• Asian Pacific Journal of Cancer Prevention
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• v.16 no.9
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• pp.4025-4029
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• 2015

Background: Gastrointestinal tract cancers are among the most common cancers in Iran and comprise approximately 38% of all the reported cases of cancer. This study aimed to describe the epidemiology and to investigate spatial clustering of common cancers of the gastrointestinal tract across the counties of Iran using full Bayesian smoothing and Moran I Index statistics. Materials and Methods: The data of the national registry cancer were used in this study. Besides, indirect standardized rates were calculated for 371 counties of Iranand smoothed using Winbug 1.4 software with a full Bayesian method. Global Moran I and local Moran I were also used to investigate clustering. Results: According to the results, 75,644 new cases of cancer were nationally registered in Iran among which 18,019 cases (23.8%) were esophagus, gastric, colorectal, and liver cancers. The results of Global Moran's I test were 0.60 (P=0.001), 0.47 (P=0.001), 0.29 (P=0.001), and 0.40 (P=0.001) for esophagus, gastric, colorectal, and liver cancers, respectively. This shows clustering of the four studied cancers in Iran at the national level. Conclusions: High level clustering of the cases was seen in northern, northwestern, western, and northeastern areas for esophagus, gastric, and colorectal cancers. Considering liver cancer, high clustering was observed in some counties in central, northeastern, and southern areas.

• Journal of Life Science
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• v.24 no.8
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• pp.813-819
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• 2014

The spatial distribution of geographical distances at five natural populations of Camellia japonica in Busan, Korea was studied. The four plots (Mollundae, Gadeok-do, Du-do, and Jwiseum) of C. japonica were uniformly distributed in the forest community and only one plot (Amnam-dong) was aggregately distributed in the forest community. Morisita index is related to the patchiness index showed that the plot $20m{\times}50m$ had an overly steep slope when the area was larger than $20m{\times}20m$, which indicated that the degree of aggregation increased significantly with increasing quadrat sizes, while the patchiness indices did not change from the plot $5m{\times}10m$ to $10m{\times}10m$. The spatial structure was quantified by Moran's I, a coefficient of spatial autocorrelation. Ten of the significant values (76.9%) were positive, indicating similarity among individuals in the first 4 distance classes (80 m), i.e., pairs of individuals with dissimilarity characteristics can separate by more than 100 m.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.25-33
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• 2016

In order to visualize point based Location-Based Social Network Services(LBSNS) data on multi-scaled tile map effectively, it is necessary to apply tile-based clustering method. Then determinating reasonable numbers and size of tiles is required. However, there is no such criteria and the numbers and size of tiles are modified based on data type and the purpose of analysis. In other words, researchers' subjectivity is always involved in this type of study. This is when Modifiable Areal Unit Problem(MAUP) occurs, that affects the results of analysis. Among LBSNS, geotagged Twitter data were chosen to find the influence of MAUP in scale effects perspective. For this purpose, the degree of spatial autocorrelation using spatial error model was altered, and change of distributions was analyzed using Morna's I. As a result, positive spatial autocorrelation showed in the original data and the spatial autocorrelation was decreased as the value of spatial autoregressive coefficient was increasing. Therefore, the intensity of the spatial autocorrelation of Twitter data was adjusted to five levels, and for each level, nine different size of grid was created. For each level and different grid sizes, Moran's I was calculated. It was found that the spatial autocorrelation was increased when the aggregation level was being increased and decreased in a certainpoint. Another tendency was found that the scale effect of MAUP was decreased when the spatial autocorrelation was high.

• Journal of Korea Water Resources Association
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• v.56 no.5
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• pp.325-336
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• 2023

In August 2022, even though flood damage occurred in the metropolitan area due to heavy rain, drought warnings were issued in Jeolla province, which indicates that the regional drought is intensified recent years. To cope with regarding intensified regional droughts, many studies have been conducted to identify spatial patterns of the occurrence of meteorological drought, however, case studies of spatial clustering for water shortage are not sufficient. In this study, using the estimations of water shortage in the Han River Basin in 2030 of the Master Plans for National Water Management, the spatial characteristics of water shortage were analyzed to identify the hotspot areas based on the Local Moran's I and Getis-Ord Gi^*, which are representative indicators of spatial clustering analysis. The spatial characteristics of water shortage areas were verified based on the p-value and the Moran scatter plot. The overall results of for three anayisis periods (S0(1967-1983), S1(1984-2000), S2(2001-2018)) indicated that the lower Imjin River (#1023) was the hotspot for water shortage, and there are moving patterns of water shortage from the east of lower Imjin River (#1023) to the west during S2 compared to S0 and S1. In addition, the Yangyang-namdaecheon (#1301) was the HL area that is adjacent to a high water shortage area and a low water shortage area, and had water shortage pattern in S2 compared to S0 and S1.

