• Journal of Life Science
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• v.18 no.10
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• pp.1325-1330
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• 2008

Salix koriyanagi is a deciduous shrub and native to Korea. The spatial distribution of multilocus allelic frequencies and geographical distances of the natural population in upper swampy area at the Namgang River in Korea were studied. The species showed a significant positive and negative spatial autocorrelation according to geographical distances as measured by Moran's I. Genetic similarity of individuals was found among subpopulations at up to a scale of a 12 m distance, and this was partly due to a combination of allelic frequencies, and therefore, a significant spatial autocorrelation was composed of a scale of 12 m intervals. Within S. koriyanagi in swampy area at the Namgang River, a strong spatial structure was observed for allozyme markers, indicating a migration within subpopulations.

• Journal of Life Science
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• v.18 no.11
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• pp.1465-1470
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• 2008

Salix koriyanagi is a deciduous shrub and native to Korea. The spatial distribution of multilocus allelic frequencies and geographical distances of the natural population in upper swampy area at the Namgang River in Korea were studied. The species showed a significant positive and negative spatial autocorrelation according to geographical distances as measured by Moran's I. Genetic similarity of individuals was found among subpopulations at up to a scale of a 12 m distance, and this was partly due to a combination of allelic frequencies, and therefore, a significant spatial autocorrelation was composed of a scale of 12 m intervals. Within S. koriyanagi in swampy area at the Namgang River, a strong spatial structure was observed for allozyme markers, indicating a migration within subpopulations.

• Geomechanics and Engineering
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• v.22 no.4
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• pp.339-348
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• 2020

The uncertain geotechnical properties of frozen soil are important evidence for the design, operation and maintenance of the frozen ground. The complex geological, environmental and physical effects can lead to the spatial variations of the frozen soil, and the uncertain mechanical properties are the key factors for the uncertain analysis of frozen soil engineering. In this study, the elastic modulus, strength and Poisson ratio of warm frozen soil were measured, and the statistical characteristics under different temperature conditions are obtained. The autocorrelation distance (ACD) and autocorrelation function (ACF) of uncertain mechanical properties are estimated by random field (RF) method. The results show that the mean elastic modulus and mean strength decrease with the increase of temperature while the mean Poisson ratio increases with the increase of temperature. The average values of the ACD for the elastic modulus, strength and Poisson ratio are 0.64m, 0.53m and 0.48m, respectively. The standard deviation of the ACD for the elastic modulus, strength and Poisson ratio are 0.03m, 0.07m and 0.03m, respectively. The ACFs of elastic modulus, strength and Poisson ratio decrease with the increase of ratio of local average distance and scale of fluctuation. The ACF of uncertain mechanical properties is different when the temperature is different. This study can improve our understanding of the spatial autocorrelation variations of uncertain geotechnical properties and provide a basis and reference for the uncertain settlement analysis of frozen soil foundation.

• Journal of Satellite, Information and Communications
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• v.10 no.1
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• pp.6-11
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• 2015

In this paper, we analyzed current states and spatial characteristics of crime occurring in A city of Colombia using big data of crime. The analysis draws on the crime statistics of Colombia National Police Agency from 2013 January to September. We also investigated spatial autocorrelation of crime using global and local Moran's Index. Spatial autocorrelation analysis shows significant spatial autocorrelation in the high frequency of crime. Global Moran's I analysis indicates that there are statistically significant value of crime area. Using local Moran's Index analysis, we also implement Local Indicators of Spatial Association(LISA) map and hot spot analysis helps us identify crime distribution.

• Journal of the Korean association of regional geographers
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• v.22 no.2
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• pp.424-438
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• 2016

In an effort to prevent urban decline and hollowing-out phenomenon and to vitalize stagnant local economy, a new urban regeneration paradigm is on the rise. This study aims to analyze urban decline characteristics using the spatial statistical method and GIS on the basis of decline standards in the Urban Regeneration Special Act, and spatial autocorrelation technique. The Gwangju Metropolitan City was set as a research target, and the decline standards in the Urban Regeneration Special Act - population reduction, business declines, and outworn buildings - were applied as the indicator to secure the objectivity. In particular, this study has a distinctive feature from the other existing ones, as applying GIS and the spatial statistical technique, in a sense to make urban decline characteristics analysis by the spatial autocorrelation technique. The overall analysis procedure was carried out by applying the standards of designating urban regeneration regions, and following the spatial exploratory procedure step by step. Therefore, the spatial statistical method procedure and the urban decline characteristics analysis data being presented in this study, as the results, are expected to contribute to the urban decline diagnosis at the level of metropolitan city, as well as to provide useful information for spatial decision making in accordance with urban regeneration.

