• Environmental Engineering Research
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• v.22 no.4
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• pp.369-376
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• 2017

The trend analysis of the study was acquired by selecting multiyear monthly groundwater table data and monitors the wells in each sub-district under the study area. The intention of this research was to analyze the outcome of the non-parametric Mann-Kendall test at greater than the significance level which is 95% of groundwater level in Sylhet. The aptitude is effective at two conjunctures where the confidence bounds are 95% and it meets the estimate line of Sen's. To calculate and assess the spatial differences in the inanition of groundwater table, geostatistical methods was applied based on data from 27 groundwater wells during the period from January 1975 to December 2011 which were obtained from a secondary source, Bangladesh Water Development Board. The geographic information system was used to assess the spatial change in order to find the level of groundwater. Cross-validation errors were found within an advisable level in estimating the groundwater depth with different interpolation models of ordinary kriging methods. Finally, surface maps were generated with the best-fitted model. The southeast region was found highly vulnerable from groundwater level point of view. Northern region was detected highest hazard prone area for diverge groundwater using kriging method.

• Geomechanics and Engineering
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• v.7 no.6
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• pp.589-612
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• 2014

This study includes determination of liquefaction potential in Erzincan city center. Erzincan Province is situated within first-degree earthquake zone on earthquake map of Turkey. In this context, the earthquake scenarios were produced using the empirical expressions. Liquefaction potential for different earthquake magnitudes (6.0, 6.5, 7.0) were determined. Liquefaction potential was investigated using Standard Penetration Test (SPT). Liquefaction potential analyses are determined in two steps: geotechnical investigations and calculations. In the first steps, boreholes were drilled to obtain disturbed and undisturbed soil samples and SPT values were obtained. Laboratory tests were made to identify geotechnical properties of soil samples. In the second step, liquefaction potential analyses were examined using two methods, namely Seed and Idriss (1971), Iwasaki et al. (1981). The liquefaction potential broadly classified into three categories, namely non-liquefiable, marginally liquefiable and liquefiable regions. Additionally, the liquefaction potential index classified into four categories, namely non-liquefiable, low, high and very high liquefiable regions. In order to liquefaction analysis complete within a short time, MATLAB program were prepared. Following the analyses, liquefaction potential index is investigated by Iwasaki et al. (1982) methods. At the final stage of this study, liquefaction potential maps and liquefaction potential index maps of the all study area by using IDW (inverse distance weighted) interpolation method in Geostatistical Analyst Module of ArcGIS 10.0 Software were prepared for different earthquake magnitudes and different depths. The results of soil liquefaction potential were evaluated in ArcGIS to map the distributions of drillings with liquefaction potential. The maps showed that there is a spatial variability in the results obtained which made it difficult to clearly separate between regional areas of high or low potential to liquefy. However, this study indicates that the presence of ground water and sandy-silty soils increases the liquefaction potential with the seismic features of the region.

• Journal of Climate Change Research
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• v.6 no.4
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• pp.331-344
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• 2015

A long-term gridded historical data at 3 km spatial resolution has been generated for practical regional applications such as hydrologic modelling. However, overly high or low values have been found at some grid points where complex topography or sparse observational network exist. In this study, the Inverse Distance Weighting (IDW) method was applied to properly smooth the overly predicted values of Improved GIS-based Regression Model (IGISRM), called the IDW-IGISRM grid data, at the same resolution for daily precipitation, maximum temperature and minimum temperature from 2001 to 2010 over South Korea. We tested various effective distances in the IDW method to detect an optimal distance that provides the highest performance. IDW-IGISRM was compared with IGISRM to evaluate the effectiveness of IDW-IGISRM with regard to spatial patterns, and quantitative performance metrics over 243 AWS observational points and four selected stations showing the largest biases. Regarding the spatial pattern, IDW-IGISRM reduced irrational overly predicted values, i. e. producing smoother spatial maps that IGISRM for all variables. In addition, all quantitative performance metrics were improved by IDW-IGISRM; correlation coefficient (CC), Index Of Agreement (IOA) increase up to 11.2% and 2.0%, respectively. Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were also reduced up to 5.4% and 15.2% respectively. At the selected four stations, this study demonstrated that the improvement was more considerable. These results indicate that IDW-IGISRM can improve the predictive performance of IGISRM, consequently providing more reliable high-resolution gridded data for assessment, adaptation, and vulnerability studies of climate change impacts.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.2
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• pp.3-13
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• 2012

