• Geosciences Journal
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• v.22 no.6
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• pp.1053-1067
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• 2018

This paper uses a probability-based approach to study the spatial relationships between landslides and their causative factors in the Mingchukur area, Bostanlik districts of Tashkent, Uzbekistan. The approach is based on digital databases and incorporates methods including probability analysis, spatial pattern analysis, and interactive mapping. First, an object-oriented conceptual model for describing landslide events is proposed, and a combined database of landslides and environmental factors is constructed by integrating various databases within a unifying conceptual framework. The frequency ratio probability model and landslide occurrence data are linked for interactive, spatial evaluation of the relationships between landslides and their causative factors. In total, 15 factors were analyzed, divided into topography, hydrology, and geology categories. All analyzed factors were also divided into numerical and categorical types. Numerical factors are continuous and were evaluated according to their $R^2$ values. A landslide susceptibility map was constructed based on conditioning factors and landslide occurrence data using the frequency ratio model. Finally, the map was validated and the accuracy showed the satisfactory value of 83.3%.

• Proceedings of the Korean Geotechical Society Conference
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• 2003.03a
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• pp.123-130
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• 2003

The estimation of key soil properties and subsequent quantitative assessment of the associated uncertainties has always been an important issue in geotechnical engineering. It is well recognized that soil properties vary spatially as a result of depositional and post-depositional processes. The stochastic nature of spatially varying soil properties can be treated as a random field. A practical statistical approach that can be used to systematically model various sources of uncertainty is presented in the context of reliability analysis of slope stability Newly developed expressions for probabilistic characterization of soil properties incorporate sampling and measurement errors, as well as spatial variability and its reduced variance due to spatial averaging. Reliability analyses of the probability of slope failure using the different statistical representations of soil properties show that the incorporation of spatial correlation and conditional simulation leads to significantly lower probability of failure than obtained using simple random variable approach.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.9-11
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• 2005

We propose a new content-based image retrieval using a block color co-occurrence matrix (BCCM) and pattern correlogram. In the proposed method, the color feature vectors are extracted by using BCCM that represents the probability of the co-occurrence of two mean colors within blocks. Also the pattern feature vectors are extracted by using pattern correlogram which is combined with spatial correlation of pattern. In the proposed pattern correlogram method. after block-divided image is classified into 48 patterns with respect to the change of the RGB color of the image, joint probability between the same pattern from the surrounding blocks existing at the fixed distance and the center pattern is calculated. Experimental results show that the proposed method can outperform the conventional methods as regards the precision and the size of the feature vector dimension.

• Korean Institute of Interior Design Journal
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• v.24 no.2
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• pp.108-116
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• 2015

The probability of visual perception occurrence varies in case the expectation of using each unit space of which the whole space consists because the size of space subject to analysis is very large or the organization is complicated in the analysis of spatial visual configuration. Therefore, it is necessary to compensate space analysis and index measurement by applying weight to the point of view for the probability of experiencing space. This study proposed a method of analyzing visibility ratio by applying the integration of space syntax theory as weight, and grasped the effect in comparison with the visibility ratio when weight was not applied.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.6
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• pp.685-692
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• 2004

A stochastic approach has been presented for superplastic deformation of Ti-6Al-4V alloy, and probability functions are used to model the heterogeneous phase distributions. The experimentally observed spatial correlation functions are developed, and microstructural evolutions together with superplastic deformation behavior have been investigated by means of the two-point and three-point probability functions. The results have shown that the probability varies approximately linearly with separation distance, and deformation enhanced probability changes during the process. The stress-strain behavior with the evolutions of probability function can be correctly predicted by the model. The finite element implementation using Monte Carlo simulation associated with reconstructed microstructures shows that better agreement with experimental data of failure strain on the test specimen.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.292-297
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• 2003

A stochastic approach has been presented for superplastic deformation of Ti-6AJ-4V alloy, and probability function are used to heterogeneous phase distributions. The experimentally observed spatial correlation function are developed, and microstructural evolutions together with superplastic deformation behavior have investigated by means of the probability function. The result have shown that the probability varies approximately linearly with separation with distance, and significant deformation enhanced probability changes during the deformation. The stress-strain behavior with the evolutions of probability function can be correctly predicted by the model. The finite clement implementation using Monte Carlo simulation associated with phase re-distributions shows that better agreement with experimental data of failure strain on the test specimen.

