• Korean Journal of Remote Sensing
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• v.36 no.1
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• pp.83-92
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• 2020

The purpose of this work was to apply geographical information system (GIS) for geostatistical analyzing by selecting a semi-variogram model to quantify the spatial correlation of the population distribution with residential neighborhoods in the both sides of Mosul city. Two hundred and sixty-eight sample sites in 240 ㎢ are adopted. After determining the population distribution with respect to neighborhoods, data were inserted to ArcGIS10.3 software. Afterward, the datasets was subjected to the semi-variogram model using ordinary kriging interpolation. The results obtained from interpolation method showed that among the various models, Spherical model gives best fit of the data by cross-validation. The kriging prediction map obtained by this study, shows a particular spatial dependence of the population distribution with the neighborhoods. The results obtained from interpolation method also indicates an unbalanced population distribution, as there is no balance between the size of the population neighborhoods and their share of the size of the population, where the results showed that the right side is more densely populated because of the small area of residential homes which occupied by more than one family, as well as the right side is concentrated in economic and social activities.

• 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 the Korean Association of Geographic Information Studies
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• v.9 no.1
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• pp.168-178
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• 2006

In recent years, an ingress of mass jellyfish into cooling water intake system causes interruption of electric power production at the Uljin nuclear power plant. Therefore, monitering and forecast on the mass ingress of marine organisms are demanded as one of the early preventing measurements. Sea water movement is a major factor on the ingress of marine organisms like Moon jellyfish which has weak self-mobile ability. When sea surface flow direction adjacent to the Uljin is the northwest, the jellyfish on the Tsushima warm currents move to the Uljin power plant. To detect the direction of sea surface warm flows, the spatial range with $25km{\times}25km$ is set up and NOAA sea surface temperature(SST) data are collected in this area. For the statistical analysis, the SST data are made as GIS point data and geostatistical analysis of ArcGIS is used. Analyzing directional semivariogram, the anisotropy of the SST point data are calculated and warm flow direction is detected. This experimental results are expected to use as an element technology for the early warning system development of mass jellyfish ingress in power plant.