• Journal of Ecology and Environment
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• v.37 no.2
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• pp.53-60
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• 2014

The arctic tundra is an important ecosystem in terms of the organic carbon cycle and climate change, and therefore, detailed analysis of vegetation distribution patterns is required to determine their association. We used grid-sampling method and applied geostatistics to analyze spatial variability and patterns of vegetation within a two-dimensional space, and calculated the Moran's I statistics and semivariance to assess the spatial autocorrelation of vegetation. Spatially autocorrelated vegetation consisted of moss, Eriophorum vaginatum, Betula nana, and Rubus chamaemorus. Interpolation maps and cross-correlograms revealed spatial specificity of Carex aquatilis and a strong negative spatial correlation between E. vaginatum and C. aquatilis. These results suggest differences between the species in water requirements for survival in the arctic tundra. Geostatistical methods could offer valuable information for identifying the vegetation spatial distribution.

• Journal of Cadastre & Land InformatiX
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• v.50 no.2
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• pp.203-219
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• 2020

The primary purpose of this study is to identify spatial distribution patterns of co-authoring activities in Korean cadastral science. The analysis showed that a small number of researchers played an essential role in the Korean cadastral co-authorship network. In particular, some authors not only had a significant influence on other nodes in the network but also served as intermediaries between researchers. Moreover, the distance between researchers influenced co-authorship decisions to a limited extent. This study differs considerably from previous studies in that it used spatial analysis techniques to identify spatial distribution patterns of co-authoring activities. However, this research is limited in that it applied only 2019 data to determine the spatial distribution pattern of co-authoring activities. We can overcome this limitation if we analyze the spatial distribution patterns of co-authoring activities using multi-year data in future studies.

• 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 Ecology and Environment
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• v.41 no.8
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• pp.223-234
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• 2017

Background: Spatial structure of plants in a population reflects complex interactions of ecological and evolutionary processes. For dioecious plants, differences in reproduction cost between sexes and sizes might affect their spatial distribution. Abiotic heterogeneity may also affect adaptation activities, and result in a unique spatial structure of the population. Thus, we examined sex- and size-related spatial distributions of old-growth forest of dioecious tree Torreya nucifera in extremely heterogeneous Gotjawal terrain of Jeju Island, South Korea. Methods: We generated a database of location, sex, and size (DBH) of T. nucifera trees for each quadrat ($160{\times}300m$) in each of the three sites previously defined (quadrat A, B, C in Site I, II, and III, respectively). T. nucifera trees were categorized into eight groups based on sex (males vs. females), size (small vs. large trees), and sex by size (small vs. large males, and small vs. large females) for spatial point pattern analysis. Univariate and bivariate spatial analyses were conducted. Results: Univariate spatial analysis showed that spatial patterns of T. nucifera trees differed among the three quadrats. In quadrat A, individual trees showed random distribution at all scales regardless of sex and size groups. When assessing univariate patterns for sex by size groups in quadrat B, small males and small females were distributed randomly at all scales whereas large males and large females were clumped. All groups in quadrat C were clustered at short distances but the pattern changed as distance was increased. Bivariate spatial analyses testing the association between sex and size groups showed that spatial segregation occurred only in quadrat C. Males and females were spatially independent at all scales. However, after controlling for size, males and females were spatially separated. Conclusions: Diverse spatial patterns of T. nucifera trees across the three sites within the Torreya Forest imply that adaptive explanations are not sufficient for understanding spatial structure in this old-growth forest. If so, the role of Gotjawal terrain in terms of creating extremely diverse microhabitats and subsequently stochastic processes of survival and mortality of trees, both of which ultimately determine spatial patterns, needs to be further examined.

• Journal of the Economic Geographical Society of Korea
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• v.16 no.3
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• pp.512-527
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• 2013

This study examines the spatial distribution characteristics of financial industry which has been a necessary service for contemporary urban life. In particular, we analyze the spatial distribution patterns of money lending business which is considered with informal financial services as well as the spatial distribution patterns of banks which are representative of the institutional financial services. For the purpose, their density distribution patterns are explored by Kernel density analysis for both financial services in first. Moran's I coefficients are estimated for these two financial services to clarify the distintion in their geographical concentration patterns. The results of spatial autocorrelation analysis show stark differences between the center city and outskirts of the Seoul metropolitan area. Multivariate regression models are developed to explain the relationships between the spatial distributions of financial services and geographical variables. Finally, we discuss financial exclusion problem in the Metropolitan Seoul based on these spatial distribution characteristics.

• Journal of the Economic Geographical Society of Korea
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• v.16 no.1
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• pp.1-16
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• 2013

This study investigates the spatial distribution characteristics of Korean fashion industries during the last decade, in which the economic geography of fashion industries has changed dynamically with economic globalization and "thus resulted in increased" demand "of" diversification. In particular, this study examines the spatial distribution patterns of fashion industries in the Seoul metropolitan area where fashion industries are highly agglomerated. For the purpose, this study applies Moran's I Index of spatial autocorrelation analysis for seven functional sectors of fashion industries related to fashion production. The global and local agglomeration patterns are examined for each functional sector. The results clarify the distinction in the spatial agglomeration patterns among the seven functional sectors of fashion industries in the Seoul Metropolitan area. Logit models are developed to examine the interrelationships among functional sectors in their spatial agglomeration distribution patterns. By conducting binary logistic regression analysis, we find out how the spatial agglomeration of each functional sector is related to the others.

