• Journal of Korean Society of Forest Science
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• v.101 no.2
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• pp.203-212
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• 2012

This study aims to test presence of spatial autocorrelation of burn severity in Uljin and Youngduk areas burned in 2011. SPOT satellite images were used to compute the NDVI representing burn severity, and NDVI values were sampled for 5,000 randomly dispersed points for each site. Spatial autocorrelations of sampled NDVI values were analyzed with Moran's I and Variogram models. Moran's I values of burn severity in Uljin and Youngduk areas were 0.7745 and 0.7968, respectively, indicating presence of strong spatial autocorrelations. On the basis of Variogram and changes of Moran's I values by lag class, ideal sampling distance were proposed, which were 566-2,151 m for Uljin and 272-402 m for Youngduk. It was recommended to apply these ranges of sampling distance in flexible corresponding to Anisotropic characteristics of burned areas.

• 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.

• Ocean and Polar Research
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• v.44 no.2
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• pp.179-190
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• 2022

Data missing in optical satellite images caused by natural variations have been a crucial barrier in observing the status of marine surfaces. Although there have been many attempts to fill the gaps of non-observation, there is little research to analyze the ratio of missing grids to overall sea grids and their seasonal patterns. This report introduces the method of quantifying the distribution of missing points and then shows how the missing points have spatial correlation and seasonal trends. Both temporal and spatial integration methods are compared to assess the effectiveness of reducing missing data. The temporal integration shows more outstanding performance than the spatial integration. Moran's I and K-function with statistical hypothesis testing show that missing grids are clustered and there is a non-random distribution from daily integration. The result of the seasonality test for Moran's I through a periodogram shows dependency on full-year, half-year, and quarter-year periods respectively. These analysis results can be used to deduce appropriate integration periods with permissible estimation errors.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.4
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• pp.60-74
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• 2007

For quantitative analysis of spatio-temporal distribution pattern on marine environment, spatial autocorrelation statistics on the both global and local aspects was applied to the observed data obtained from Gwangyang Bay in South Sea of Korea. Global indexes such as Moran's I and General G were used for understanding environmental distribution pattern in the whole study area. LISAs (local indicators of spatial association) such as Moran's I ($I_i$) and $G_i{^*}$ were considered to find similarity between a target feature and its neighborhood features and to detect hot spot and/or cold spot. Additionally, the significance test on clustered patterns by Z-scores was carried out. Statistical results showed variations of spatial patterns quantitatively in the whole year. Then all of general water quality, nutrients, chlorophyll-a and phytoplankton had strong clustered pattern in summer. When global indexes showed strong clustered pattern, the front region with a negative $I_i$ which means a strong spatial variation was observed. Also, when global indexes showed random pattern, hot spot and/or cold spot were/was found in the small local region with a local index $G_i{^*}$. Therefore, global indexes were useful for observing the strength and time series variations of clustered patterns in the whole study area, and local indexes were useful for tracing the location of hot spot and/or cold spot. Quantification of both spatial distribution pattern and clustering characteristics may play an important role to understand marine environment in depth and to find the reasons for spatial pattern.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.64-78
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• 2019

This paper explores key factors affecting taxi travel using global positioning system(GPS) data in Seoul, Korea, considering spatial dependence. We first analyzed the travel characteristics of taxis such as average travel time, average travel distance, and spatial distribution of taxi trips according to the time of the day and the day of the week. As a result, it is found that the most taxi trips were generated during the morning peak time (8 a.m. to 9 a.m.) and after the midnight (until 1 a.m.) on weekdays. The average travel distance and travel time for taxi trips were 5.9 km and 13 minutes, respectively. This implies that taxis are mainly used for short-distance travel and as an alternative to public transit after midnight in a large city. In addition, we identified that taxi trips were spatially correlated at the traffic analysis zone(TAZ) level through the Moran's I test. Thus, spatial regression models (spatial-lagged and spatial-error models) for taxi trips were developed, accounting for socio-demographics (such as the number of households, the number of elderly people, female ratio to the total population, and the number of vehicles), transportation services (such as the number of subway stations and bus stops), and land-use characteristics (such as population density, employment density, and residential areas) as explanatory variables. The model results indicate that these variables are significantly associated with taxi trips.

