• Management & Information Systems Review
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• v.37 no.3
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• pp.27-47
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• 2018

In this study, we examine how land use zoning affects the land price controlling other variables such as road-facing condition of the land, land form, land age after its development and land size. We employ geographically weighted regression analysis which reflects spatial dependency as methodology with a data sample of land transaction price data of Jangyu, a new town, in Korea. The results of our empirical analysis show that the respective coefficients of traditional regression and geographically weighted regression are not significantly different. However, after calculating Moran's Index with residuals of both OLS and GWR models, we find that Moran's Index of GWR decreases around 26% compared to that of OLS model, thus improving the problem of spatial autoregression of residuals considerably. Unlike our expectation, though, in both traditional regression and geographically weighted regression where residential exclusive area is used as a reference variable, the dummy variable of the residential land for both housing and shops shows a negative sign. This may be because the residential land for both housing and shops is usually located in the level area while the residential exclusive area is located at the foot of a mountain or on a gentle hill where the residents can have good quality air and scenery. Although the utility of the residential land for both housing and shops is higher than its counterpart's since it has higher floor area ratio, amenity which can be explained as high quality of air and scenery in this study seems to have higher impact in purchase of land for housing. On the other hand, land for neighbourhood living facility seems to be valued higher than any other land zonings used in this research since it has much higher floor area ratio than the two land zonings above and can have a building with up to 5 stories constructed on it. With regard to road-facing condition, land buyers seem to prefer land which faces a medium-width road as expected. Land facing a wide-width road may have some disadvantage in that it can be exposed to noise and exhaust gas from cars and that entrance may not be easy due to the high speed traffic of the road. In contrast, land facing a narrow road can be free of noise or fume from cars and have privacy protected while it has some inconvenience in that entrance may be blocked by cars parked in both sides of the narrow road. Finally, land age variable shows a negative sign, which means that the price of land declines over time. This may be because decline of the land price of Jangyu was bigger than that of other regions in Gimhae where Jangyu, a new town, also belong, during the global financial crisis of 2008.

• Journal of the Economic Geographical Society of Korea
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• v.23 no.1
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• pp.56-70
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• 2020

This study identifies the impact of social network service (SNS) on the spatial characteristics of retail stores locations in the hyper-connected society, which have been closely related to the everyday lives of urban residents. In particular, we focus on the changes in the spatial distribution of restaurants since the information retrieval process was added to the decision-making process of a consumer's restaurant selection. Empirically, we analyze restaurants in Seoul, Korea since the smart-phone was introduced. By applying the kernel density estimation and Moran's I index, we examine the changes in the spatial distribution pattern of restaurants during the last ten years for running, newly-open and closed restaurants as well as SNS popular ones. Finally, we develop a spatial regression model to identify geographic features affecting their locations. As the results, we identified geographical variables and online factors that influence the location of restaurants. The results of this study could provide important groundwork for food and beverage location planning and policy formulation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.391-397
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• 2008

This paper analyzes the spatial patterns of population distribution in Seoul Metropolitan Area in terms of spatial association using spatial statistics and spatial exploratory technique. Our empirical analysis based on global index shows that, in Seoul Metropolitan Area, the population had been distributed with strong positive spatial association over the period of 1980-2005. It implies that the population of each region is affected by the population distribution of adjacent regions. In addition, the analysis using local index was conducted for detecting the local patterns of spatial association, and the result shows that the clusters of population had been moved in the direction of West(Incheon and Bucheon) and South(Anyang and Seongnam) of Seoul where a large scale of lands or towns were developed over the period. These results will be the preliminary data for establishing management and development plans of Seoul Metropolitan Area.

• Journal of the Korean Institute of Landscape Architecture
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• v.48 no.5
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• pp.67-79
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• 2020

Plans to mitigate overheating in urban areas requires the identification of the characteristics of the thermal environment of the city. The key information is the distribution of higher and lower temperatures (referred to as "hotspot" or "coldspot", respectively) in the city. This study aims to identify the areas within Jeonju City that are suffering from increasing land surface temperatures (LST) and the factors linked to such this phenomenon. To identify the hot and cold spots, Local Moran's I and Getis-Ord Gi^* were calculated for the LST based on 2017 images taken using the thermal band of the Landsat 8 satellite. Hotspot analysis revealed that hotspot regions, (the areas with a high concentration of Land Surface Temperature) are located in the old town area and in industrial districts. To figure out the factors linked to the hotspots, a correlation analysis, and a regression analysis taking into account environmental covariates including Normalized Difference Vegetation Index (NDVI) and land cover. The values of NDVI showed that it had the strongest effect on the lowering LSTs. The results of this study are expected to provide directions for urban thermal environment designing and policy development to mitigate the urban heat island effect in the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.4
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• pp.162-174
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• 2012

To visualize the characteristics of vertical seawater temperature data, in the ocean having 3D spatial characteristics, 2D thematic maps like horizontal seawater temperature distribution map at each depth layer and 3D volume model using 3D spatial interpolation are used. Although these methods are useful to understand oceanographic phenomena visually, there is a limit to analyze the spatial pattern of vertical temperature distribution or the relationship between vertical temperature characteristics and other oceanic factors (seawater chemistry, marine organism, climate change, etc). Therefore, this study aims to determine the spatial distribution characteristics of vertical temperature profiles in the South Sea of Jeju by quantifying the characteristics of vertical temperature profiles by using an algorithm that can extract the thermocline parameters, such as mixed layer depth, maximum temperature gradient and thermocline thickness. For this purpose spatial autocorrelation index (Moran's I) was calculated including mapping of spatial distribution for three parameters representing the vertical temperature profiles. Also, after grouping study area as four regions by using cluster analysis with three parameters, the characteristics of vertical temperature profiles were defined for each region.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.3
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• pp.1149-1154
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• 2014