• The Korean Journal of Ecology
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• v.23 no.1
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• pp.17-23
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• 2000

The spatial distribution of allelic frequencies was studied in the natural population of three species (Ligustrum obtusiflolium, Alnus japonica, and Pinus densflora). The distributional patterns of the crown-cover centers were compared between two populations in forests. L. obtusifolium and p. densiflora showed a significantly positive spatial autocorrelation as measured by Moran's I. In P densiflora, the genetic similarity was shown by individuals within up to a scale of 18 m distance and this is partly due to combination of pollen dispersal and long distance seed dispersal by wind or men. In L. obtusifolium, population structure in the distribution of allelic frequencies is related to mating systems and is consisted of a scale of 12.5 m intervals. No spatial structuring of allele frequencies was found for polymorphic enzyme loci within a natural population of Alnus japonica. The results also in- dicate that positive associations between L. obtusifolium and P densiflora can occur when both select the same habitat or have the same environmental requirements.

• 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.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.24 no.5
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• pp.25-34
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• 2021

Increase in avian species richness is one of the important issues of urban biodiversity policies, since it can promote diverse ecosystem services such as seed dispersal, education, and pollination. However, though human disturbance can significantly affect avian species richness, there are limited studies on the way to reflect the dynamics of floating population. Therefore, this study analyzed the spatial relationship between avian species richness, floating population, and vegetation cover using telecommunications information to identify the areas that requiring targeted monitoring and restoration action. Bivariate Local Moran's I was applied to identify LISA cluster map that showing representative biotopes, which reflect significant spatial relationship between species richness and population distribution. Edge density and distribution of ndvi were identified for evaluating relative adequacy of selected biotopes to strengthen the robust biodiversity network. This study offers insight to consider human disturbance in spatial context using innovative big data to increase the effectiveness of urban biodiversity measures.

• Journal of Preventive Veterinary Medicine
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• v.41 no.2
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• pp.79-83
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• 2017

In this study, we used a choropleth map to explore the spatial variation of the risk of cattle herds being bovine tuberculosis (BTB) positive in Gangwon-do in 2015. The map shows that the risk of being BTB-positive was lower in provinces located in the middle of Gangwon-do (Wonju, Youngwol, Peongchang, and Kangneung) than in other provinces. In addition, one province located in the north (Goseong) had a low risk of BTB. The estimate for the intercept of the spatial lag model was 0.66, and the spatial autocorrelation coefficient (lambda) was 0.20 (Table 1). The Moran's I was 0.33 with p-value of 0.02. In 2015, provinces located in the North West (Hwacheon) and East (Donghae) of Gangwon-do had a higher BTB risk. We identified some specific provinces at low BTB-positive risk, information that may prove useful for control of BTB in the study area.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.1
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• pp.41-55
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• 2022

Social interest in the fine particulate matter has increased significantly since the 2010s, and various efforts have been made to reduce it through environmental plans and policies. To support such environmental planning, in this study, spatial cluster characteristics of fine particulate matter (PM2.5) concentrations were analyzed in the metropolitan area to identify high-risk areas spatially, and the correlation with local environmental characteristics was also confirmed. The PM2.5 concentration for the recent 5 years (2016-2020) was targeted, and representative spatial statistical methods Getis-Ord Gi^* and Local Moran's I were applied. As a result of the analysis, the cluster form was different in Getis-Ord Gi^* and Local Moran's I, but they show high similarity in direction, therefore complementary results could be obtained. In the high concentration period, the hotspot concentration of the Getis-Ord Gi* method increased, but in Local Moran's I, the HH region, the high concentration cluster, showed a decreasing trend. Hotspots of the Getis-Ord Gi^* technique were prominent in the Pyeongtaek-Hwaseong and Yeoju-Icheon regions, and the HH cluster of Local Moran's I was located in the southwest, and the LL cluster was located in the northeast. As in the case of the metropolitan area, in the results of Seoul, there was a phenomenon of division between the northeast and southwest regions. The PM2.5 concentration showed a high correlation with the elevation, vegetation greenness and the industrial area ratio. During the high concentration period, the relation with vegetation greenness increased, and the elevation and industrial area ratio increased in the case of the annual average. This suggests that the function of vegetation can be maximized at a high concentration period, and the influence of topography and industrial areas is large on average. This characteristic was also confirmed in the basic statistics for each major cluster. The spatial clustering characteristics of PM2.5 can be considered in the national land and environmental plan at the metropolitan level. In particular, it will be effective to utilize the clustering characteristics based on the annual average concentration, which contributes to domestic emissions.

• Korean Journal of Remote Sensing
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• v.23 no.6
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• pp.521-528
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• 2007

The overall objective of this research was to investigate various combination of segmentation parameters and to improve classification accuracy of object-oriented classification. This research presents a method for evaluation of segmentation parameters by calculating Moran's I and Intrasegment Variance. This research used Landsat-7/ETM image of $11{\times}14$ Km developed area in Ansung, Korea. Segmented images are generated by 75 combinations of parameter. Selecting 7 combinations of high, middle and low grade expected classification accuracy was based on calculated Moran's I and Intrasegment Variance. Selected segmentation images are classified 4 classes and analyzed classification accuracy according to method of objected-oriented classification. The research result proved that classification accuracy is related to segmentation parameters. The case of high grade of expected classification accuracy showed more than 85% overall accuracy. On the other hand, low ado showed around 50% overall accuracy.