential increase in productivity by the technical means like mechanization is not considered. All the management input given at the base year 1995 was kept same for the next twenty-year changes until 2015. The simulated distributions of crops under current climatic conditions coincide largely with the current agricultural or specific crop growing regions. Simulation with assumed weather generated derived climate change scenario illustrate changes in the agricultural potential. There are large regional differences in the response across the country. The north-south and east-west regions responded differently with projected climate changes with increased and decreased productivity depending upon the crops and scenarios separately. When water was limiting or facilitating as non-irrigated and irrigated area crop-production effects of temperature rise and higher $CO_2$ levels were different depending on the crops and accordingly their production. Rise in temperature led to yield reduction in case of maize and rice whereas a gain was observed for wheat crop, doubled $CO_2$ concentration enhanced yield for all crops and their several combinations behaved differently with increase or decrease in yields. Finally, with this spatial modeling approach we succeeded in quantifying the crop productivity which may bring regional disparities under the different climatic scenarios where one region may become better off and the other may go worse off.

• Environmental and Resource Economics Review
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• v.13 no.1
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• pp.83-117
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• 2004

This study investigates the spatial distributions of the ambient levels of air pollutants ($SO_2$, $NO_2$, $O_3$, CO, and PM) in Seoul metropolitan area using the data obtained by the air pollution observation stations. This study estimated a non-parametric kernel density function and two types of inequality indices, Gini and Entropy. Our estimation results show that the degree of inequality in spatial distribution of air pollution, in general, tends to be stable or slightly decreasing for the period of 1990~2001. In addition, we found that there are significant dynamics of air pollution levels in terms of spatial ranking.

• Proceedings of the Korea Water Resources Association Conference
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• 1998.05b
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• pp.7-13
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• 1998

A methodology to analyze and quantify regional meteorological drough based on annual precipitation data has been introduced in this paper In this study, based on posterior probability estimator and Bayesian classifier in Spatial Analysis Neural Network ISANN), point drought probabilities categorized as extreme, severe, mild, and non drought events has been defined, and a Bayesian Drought Severity Index (BPSI) has been introduced to classify the region of interest into four drought serverities. For example, the proposed methodology has been applied to analyze the regional drought of South Korea. This is a new method to classify and quantify the spatial or regional drought based on neural network pattern recognition technique and the results show that it may be apprepriate and valuable to analyze the spatial drought.

• Proceedings of the Safety Management and Science Conference
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• 2006.04a
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• pp.471-484
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• 2006

The focus of analysis is effect on Non-electrical Machinery and Equipment of Macroeconomic variables through long-term and short-term periods. Also, this paper is related with implication on steady growth possibility of Non-electrical Machinery and Equipment. The period of variables is from 1985 to April in 2005. In case of not-available data is treated as missing figures. As spatial scope, these data are Non-electrical Machinery and Equipment on the basis of KSIC. In case of items, it composes MTI 1&3 digit of Korea International Trade Association (KITA), on the basis of HSK & classification of Korea Machinery industries. According to Granger causality test, yield of Cooperate Bond and export amount of Machinery have a meaning at statistical Confidence level of 10%. In case of index of the unit cost of export and export amount of Machinery, they have an interactive Granger cause. In yen dollar exchange rate and export amount of Machinery, former variable gives an unilateral Granger cause to latter that.

• Journal of Advanced Marine Engineering and Technology
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• v.34 no.1
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• pp.183-194
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• 2010

A suitability analysis for marine afforestation was carried out on physical items based on slop rate, bottom sediment, light intensity, velocity, and wave at north Geomoon waters in Korea. The data from each physical item were changed to a GSDM (Gridded Spatial Distribution Map) using Kriging interpolation. A GSDM grid includes information, and each grid was given a SI (suitability index) of 3 grades(SI of first suitability was 100, SI of second suitability was 50, and non-suitability had no SI). According to the analysis results of all overlaid GSDM, first suitability had 500 SI, and suitability area was 0.25ha. Second and third suitability had 400~450 SI, and suitability area was 2.36ha, 1.80ha, respectively. Therefore, the results suggest that reefs installed for marine afforestation should be anti-slip types against steep slope, and the target species need to include algae with low compensation light intensity in second and third suitability.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.458-458
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• 2012

Climate extreme variability is a major cause of disaster such as flood and drought types occurred in Korea and its effects is also more severe damage in last decades which can be danger mature events in the future. The main aim of this study was to assess the effectives of climate change on drought for an agriculture as Nakdong basin in Korea using climate change data in the future from data of General Circulation Models (GCM) of ECHO-G, with the developing countries like Korea, the developed climate scenario of medium-high greenhouse gas emission was proposed of the SRES A2. The Standardized Precipitation Index (SPI) was applied for drought evaluation. The drought index (SPI) applied for sites in catchment and it is evaluated accordingly by current and future precipitation data, specific as determined for data from nine precipitation stations with data covering the period 1980-2009 for current and three periods 2010-2039, 2040-2069 and 2070-2099 for future; time scales of 3month were used for evaluating. The results determined drought duration, magnitude and spatial extent. The drought in catchment act intensively occurred in March, April, May and November and months of drought extreme often appeared annual in May and November; drought frequent is a non-uniform cyclic pattern in an irregular repetitive manner, but results showed drought intensity increasing in future periods. The results indicated also spatial point of view, the SPI analysis showed two of drought extents; local drought acting on one or more one of sites and entire drought as cover all of site in catchment. In addition, the meteorology drought simulation maps of spatial drought representation were carried out with GIS software to generate for some drought extreme years in study area. The method applied in this study are expected to be appropriately applicable to the evaluation of the effects of extreme hydrologic events, the results also provide useful for the drought warning and sustainable water resources management strategies and policy in agriculture basins.