This study evaluated the feasibility of the location for PM-10 Monitoring Stations utilizing through GIS analysis. In addition, optimal sites were investigated to properly manage PM-10 which are closely related with public health. There are 11 PM-10 monitoring stations in Daegu area and the PM-10 data monitored at these stations are utilized to understand the overall status of PM-10 pollution. However, there are contrastive issues on the locations of current monitoring stations. Thus, this study prepared the map of PM-10 concentrations in Daegu area using IDW and Kriging techniques. Furthermore, average PM-10 concentrations were calculated using zonal statistical methods according to legal divisions and then, the current monitoring stations were evaluated whether their location is appropriate or not for PM-10 pollution distribution. It was found that, on the basis of yearly, seasonal and daily concentration analysis, the location of current PM-10 monitoring stations were not appropriate, particularly as they could not represent regional PM-10 pollution characteristics. In order to supplement this deficiency, seven sites(Namsandong, Namildong, Dongildong, Buksungro 1, Jongro 1, Hyangchondong and Haejeondong) commonly selected from each analytical step are suggested as additional PM-10 monitoring sites. It is further suggested that this kind of scientific evaluation for the location of PM-10 monitoring stations are needed in order to properly manage public heath in other cities as well as Daegu area.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.3
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• pp.146-155
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• 2006

A handful of previous studies have attempted to integrate socioeconomic data and remotely sensed data for urban quality of life assessment with their spatial dimension in a zonal unit. However, such a zone-based approach not only has the unrealistic assumption that all attributes of a zone are uniformly spatially distributed throughout the zone, but also has resulted in serious methodological difficulties such as the modifiable areal unit problem and the incompatibility problem with environmental data. An alternative to the zone-based approach can be a pixel-based approach which gets its spatial dimension through a pixel. This paper proposes a pixel-based approach to linking remotely sensed data with socioeconomic data in GIS for urban quality of life assessment. The pixel-based approach uses dasymetric mapping and spatial interpolation to spatially disaggregate socioeconomic data and integrates remotely sensed data with spatially disaggregated socioeconomic data for the quality of life assessment. This approach was implemented and compared with a zone-based approach using a case study of Fulton County, Georgia. Results indicate that the pixel-based approach allows for the calculation of a microscale indicator in the urban quality of life assessment and facilitates efficient data integration and visualization in the assessment although it costs an intermediate step with more processing time such as the disaggregation of zonal data. The results also demonstrate that the pixel-based approach opens up the potential for the development of new database and increased analytical capabilities in urban analysis.

• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.3
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• pp.170-176
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• 2004

This study was carried out to establish a spatial decision support system for evaluating climatic aspects of a given geographic location in complex terrains with respect to the quality apple production. Monthly climate data from S6 synoptic stations across South Korea were collected for 1971-2000. A digital elevation model (DEM) with a 10-m cell spacing was used to spatially interpolate daily maximum and minimum temperatures based on relevant topoclimatological models applied to Jangsoo county in Korea. 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. Freezing risk in January was estimated under the recurrence intervals of 30 years. Frost risk at bud-burst and blossom was also estimated. Fruit quality was evaluated for soluble solids, anthocyanin content, Hunter L and A values, and LID ratio, which were expressed as empirical functions of temperature based on long-term field observations. AU themes were prepared as ArcGlS Grids with a 10-m cell spacing. Analysis showed that 11 percent of the whole land area of Jangsoo county might be suitable for quality 'Fuji' apple production. A computer program (MAPLE) was written to help utilize the results in decision-making for site-selection of new orchards in this region.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.1
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• pp.98-112
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• 2017

