• Journal of Korea Planning Association
• /
• v.54 no.2
• /
• pp.93-108
• /
• 2019

This study examines the relationship between three-dimensional urban built environment and urban surface temperature using LANDSAT 8 satellite image data in Seoul city. The image was divided into 600m×600m grid units as an unit of analysis. Due to the high level of spatial dependency in surface temperature, this study uses spatial statistics to take into account spatial auto-correlation. The spatial error model shows the best goodness of fit. The analysis results show that the three-dimensional built environment and transport environment as well as natural environment have statistically significant associations with surface temperature. First, natural environment variables such as green space, streams and river, and average elevation show statistically significant negative association with surface temperature. Second, the building area shows a positive association with surface temperature. In addition, while sky view factor (SVF) has a positive association with surface temperature, surface roughness (SR) shows a negative association with it. Third, transportation related variables such as road density, railway density, and traffic volume show positive associations with surface temperature. Moreover, this study finds that SVF and SR have different effects on surface temperature in regard to the levels of total floor areas in built environment. The results indicate that interactions between floor area ratio (FAR) and three-dimensional built environmental variables such as SVF and SR should be considered to reduce urban surface temperature.

• Journal of Agricultural Extension & Community Development
• /
• v.26 no.4
• /
• pp.181-191
• /
• 2019

The purpose of this study is to identify the characteristics of young farmers' residential location characteristics. Based on residential location theory and previous studies on the stated preference for residential environment of young farmers, this study develops a spatial econometrics model using housing and neighborhood variables, accessibility variables, natural environment variables and farm economics and management variables. The findings suggest that the higher rate of young farmers has a positive relationship with higher population density, higher housing price, closer distance to city centers and Eup districts compared to Myeon districts. In addition, areas which have higher rate of farmers with high sales and growing certain crops such as fruits and vegetables are revealed to have higher rate of young farmers. This study presents that maintaining rural vitality is also crucial for attracting young farmers to rural areas and remaining them in the farm as active agricultural workforce.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.22 no.1
• /
• pp.1-18
• /
• 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 the Korean Institute of Landscape Architecture
• /
• v.32 no.5
• /
• pp.23-34
• /
• 2004

In this study, 1 dependent variable and 9 independent variables were established to examine suitable illuminance by spaces in urban parks in consideration of night users' psychological reactions and activity types. Such fixed variables were evaluated by a series of experiments of changing illuminance, and correlation among those variables was verified by correlation analysis and multiple regression analysis to suggest suitable illuminance by spaces. The results of this study are as follows: 1) The independent variables influencing suitable illuminance by spaces in urban parks were directly influenced rather by the psychological reaction of night users than the activity types by spatial functions. 2) Securing suitable illuminance by spaces commonly increased spatial availability, created certain atmosphere, and provided safety in the psychological reaction of night users. 3) Suitable illuminance by spaces in urban parks is: Central square is 31.88lx, resting space 6.30lx, exercising space 33.14lx, children's playground 14.19lx, pedestrian road 12.29lx, entry space 16.30lx, and green space 7.03lx. That is, when a place had more positive activities, spatial illuminance was increased. 4) Though comparison by spaces with the illuminance standard for urban parks as mentioned in KS A 3011-1993 can not be made, such illuminance was relatively compatible with the permissible range of illuminance in the author's opinion. It is expected that this study investigating suitable illuminance by spaces for night use in urban parks, will provide necessary knowledge for securing suitable illuminance by spaces in urban parks through classifyingin detail the illuminance standard of KS A 3011-1993. Besides, by helping make us aware of the importance of illuminance in urban parks as well as of external space in the night, this study will contribute to academic research and development in the field of landscape architecture and associated fields and be utilized in establishing legal and institutional standards.

• Journal of Korean Society for Geospatial Information Science
• /
• v.20 no.3
• /
• pp.57-63
• /
• 2012

The ordinary least square (OLS) regression model is assumed that the relationship between distribution of longevity population and environmental factors to be identical. Therefore, the OLS regression analysis can't explain sufficiently the spatial characteristics of longevity phenomenon and related variables. The geographically weighted regression (GWR) model can be representing the spatial relationship of adjacent area using geographically weighted function. It also characterized which can locally explain the spatial variation of distribution of longevity population by environmental characteristics. From this point of view, this study was performed the comparative analysis between OLS and GWR model for ecological factors of longevity existing studies. In the results, GWR model has higher corresponded to model than OLS model and can be accounting for spatial variability about effect of specific environmental variables.

• Environmental Analysis Health and Toxicology
• /
• v.30
• /
• pp.10.1-10.14
• /
• 2015

Recent cohort studies have relied on exposure prediction models to estimate individual-level air pollution concentrations because individual air pollution measurements are not available for cohort locations. For such prediction models, geographic variables related to pollution sources are important inputs. We demonstrated the computation process of geographic variables mostly recorded in 2010 at regulatory air pollution monitoring sites in South Korea. On the basis of previous studies, we finalized a list of 313 geographic variables related to air pollution sources in eight categories including traffic, demographic characteristics, land use, transportation facilities, physical geography, emissions, vegetation, and altitude. We then obtained data from different sources such as the Statistics Geographic Information Service and Korean Transport Database. After integrating all available data to a single database by matching coordinate systems and converting non-spatial data to spatial data, we computed geographic variables at 294 regulatory monitoring sites in South Korea. The data integration and variable computation were performed by using ArcGIS version 10.2 (ESRI Inc., Redlands, CA, USA). For traffic, we computed the distances to the nearest roads and the sums of road lengths within different sizes of circular buffers. In addition, we calculated the numbers of residents, households, housing buildings, companies, and employees within the buffers. The percentages of areas for different types of land use compared to total areas were calculated within the buffers. For transportation facilities and physical geography, we computed the distances to the closest public transportation depots and the boundary lines. The vegetation index and altitude were estimated at a given location by using satellite data. The summary statistics of geographic variables in Seoul across monitoring sites showed different patterns between urban background and urban roadside sites. This study provided practical knowledge on the computation process of geographic variables in South Korea, which will improve air pollution prediction models and contribute to subsequent health analyses.