• Steel and Composite Structures
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• v.31 no.1
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• pp.43-51
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• 2019

This paper is concerned with the numerical calculation of mixed-mode stress intensity factors (SIFs) of 2-D isotropic functionally graded materials (FGMs) by the natural element method (more exactly, Petrov-Galerkin NEM). The spatial variation of elastic modulus in non-homogeneous FGMs is reflected into the modified interaction integral ${\tilde{M}}^{(1,2)}$. The local NEM grid near the crack tip is refined, and the directly approximated strain and stress fields by PG-NEM are enhanced and smoothened by the patch recovery technique. Two numerical examples with the exponentially varying elastic modulus are taken to illustrate the proposed method. The mixed-mode SIFs are parametrically computed with respect to the exponent index in the elastic modulus and external loading and the crack angle and compared with the other reported results. It has been justified from the numerical results that the present method successfully and accurately calculates the mixed-mode stress intensity factors of 2-D non-homogeneous functionally graded materials.

• Journal of Environmental Impact Assessment
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• v.22 no.5
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• pp.467-479
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• 2013

This study was conducted to find out characterization of spatial distribution of birds observed in river areas. Our bird survey was carried out 4 times at 31 sites from January to September in 2011. A total of 1,609 accumulated individuals belonging to 59 species, 28 families and 11 orders were observed. In the result of spatial autocorrelation analysis using the richness index of the maximum counts of each sites, we confirmed that the distribution of birds in Namdaecheon river was clustered and the tendency of spatial autocorrelation was apparent. The area of each sites within a 200m radius was classified in four biotope categories such as agricultural land, forest, residential area and water area, and the spatial autocorrelation was analysed about four types. In the result of spatial autocorrelation analysis for four biotope categories, all types were showed the positive spatial autocorrelation, but the type of water area was higher than other types. The positive correlation was found between the water area and water birds in statistical significance. However, the forest birds had non-significance values. Therefore, it is appropriate to focus on water birds except for forest birds, when researches of bird distribution in river ecosystem is conducted. The number of bird species and individuals increased as the riverside of water area was to widen. Thus, if the areas of riverside offering the feeding and roosting area increase, it will be accommodated many birds. Also, the areas of riverside should be maintained naturally because it is an important habitats of birds. Our study area is on the outskirts the city of higher rates of forest and agricultural land, it may be unreasonable to apply our results to the whole rivers. If the research about the river flowing around the city will be conducted, it is expected to be useful to the relation study area such as ecological river's restoration.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.424-424
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• 2017

Several studies of the world have analyzed the regional rainfall trends in large data sets. However, it reported that the long-term behavior of rainfall was different on spatial and temporal scales. The objective of this study is to determine the local trends of rainfall indices in the Yom River Basin, Thailand. The rainfall indices consist of the annual total precipitation (PRCTPOP), number of heavy rainfall days ($R_{10}$), number of very heavy rainfall days ($R_{20}$), consecutive of dry days (CDD), consecutive of wet days (CWD), daily maximum rainfall ($R_{x1}$), five-days maximum rainfall ($R_{x5}$), and total of annual rainy day ($R_{annual}$). The rainfall data from twelve hydrological stations during the period 1965-2015 were used to analysis rainfall trend. The Mann-Kendall test, which is non-parametric test was adopted to detect trend at 95 percent confident level. The results of these data were found that there is only one station an increasing significantly trend in PRCTPOP index. CWD, which the index is expresses longest annual wet days, was exhibited significant negative trend in three locations. Meanwhile, the significant positive trend of CDD that represents longest annual dry spell was exhibited four locations. Three out of thirteen stations had significant decreasing trend in $R_{annual}$ index. In contrast, there is a station statistically significant increasing trend. The analysis of $R_{x1}$ was showed a station significant decreasing trend at located in the middle of basin, while the $R_{x5}$ of the most locations an insignificant decreasing trend. The heavy rainfall index indicated significant decreasing trend in two rainfall stations, whereas was not notice the increase or decrease trends in very heavy rainfall index. The results of this study suggest that the trend signal in the Yom River Basin in the half twentieth century showed the decreasing tendency in both of intensity and frequency of rainfall.

• Journal of Korea Water Resources Association
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• v.32 no.1
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• pp.15-29
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• 1999

A new methodology to analyze and quantify regional meteorological drought based on annual precipitation data has been introduced in this paper In this study, based on posterior probability estimator and Bayesian classifier in Spatial Analysis Neural Network (SANN), point drought probabilities categorized as extreme, severe, mild, and non drought events has been defined, and a Bayesian Drought Severity Index (BPSI) has been introduced to classify the region of interest into four drought severities. In addition, to estimate the regional drought severity for the entire region, regional extreme, severe, mild, and non drought probabilities which are the areal averages of point drought probabilities over the region has been computed and applied. In this study, the proposed methodology has been applied to analyze the regional drought of South Korea during 1967-1996 years. The drought severity for the whole South Korea was defined spatially at each year and each year was classified in a drought severity criterion. The results may be useful for water manager to understand the South Korean drought with respect to the spatial and temporal variation.