• Journal of Cadastre & Land InformatiX
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• v.50 no.1
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• pp.25-45
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• 2020

The primary purpose of this study is to compare and analyze the performance of local spatial autocorrelation techniques in identifying spatial distribution patterns of green spaces. To achieve the objective, this researcher uses satellite image analysis and spatial autocorrelation techniques. The result of the study shows that the LISA cluster map with the spatial outlier cluster is superior to other analytical methods in identifying the spatial distribution pattern of urban green space. This study can contribute to the related fields in that it uses several different research methods than the existing ones. Despite this differentiation and usefulness, this study has limitations in using low-resolution satellite imagery and NDVI among vegetation indices in identifying spatial distribution patterns of green areas. These limitations may be overcome in future studies by using UAV images or by simultaneously using several vegetation indices.

• Journal of Korean Society of Rural Planning
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• v.22 no.4
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• pp.139-146
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• 2016

Aging phenomenon is an important issue in Korea national policy. This aging phenomenon depends on the social and environmental characteristics of regions. Also aging phenomenon and regional characteristics have spatial dependency. The purpose of this study is to discover the spatial changes in aging population rate and to find local factors of regional aging phenomenon considering spatial autocorrelation. For spatial analysis of ageing phenomenon, local Moran's I and Geographically Weighted Regression (GWR) were applied. As the results, the most significant changes of aging phenomenon appeared between 2000 and 2005, and most of hot-spot regions (aged regions) were distributed in Jullanam-do and Jullabuk-do. The results of GWR (R-square: 0.681) shows that total fertility rate, the number of doctor per 1,000 people and forest area rate have positive relation with aging population rate, but the number of private academy per 1,000 people has negative relation.

• The Journal of the Korea Contents Association
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• v.12 no.2
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• pp.461-471
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• 2012

The purpose of this paper is to visualize the housing market dynamics with ESDA (Exploratory Spatial Data Analysis) using MATLAB toolbox, in terms of the modeling housing market dynamics in the Busan Metropolitan City. The data are used the real housing price transaction records in Busan from the first quarter of 2006 to the second quarter of 2009. Hedonic house price model, which is not reflecting spatial autocorrelation, has been a powerful tool in understanding housing market dynamics in urban housing economics. This study considers spatial autocorrelation in order to improve the traditional hedonic model which is based on OLS(Ordinary Least Squares) method. The study is, also, investigated the comparison in terms of $R^2$, Sigma Square(${\sigma}^2$), Likelihood(LR) among spatial econometrics models such as SAR(Spatial Autoregressive Models), SEM(Spatial Errors Models), and SAC(General Spatial Models). The major finding of the study is that the SAR, SEM, SAC are far better than the traditional OLS model, considering the various indicators. In addition, the SEM and the SAC are superior to the SAR.

• Journal of Mechanical Science and Technology
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• v.14 no.10
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• pp.1041-1050
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• 2000

In this paper the effect of specimen thickness on fatigue crack growth with the spatial distribution of material properties is presented. Basically, the material resistance to fatigue crack growth is treated as a spatial stochastic process, which varies randomly on the crack surface. The theoretical autocorrelation functions of fatigue crack growth resistance with specimen thickness are discussed for several correlation lengths. Constant ${\Delta}K$ fatigue crack growth tests were also performed on CT type specimens with three different thicknesses of BS 4360 steel. Applying the proposed stochastic model and statistical analysis procedure, the experimental data were analyzed for different specimen thicknesses for determining the autocorrelation functions and probability distributions of the fatigue crack growth resistance.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.3
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• pp.55-63
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• 2012

Soil properties are not random values which is represented by mean and standard deviation but show spatial correlation. Especially, soils are highly variable in their properties and rarely homogeneous. Thus, the accuracy and reliability of probabilistic analysis results is decreased when using only one random variable as design parameter. In this paper, to consider spatial variability of soil property, one-dimensional random fields of coefficient of consolidation ($C_v$) were generated based on a Karhunen-Loeve expansion. A Latin hypercube Monte Calro simulation coupled with finite difference method for Terzaghi's one dimensional consolidation theory was then used to probabilistic analysis. The results show that the failure probability is smaller when consider spatial variability of $C_v$ than not considered and the failure probability increased when the autocorrelation distance increased. Thus, the uncertainty of soil can be overestimated when spatial variability of soil property is not considered, and therefore, to perform a more accurate probabilistic analysis, spatial variability of soil property needed to be considered.