• Journal of Korean Society for Geospatial Information Science
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• v.20 no.2
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• pp.73-79
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• 2012

This study attempts to analyze changes in land use patterns in a compound urban and agricultural city Kimje-si, using LANDSAT TM imagery and to forecast future changes accordingly. As a new approach to supervised classification, HSB(Hue, Saturation, Brightness)-transformed images were used to select training zones, and in doing so classification accuracy increased by more than 5 percent. Land use changes were forecasted by using a cellular automaton algorithm developed by applying Markov Chain techniques, and by taking into account classification results and GIS data, such as population of the pertinent region by area, DEMs, road networks, water systems. Upon comparing the results of the forecast of the land use changes, it appears that geographical features had the greatest influence on the changes. Moreover, a forecast of post-2030 land use change patterns demonstrates that 21.67 percent of mountain lands in Kimje-si is likely to be farmland, and 13.11 percent is likely to become city areas. The major changes are likely to occur in small mountain lands located in the heart of the city. Based on the study result, it seems certain that forecasting future land use changes can help plan land use in a compound urban and agricultural city to procure food resources.

• Journal of the Korea Society of Computer and Information
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• v.17 no.11
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• pp.107-116
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• 2012

In this paper we propose a method that can generate the risk probability map in the form of raster shape by using Markov Chain methodology applied to the object interpretation keys and quantified risk indexes. These object interpretation keys, which are primarily characteristics that can be identified by the naked eye, are set based on the objects that comprise the spatial information of a certain urban area. Each key is divided into a cell, and then is weighted by its own risk index. These keys in turn are used to generate the unified risk probability map using various levels of crime prediction probability maps. The risk probability map may vary over time and means of applying different sets of object interpretation keys. Therefore, this method can be used to prevent crimes by providing the ways of setting up the best possible police patrol beat as well as the optimal arrangement of surveillance equipments.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.309-313
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• 2008

본 논문의 목적은 ENSO의 영향에 의한 우리나라 강우의 특성을 분석하는 것이다. 따라서 우리나라 기상관측소의 강우량 자료를 Warm(El Nino), Cold(La Nina), Normal 에피소드에 따라 기간별로 분류하였다. 또한 이렇게 분류한 자료는 Markov Chain 모형을 이용하여 100년의 자료로 모의 발생하였고 에피소드별로 빈도분석을 실시하였다. 빈도분석 결과 에피소드에 따라 각 기상관측소별로 강우의 크기에 영향을 미치고 있음을 알 수 있었다. 또한 군집분석을 실시하여 각 에피소드의 공간적인 영향에 대해서 분석하였다. 결과적으로 Warm(El Nino), Cold(La Nina) and Normal 에피소드로 대표되는 ENSO는 우리나라의 강우특성에 크게 영향을 미치는 것으로 파악되었다.

• Journal of the Korean Data and Information Science Society
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• v.27 no.3
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• pp.803-814
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• 2016

Recent times have seen an exponential increase in the amount of spatial data, which is in many cases associated with temporal data. Recent advances in computer technology and computation of hierarchical Bayesian models have enabled to analyze complex spatio-temporal data. Our work aims at modeling data of daily average nitrogen dioxide (NO2) levels obtained from 25 air monitoring sites in Seoul between 2003 and 2010. We considered an independent Gaussian process model and an auto-regressive model and carried out estimation within a hierarchical Bayesian framework with Markov chain Monte Carlo techniques. A Gaussian predictive process approximation has shown the better prediction performance rather than a Hierarchical auto-regressive model for the illustrative NO2 concentration levels at any unmonitored location.

• Journal of Korean Society on Water Environment
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• v.24 no.6
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• pp.725-740
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• 2008

In this study a multi-site daily precipitation generator which generates the precipitation with similar spatial correlation, and at the same time, with conserving statistical properties of the observed data is developed. The proposed generator is intended to be a tool for down-scaling the data obtained from GCMs or RCMs into local scales. The occurrences of precipitation are simultaneously modeled in multi-sites by 2-parameter first-order Markov chain using random variables of spatially correlated while temporally independent, and then, the amount of precipitation is simulated by 3-parameter mixed exponential probability density function that resolves the issue of maintaining intermittence of precipitation field. This approach is applied to the Nakdong river basin and the observed data are daily precipitation data of 19 locations. The results show that spatial correlations of precipitation series are relatively well simulated and statistical properties of observed precipitation series are simulated properly.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.1
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• pp.32.3-33
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• 2021

We present H I gas kinematics and star formation activities of NGC 6822, a dwarf galaxy located in the Local Volume at a distance of ~ 490 kpc. We perform profile decomposition of the line-of-sight velocity profiles of the high-resolution (42.4" × 12" spatial; 1.6 km/s spectral) H I data cube taken with the Australia Telescope Compact Array (ATCA). For this, we use a new tool, the so-called BAYGAUD (BAYesian GAUssian Decompositor) which is based on Bayesian Markov Chain Monte Carlo (MCMC) techniques, allowing us to decompose a line-of-sight velocity profile into an optimal number of Gaussian components in a quantitative manner. We classify the decomposed H I gas components of NGC 6822 into bulk-narrow, bulk-broad, and non_bulk with respect to their velocity and velocity dispersion. We correlate their gas surface densities with the surface star formation rates derived using both GALEX far-ultraviolet and WISE 22 micron data to examine the impact of gas turbulence caused by stellar feedback on the Kennicutt-Schmidt (K-S) law. The bulk-narrow component that resides within r25 is likely to follow the linear extension of the Kennicutt-Schmidt (K-S) law for molecular hydrogen (H2) at the low gas surface density regime where H I is not saturated.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.25 no.6
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• pp.394-404
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• 2013