Recently, various research has been conducted on the use of a game engine instead of a commercial geographic information system (GIS) engine for the development of 3D GIS. The advantage of the 3D game engine is that it allows developers to develop various modules according to their abilities. In particular, in the area of disasters, a wide range of alternatives for prevention as well as prediction can be presented when new analyses are attempted by combining geographic information and disaster-related information. Furthermore, 3D analysis can be an important factor in analyzing the phenomena occurring in the real 3D world because of the nature of disasters. Therefore, in this study, we tried to develop a visualization module for flood disaster information through a 3D game engine by considering the solutions for cost and manpower problems and the degree of freedom of development. Raw flood data was mapped onto spatial information and interpolation was performed for the natural display of the mapped flood information. Furthermore, we developed a module that intuitively shows dangerous areas to users by generating cumulative information in order to display multidimensional information based on this information. The results of this study are expected to enable various flood information analyses as well as quick response and countermeasures to floods.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.4
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• pp.47-58
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• 2016

The purpose of this study was to select the sectoral vulnerable areas index in welfare field and analyze the socially vulnerable areas from comprehensive analysis. For this study, preceding research and theoretical background were reviewed. Through this, we selected for the analysis index and criteria, and data corresponding to the index are collected. Based on the index and criteria, the data analysis was performed in Seoul Metropolitan City selected as the spatial extent of this study. From the results of analysis, the sectoral lower rank 10% of social vulnerable areas was determined. In addition, Junggu, Yongsangu, and Seodaemungu from the comprehensive analysis of individual vulnerable areas were derived as a final vulnerable areas. In particular, Junggu was weak in all sectors; Yongsangu was in the medical sector; and Seodaemungu was poor in housing and education. Lower vulnerability index of all sectors (energy, housing, medical, transportation, and education) in 1st, 2nd, and 3rd residential areas by examining use zoning was showed. From the results of this study, we can expect time and labor saving of policy support in public sector.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.669-678
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• 2018

This study developed information technology infrastructures for building a driving environment analysis platform using various big data, such as vehicle sensing data, public data, etc. First, a small platform server with a parallel structure for big data distribution processing was developed with H/W technology. Next, programs for big data collection/storage, processing/analysis, and information visualization were developed with S/W technology. The collection S/W was developed as a collection interface using Kafka, Flume, and Sqoop. The storage S/W was developed to be divided into a Hadoop distributed file system and Cassandra DB according to the utilization of data. Processing S/W was developed for spatial unit matching and time interval interpolation/aggregation of the collected data by applying the grid index method. An analysis S/W was developed as an analytical tool based on the Zeppelin notebook for the application and evaluation of a development algorithm. Finally, Information Visualization S/W was developed as a Web GIS engine program for providing various driving environment information and visualization. As a result of the performance evaluation, the number of executors, the optimal memory capacity, and number of cores for the development server were derived, and the computation performance was superior to that of the other cloud computing.

• Journal of the Korean association of regional geographers
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• v.11 no.6
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• pp.530-542
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• 2005

In this study, GIS method has been used to get fractal characteristics. Using the projected area and surface area, 2 dimensional fractal characteristic of terrain was found out. Correlation of fractal dimension and mean slope were also checked over. Results are as below. 1) To get a fractal dimension, the method which is using the surface area is also directly proportional to complexity of the terrain as other fractal dimension. 2) Fractal dimensions using the surface area, that is proposed in this thesis are carried out as below : Uiseong : $2.02{\sim}2.15$ Yeongcheon : $2.10{\sim}2.24$. These values are in a range of fractal $2.10{\sim}2.20$ dimensions which has known. 3) Correlation of mean slope and fractal dimension is diminished about 30% in a region which is more than $25^{\circ}$ of mean slope. So, in this region using the fractal dimension method is better than using the mean slope. From this study, on formula using the projected area and surface area is still good to get a fractal dimension that has been found. But to confirm this method the region of research should be wider and be set up the correlation of mean slope, surface area and fractal dimension. It can be applicable to restoration of terrain and traffic flow analysis in the future research.