Background: In Malaysia, data from the Malaysian Health Ministry showed colorectal cancer (CRC) to be the second most common type of cancer in 2007-2009, after breast cancer. The same was apparent after looking at males and females cases separately. In the present study, the Geographic Information System (GIS) was employed to describe the distribution of CRC cases in Kuala Lumpur (KL), Malaysia, according to socio-demographic factors (age, gender, ethnicity and district). Materials and Methods: This retrospective review concerned data for patients diagnosed with colorectal cancer in the years 1995 to 2011 collected from the Wilayah Persekutuan Health Office, taken from the cancer notification form (NCR-2), and patient medical records from the Surgical Department, Universiti Kebangsaan Malaysia Medical Centre (UKMMC). A total of 146 cases were analyzed. All the data collected were analysed using ArcGIS version 10.0 and SPSS version 19.0. Results: Patients aged 60 to 69 years accounted for the highest proportion of cases (34.2%) and males slightly predominated 76 (52.1%), Chinese had the highest number of registered cases at 108 (74.0%) and staging revealed most cases in the 3rd and 4th stages. Kernel density analysis showed more cases are concentrated up in the northern area of Petaling and Kuala Lumpur subdistricts. Spatial global pattern analysis by average nearest neighbour resulted in nearest neighbour ratio of 0.75, with Z-score of -5.59, p value of <0.01 and the z-score of -5.59. Spatial autocorrelation (Moran's I) showed clustering significant with p<0.01, Z score 3.14 and Moran's Index of 0.007. When mapping clusters with hotspot analysis (Getis-Ord Gi), hot and cold spots were identified. Hot spot areas fell on the northeast side of KL. Conclusions: This study demonstrated significant spatial patterns of cancer incidence in KL. Knowledge about these spatial patterns can provide useful information to policymakers in the planning of screening of CRC in the targeted population and improvement of healthcare facilities to provide better treatment for CRC patients.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.295-304
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• 2020

The IPCC (Intergovernmental Panel on Climate Change) recommended the importance of preventive measures against extreme weather, and heat waves are one of the main themes for establishing preventive measures. In this study, we tried to analyze the heat vulnerable areas by considering not only spatial characteristics but also social characteristics. Energy consumption, popu lation density, normalized difference vegetation index, waterfront distance, solar radiation, and road distribution were examined as variables. Then, by selecting a suitable model, SLM (Spatial Lag Model), available variables were extracted. Then, based on the Fuzzy theory, the degree of vulnerability to heat waves was analyzed for each variable, and six variables were superimposed to finally derive the heat vulnerable area. The study site was selected as the Daegu area where the effects of the heat wave were high. In the case of vulnerable areas, it was confirmed that the existing urban areas are mainly distributed in Seogu, Namgu, and Dalseogu of Daegu, which are less affected by waterside and vegetation. It was confirmed that both spatial and social characteristics should be considered in policy support for reducing heat waves in Daegu.

• 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.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.1-18
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• 2019

This research measured and visualized the spatial dependency and the spatial heterogeneity of the small business in Cheonan-si, Asan-si with $100m{\times}100m$ grids based on global and local spatial autocorrelation. First, we confirmed positive spatial autocorrelation of small business in the research area using Moran's I Index, which is ESDA(Exploratory Spatial Data Analysis). And then, through Getis-Ord $GI{\ast}$, one kind of LISA(Local Indicators of Spatial Association), local patterns of spatial autocorrelation were visualized. These verified that Spatial Regression Model is valid for the location factor analysis on small business commercial buildings. Next, GWR(Geographically Weighted Regression) was used to analyze the spatial relations between the distribution of small business, hourly mobile traffic-based floating population, land use attributes index, residence, commercial building, road networks, and the node of traffic networks. Final six variables were applied and the accessibility to bus stops, afternoon time floating population, and evening time floating population were excluded due to multicollinearity. By this, we demonstrated that GWR is statistically improved compared to OLS. We visualized the spatial influence of the individual variables using the regression coefficients and local coefficients of determinant of the six variables. This research applied the measured population information in a practical way. Reflecting the dynamic information of the urban people using the commercial area. It is different from other studies that performed commercial analysis. Finally, this research has a differentiated advantage over the existing commercial area analysis in that it employed hourly changing commercial service population data and it applied spatial statistical models to micro spatial units. This research proposed new framework for the commercial analysis area analysis.

• Journal of Korean Society of Forest Science
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• v.102 no.1
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• pp.113-121
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• 2013

It has been known that edges of forest fire areas play significant roles in post-fire change of forest ecosystem and recovery process. The purpose of this study was to analyze the relationships between edge formation of burned forests and landscape characteristics with consideration on spatial autocorrelation. Samcheok fire site burned in 2000 was selected as the study area. Seven hundred fifty three of 500 $m^2$ grid cells were generated for measuring landscape characteristics. This study used the topographic variables including slop, elevation, topographic wetness index, solar radiation index and proportions of fuel and land use types. In delineating landscape characteristics correlation analysis with modified t-test were performed for exploring the relationships between edge formation and landscape characteristics. The results indicated that edge formation of burned forests was positively correlated with most variables including TWI, SRI, water, paddy, developed, farm, grass, bare soil, and negatively related with elevation, slope and all fuel types. Especially TWI (r=0.437) showed a strong positive correlation with edge formation. According to the results, edge of burned forests were likely formed when proportions of heterogeneous land use types were high with mild slope and low elevation.