• Health Policy and Management
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• v.23 no.4
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• pp.387-396
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• 2013

Background: The purpose of this study was to analyze the association between areas of Korea Train Express (KTX) region and external medical service use in Korean society using spatial statistical model. Methods: The data which was used in this study was extracted from 2011 regional health care utilization statistics and health insurance key statistics from National Health Insurance Corporation. A total spatial units of 229 districts (si-gun-gu) were included in this study and spatial area was all parts of the country excepted Jeju, Ulleungdo island. We conducted Kruskal-Wallis test, correlation, Moran's I and hot-spot analysis. And after, ordinary linear regression, spatial lag, spatial error analysis was performed in order to find factors which were associated with external medical service use. The data was processed by SAS ver. 9.1 and Geoda095i (windows). Results: Moran's I of health insurance patients' external medical service use was 0.644. Also, population density, Seoul region, doctor factors positively associated with health insurance patients' external medical service. In contrast, average age, health care organization per 100 thousand were negatively associated with health insurance patients' external medical service use. Conclusion: The finding of this study suggested that health insurance patient's external medical service use correlated for seoul region in korea. The study results imply the need for more attention medical needs in the region (si-gun-gu unit) for health insurance patients of seoul region. It is important to adapt strategy to activation of primary health care as well as enhancing public health institution for prevent leakage of patients to other areas.

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.3
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• pp.79-88
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• 2007

This paper suggests a hierarchial method to select the target sites for the nonpoint source pollution management considering factors which reflect the interrelationships of significant outflow characteristics of nonpoint source pollution at given sites. The factors consist of land slope, delivery distance to the outlet, effective rainfall, impervious area ratio and soil loss. The weight of each factor was calculated by an analytic hierarchy process(AHP) algorithm and the resulting influencing index was defined from the sum of the product of each factor and its computed weight value. The higher index reflect the proposed target sites for nonpoint source pollution management. The proposed method was applied to the Baran HP#6 watershed, located southwest from Suwon city. The Agricultural Nonpoint Pollution Source(AGNPS) model was also applied to identify sites contributing significantly to the nonpoint source pollution loads from the watershed. The spatial correlation between the two results for sites was analyzed using Moran's I values. The I values were $0.38{\sim}0.45$ for total nitrogen(T-N), and $0.15{\sim}0.22$ for total phosphorus(T-P), respectively. The results showed that two independent estimates for sites within the test water-shed were highly correlated, and that the proposed hierarchial method may be applied to select the target sites for nonpoint source pollution management.

• Journal of Life Science
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• v.25 no.4
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• pp.369-375
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• 2015

Data on the spatial distribution of a plant population among administrative areas is useful for various purposes. In this study, I analyzed the spatial distribution of the geographical distances of Carex siderosticta at Mt. Geumjeong and Mt. Ahop in Korea. The aim was to test a spatial structure within two populations of C. siderosticta. Most natural plots of C. siderosticta are not uniformly distributed in the forest community; for example, uniform plots were aggregately distributed within a space of 6.0 m $\times$ 6.0 m. When the sampling plots were larger than 6.0 m $\times$ 12.0 m, the individuals of C. siderosticta were aggregately distributed. The neighboring patches of C. siderosticta were predominantly 7.5 m to 9.0 m apart, on average; however, if the natural populations were disturbed by human activities, the aggregation occurred in shorter distances than a scale of 9.0 m. Moran's I of C. siderosticta significantly differed from the expected value in only 16 of 40 cases (40%). In conclusion, the geographical distribution of C. siderosticta is not even, with varying degrees of size in the plots, while human activities give rise to density effects in the plots at both Mt. Geumjeong and Mt. Ahop in Korea.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.3
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• pp.77-84
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• 2015

The key objective of this research is to review the effectiveness of spatial regression to identify the influencing factors of spatial distribution patterns of floating population. To this end, global and local spatial autocorrelation test were performed using seoul floating population survey(2014) data. The result of Moran's I and Getis-Ord $Gi^*$ as used in the analysis derived spatial heterogeneity and spatial similarities of floating population patterns in a statistically significant range. Accordingly, Geographically Weighted Regression was applied to identify the relationship between land use attributes and population floating. Urbanization area, green tract of land of micro land cover data were aggregated in to $400m{\times}400m$ grid boundary of Seoul. Additionally public transportation variables such as intersection density transit accessibility, road density and pedestrian passage density were adopted as transit environmental factors. As a result, the GWR model derived more improved results than Ordinary Least Square(OLS) regression model. Furthermore, the spatial variation of applied local effect of independent variables for the floating population distributions.