• Ocean and Polar Research
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• v.29 no.4
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• pp.391-400
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• 2007

To identify the spatial distribution pattern of water quality in Masan Bay, Pearson's correlation as a common statistic method and Moran's I as a spatial autocorrelation statistics were applied to the hydrological data seasonally collected from Masan Bay for two years ($2004{\sim}2005$). Spatial distribution of salinity, DO and silicate among the hydrological parameters clustered strongly while chlorophyll a distribution displayed a weak clustering. When the similarity matrix of Moran's I was compared with correlation matrix of Pearson's r, only the relationships of temperature vs. salinity, temperature vs. silicate and silicate vs. total inorganic nitrogen showed significant correlation and similarity of spatial clustered pattern. Considering Pearson's correlation and the spatial autocorrelation results, water quality distribution patterns of Masan Bay were conceptually simplified into four types. Based on the simplified types, Moran's I and Pearson's r were compared respectively with spatial distribution maps on salinity and silicate with a strong clustered pattern, and with chlorophyll a having no clustered pattern. According to these test results, spatial distribution of the water quality in Masan Bay could be summed up in four patterns. This summation should be developed as spatial index to be linked with pollutant and ecological indicators for coastal health assessment.

• Journal of Distribution Science
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• v.20 no.3
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• pp.71-82
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• 2022

Purpose: This study aims to not only measure the elderly welfare supply index but investigate spatial patterns and determinants of local elderly welfare services in South Korea. Research design, data, and methodology: The index for local elderly welfare services is measured by employing standardized scores for critical variables related to elderly welfare. The present study utilized the GIS technique and Moran's I index to examine spatial patterns of elderly welfare services. The determinants of local elderly welfare service are analyzed by a series of regression models using R. Results: Spatial imbalance and asymmetric distribution were serious in the supply of elderly welfare service. It was also confirmed that the factors affecting the level of welfare services for the elderly vary depending on the type of service. In particular, the higher the proportion of the elderly population and the social welfare budget, the lower the level of welfare services for the elderly. Conclusions: Given the circumstance of spatial mismatch between supply and demand for elderly welfare services, it is necessary to consider and provide policy tactics about how the economic benefits and welfare budgets generated in the region can contribute to strengthening the welfare service system for the elderly.

• Journal of Distribution Science
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• v.17 no.3
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• pp.21-30
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• 2019

Purpose - While many related prior studies have focused on the segregation by race and ethnicity, the academic interest in the separation of residence by income and social class is gradually increasing. This study aims to not only investigate spatial pattern of economic segregation and poverty rate in South Korea, but also shed light on what affect residential distribution of the poor. Research design, data, and methodology - The unit of analysis is Si-Gun-Gu municipal level entities of South Korea. Most demographic, socioeconomic, and residential variables were derived from Korean Census Data in 2015. In order to examine spatial patterns of economic segregation and poverty rate in South Korea, a series of measurements and visualization was conducted through the Geo-Segregation Analyzer and ArcGIS programs. Determinants of economic segregation and local poverty rates were investigated by regression analyses using STATA. Results - The spatial patterns of areas with high poverty rates were extremely clustered, while the distribution of areas with high economic segregation was relatively evenly distributed. Demographic, residential, and local factors appeared to affect whether the poor live in particular area or spread evenly. Conclusions - The factors that raise the poverty rate result in lower level of economic segregation, while factors that reduce the poverty rate lead to severe level of economic segregation.

• Journal of Ecology and Environment
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• v.33 no.1
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• pp.67-77
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• 2010

Stand structure and spatial associations of the dominant tree species in Quercus mongolica stands were investigated to understand interspecific relationships and the persistent dominance of Q. mongolica. We examined the species composition, DBH (diameter at breast height) distribution, and spatial distribution of trees (${\geq}\;2.5\;cm$ DBH) in two permanent $100\;m\;{\times}\;100\;m$ plots in Q. mongolica-dominant stands on the western part of Mt. Jiri. Ripley's K-function was used to characterize the spatial patterns and associations of dominant tree species. Q. mongolica showed a continuous and reverse-J shaped DBH distribution with clumped spatial distribution in both study sites. Q. mongolica and Abies koreana exhibited a negative association implying potential interspecific competition. The positive spatial association between Q. mongolica and Alnus hirsuta var. sibirica and Fraxinus sieboldiana were affected by site characteristics: limited habitat conditions with a large proportion of rock surface. Our results suggest that interactions among species were complex and ranged from positive to negative. Differences in stand and site characteristics and regeneration mechanisms among the species play an important role in regulating their spatial distribution patterns, while competition between individuals also contributes to spatial patterning of these communities. The high density and the early developmental stage of spatial distribution and structural characteristics of Q. mongolica and the relatively low importance values of other species in the stands imply that Q. mongolica will remain dominant in the study sites in the near future.