• International Journal of High-Rise Buildings
• /
• v.5 no.2
• /
• pp.95-103
• /
• 2016

One of the key problems in the design of high-rise commercial complex is how to guide reasonable pedestrian distribution in commercial space. In this study, pedestrian distribution in three high-rise commercial complexes in Shanghai and Hong Kong was studied using spatial configuration analysis software Space Syntax and quantification of physical elements in commercial spaces, such as functional attractiveness, entrances, escalators, level variations and passage width. Additionally, in an attempt to integrate functions with spatial integration and spatial depth, two combination variables, the spatial coefficient of function (IF) and spatial depth coefficient of function (F/D), were proposed. The results of the correlation analysis and multiple regression analyses reflected the following: (1) Regarding the influence on pedestrian distribution, there was a synergistic and complementary relationship between function and space; (2) The comprehensive flow distribution analytic model could successfully interpret flow distribution in high-rise commercial complexes and its R Square ranged up to about 70% in the three cases; (3) The spatial coefficient of function (IF) and spatial depth coefficient (F/D) could effectively integrate functions and spatial configuration, which could help close the gap between over-emphasis on function in commercial research and the lack of consideration of function in space-syntax analysis.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.17 no.4
• /
• pp.124-137
• /
• 2018

The main purpose of this study is to find the hotspots of crimes that occur frequently in the space and to derive the appropriate CCTV installation location. One of the characteristics of crime is clustered around past occurrence area, and these crimes are strongly correlated. It is also possible to find the cause of the clusters and the variables that affect the crime through the history of the crime. In addition to the traditional OLS model, spatial differential model including spatial autocorrelation and spatial error model were used to select the variables influencing the five major crime rate, the theft rate and the foreign resident rate. The variables affecting the Five major crimes were positive (+) sign for the welfare and the rate of the bar cluster rate, and negative (-) for the street density. The CCTV area occupies 46% of the hotspots based on the overlapping of the areas where the elderly people are crowded, the bar cluster, many multicultural families, and the areas with low density of street lamps. It turned out. Taking into account the current CCTV operation, the total number of new cases to cover the risk point was 89.

• Journal of Preventive Medicine and Public Health
• /
• v.51 no.1
• /
• pp.33-40
• /
• 2018

Objectives: The aim of this study was to determine the factors associated with the spatial distribution of the incidence of colorectal cancer (CRC) in the neighborhoods of Tehran, Iran using Bayesian spatial models. Methods: This ecological study was implemented in Tehran on the neighborhood level. Socioeconomic variables, risk factors, and health costs were extracted from the Equity Assessment Study conducted in Tehran. The data on CRC incidence were extracted from the Iranian population-based cancer registry. The $Besag-York-Molli{\acute{e}}$ (BYM) model was used to identify factors associated with the spatial distribution of CRC incidence. The software programs OpenBUGS version 3.2.3, ArcGIS 10.3, and GeoDa were used for the analysis. Results: The Moran index was statistically significant for all the variables studied (p<0.05). The BYM model showed that having a women head of household (median standardized incidence ratio [SIR], 1.63; 95% confidence interval [CI], 1.06 to 2.53), living in a rental house (median SIR, 0.82; 95% CI, 0.71 to 0.96), not consuming milk daily (median SIR, 0.71; 95% CI, 0.55 to 0.94) and having greater household health expenditures (median SIR, 1.34; 95% CI, 1.06 to 1.68) were associated with a statistically significant elevation in the SIR of CRC. The median (interquartile range) and mean (standard deviation) values of the SIR of CRC, with the inclusion of all the variables studied in the model, were 0.57 (1.01) and 1.05 (1.31), respectively. Conclusions: Inequality was found in the spatial distribution of CRC incidence in Tehran on the neighborhood level. Paying attention to this inequality and the factors associated with it may be useful for resource allocation and developing preventive strategies in at-risk areas.

• Journal of Engineering Education Research
• /
• v.18 no.5
• /
• pp.42-50
• /
• 2015

In spite that spatial ability has been recognized as an important element of academic achievement in engineering studies, researches on the topic are rather limited in Korea. In this study, the relationship between spatial visualization skill and academic achievement of engineering students was investigated based on the several variables such as gender, high school education background and college course achievement. The result showed that there were significant relevance between spatial visualization skill and gender, high school type, achievement of high school level math & physics, and college course work grade of computer graphic and capstone design. According the case study, from the entry time of engineering college, support programs to reinforce spatial visualization skill are required for lower skill groups such as female and graduate from art course in high school. Also, college curriculum such as Engineering graphics, Capstone design are substantial to improve spatial visualization skill. However, more diversified sample groups and research methods are required in order to draw in depth results.