• Spatial Information Research
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• v.22 no.4
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• pp.49-58
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• 2014

Natural disasters of large scale such as typhoon, heat waves and snow storm have recently been increased because of climate change according to global warming which is most likely caused by greenhouse gas in the atmosphere. Increase of greenhouse gases concentration has caused the augmentation of earth's surface temperature, which raised the frequency of incidences of extreme weather in northern hemisphere. In this paper, we present spatial analysis of future typhoon genesis based on IPCC AR5 RCP 8.5 scenario, which applied latest carbon dioxide concentration trend. For this analysis, we firstly calculated GPI using RCP 8.5 monthly data during 1982~2100. By spatially comparing the monthly averaged GPIs and typhoon genesis locations of 1982~2010, a probability density distribution(PDF) of the typhoon genesis was estimated. Then, we defined 0.05GPI, 0.1GPI and 0.15GPI based on the GPI ranges which are corresponding to probability densities of 0.05, 0.1 and 0.15, respectively. Based on the PDF-related GPIs, spatial distributions of probability on the typhoon genesis were estimated for the periods of 1982~2010, 2011~2040, 2041~2070 and 2071~2100. Also, we analyzed area density using historical genesis points and spatial distributions. As the results, Philippines' east area corresponding to region of latitude $10^{\circ}{\sim}20^{\circ}$ shows high typhoon genesis probability in future. Using this result, we expect to estimate the potential region of typhoon genesis in the future and to develop the genesis model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.10
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• pp.6917-6924
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• 2015

The universal nature of humans is formed by the view angle and the visibility range. However, the majority of theories on spatial structure analysis based on the visual perception do neither reflect the view angle nor consider only the flat view angle. Some theories that reflect them is a theory where the part included in the view angle and the part excluded in the view angle have been separated in a dichotomous way, excluding the universal characteristics of humans. This study applied an observing probability to a 3-D visibility analysis theory by conducting a eye-tracking experiment, empirically determining the limits of the field of view, and deriving the observing probability by view angle. In addition, it attempted to identify the probability by manufacturing an application of spacial, visual perception analysis and applying the concept of multiple frustum culling. For the characteristics of observation, the data were measured and collected regarding the walking course for 3 minutes for an optional space, aimed for 33 people as subjects. Subsequently, the data were prepared by analyzing the observation fixation frequency probability.

• Spatial Information Research
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• v.2 no.1
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• pp.47-51
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• 1994

The purpose of the study is to establ ish models of land Cover (use) prediction system for development and management of land resources using remotely sensed data as well as ancillary data in the context of multi-dis¬ciplinary approach in the application to CheJoo Island. The model adopts multi-date processing techniques and is a spatial/temporal land-Cover projection strategy emerged as a synthesis of the probability tra-nsition model and the discrimnant-analys is model. A discriminant modelis applied to all pixels in CheJoo landscape plane to predict the most likely change in land Cover. The probability transition model provides the number of these pixels that will convert to different land Cover in a given future time increment. The syntheric model predicts the future change in land Cover and its volume of pixels in the landscape plane.

• Journal of the Korean Geographical Society
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• v.51 no.4
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• pp.525-539
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• 2016

This study attempts to predict the changes in the spatial distribution of occupational employment in Korea by applying Markov Chain Model. For the purpose we analyze the job-related migration pattern and estimate the transition probability with the last six years job-related migration data. By applying the Chapman-Kolmogorov equation based on the transition probability, we predict the changes in the spatial distribution of occupational employment for the next ten years. The result reveals that the employment of professional jobs is predicted to increase at every city and region except Seoul, while the employment of elementary labor jobs is predicted to increase slightly in Seoul. In particular, Gangwon-do and Chuncheongdo are predicted to increase in the employment of all occupational jobs.