In the present study, the characteristics of spectral peakedness parameter $Q_p$, bandwidth parameter ${\varepsilon}$, and spectral width parameter ${\nu}$ were analyzed as a first step to define the swell waves quantitatively. For the analysis, the joint probability density function of significant wave heights and peak periods were newly developed. The MCMC(Markov Chain Monte Carlo) simulations have been performed to generate the significant wave heights and peak periods from the developed probability density functions. Applying the simulated significant wave heights and peak periods to the theoretical wave spectrum models, the spectral shapes parameters were obtained and analyzed. Among the spectral shape parameters, only the spectral peakedness parameter $Q_p$, is shown to be independent with the significant wave height and peak wave period. It also best represents the peakedness of the spectral shape, and henceforth $Q_p$ should be used to define the swell waves with a wave period. For the field verification of the results, wave data obtained from Hupo port and Ulleungdo were analyzed and results showed the same trend with the MCMC simulation results.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5B
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• pp.397-408
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• 2009

In this study, a stochastic precipitation generation framework for simultaneous simulation of daily precipitation at multiple sites is presented. The precipitation occurrence at individual sites is generated using hybrid-order Markov chain model which allows higher-order dependence for dry sequences. The precipitation amounts are reproduced using Anscombe residuals and gamma distributions. Multisite spatial correlations in the precipitation occurrence and amount series are represented with spatially correlated random numbers. The proposed model is applied for a network of 17 locations in the middle of Korean peninsular. Evaluation statistics are reported by generating 50 realizations of the precipitation of length equal to the observed record. The analysis of results show that the model reproduces wet day number, wet and dry day spell, and mean and standard deviation of wet day amount fairly well. However, mean values of 50 realizations of generated precipitation series yield around 23% Root Mean Square Errors (RMSE) of the average value of observed maximum numbers of consecutive wet and dry days and 17% RMSE of the average value of observed annual maximum precipitations for return periods of 100 and 200 years. The provided model also reproduces spatial correlations in observed precipitation occurrence and amount series accurately.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.70.2-71
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• 2021

We examine gas kinematics and star formation activities of NGC 6822, a gas-rich dwarf irregular galaxy in the Local Group at a distance of ~490 kpc. We perform profile decomposition of all the line-of-sight (LOS) HI velocity profiles of the high-resolution (42.4" × 12" spatial; 1.6 km/s spectral) HI data cube of the galaxy, taken with the Australian Telescope Compact Array (ATCA). To this end, we use a novel tool based on Bayesian Markov Chain Monte Carlo (MCMC) techniques, the so-called BAYGAUD, which allows us to decompose a velocity profile into an optimal number of Gaussian components in a quantitative manner. We group all the decomposed components into bulk-narrow, bulk-broad, and non-bulk gas components classified with respect to their velocity dispersions and the amounts of velocity offset from the global kinematics, respectively. Using the surface densities and velocity dispersions of the kinematically decomposed HI gas maps together with the rotation curve of NGC 6822, we derive Toomre-Q parameters for individual regions of the galaxy which quantify the level of local gravitational instability of the gaseous disk. We also measure the local star formation rate (SFR) of the corresponding regions in the galaxy by combining GALEX Far-ultraviolet (FUV) and WISE 22㎛ images. We then relate the gas and SFR surface densities in order to investigate the local Kennicutt-Schmidt (K-S) law of gravitationally unstable regions which are selected from the Toomre Q analysis. Of the three groups, the bulk-narrow, bulk-broad and non-bulk gas components, we find that the lower Toomre-Q values the bulk-narrow gas components have, the more consistent with the linear extension of the K-S law derived from molecular hydrogen (H2) observations.

• The Bulletin of The Korean Astronomical Society
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• v.45 no.1
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• pp.61.4-62
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• 2020

We present H I gas kinematics and star formation activities of NGC 6822, a dwarf galaxy located in the Local Volume at a distance of ~490 kpc. We perform profile decomposition of the line-of-sight velocity profiles of the high-resolution (~42.4" × 12") spatial; ~1.6 km/s spectral) H I data cube taken with the Australia Telescope Compact Array (ATCA). For this, we use a new tool, the so-called BAYGAUD (BAYesian GAUssian Decompositor) which is based on Bayesian Markov Chain Monte Carlo (MCMC) techniques, allowing us to decompose a line-of-sight velocity profile into an optimal number of Gaussian components in a quantitative manner. We classify the decomposed H I gas components of NGC 6822 into kinematically cold, warm or hot ones with respect to their velocity dispersion: 1) cold: < 4 km/s, 2) warm: 4 ~ 8 km/s, 3) hot: > 8 km/s. We then derive the Toomre-Q parameters of NGC 6822 using the kinematically decomposed H I gas maps. We also correlate their gas surface densities with the surface star formation rates derived using both GALEX far-ultraviolet and WISE 22 micron data to examine the impact of gas turbulence caused by stellar feedback on the Kennicutt-Schmidt (K-S) law. The kinematically cold component is likely to better follow the linear extension of the Kennicutt-Schmidt (K-S) law for molecular hydrogen (H2) at the low gas surface density regime where H I is not saturated.