• The Korean Journal of Applied Statistics
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• v.18 no.2
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• pp.271-280
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• 2005

Kriging methods as traditional spatial data analysis methods and geographical weighted regression models as statistical analysis methods are compared. In this paper, we apply data from the Ministry of Environment to spatial analysis for practical study. We compare these methods to performance with monthly carbon monoxide observations taken at 116 measuring area of air pollution in 1999.

• Journal of Korean Society for Geospatial Information Science
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• v.3 no.1 s.5
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• pp.139-150
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• 1995

The assessment/evaluation of land use suitability is an important part of land use planning. In this paper, we developed. The Expert System for a suitability analysis including the function of data storage, analysis, assessment and display by using Borland C++ Language and could suggest the following results in the suitability analysis to select a site for an industrial complex using this system. 1. With the increase in volume and variety of geo-spatial data now available, it has become necessary to find more efficient ways of storing this data. This report presents the Quadtree structure, as a method of gaining significant savings over conventional raster processing in data storage. 2. In order to get the criteria of suitability analysis, the opinions of specialists, administrative officers and citizens were collected by a questionnaire, and used to calculate the weight of geo-spatial data. Also, The Expert System, which we developed, was designed to do overlay and spatial analysis, as well as reflect the various opinions we collected in the questionnaire. The Expert System is expected to be used in other land use planning.

• Journal of Environmental Impact Assessment
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• v.22 no.1
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• pp.19-26
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• 2013

The propose of this study is to analyze the optimum spatial resolution of the urban spatial thermal environment structure and to evaluate of the possibility detection using aerial photographs and thermal satellite images. The proper techniques of the optimum spatial resolution for the urban spatial thermal environment structure were analyzed. Thermal infrared satellite image of Seoul city were used for the change rate of surface temperature variation and suggested to the spatial extent and effects of urban surface characteristics and spatial data was interpreted as regions. To extract the surface temperature, Landsat thermal infrared satellite image compared with an automatic weather station data and in the field of the measured temperature and surface temperature by thermal environment affects, the spatial domain has been verified. The surface temperature of the satellite images to extract after adjusting surface temperature isotherms were constructed. The changes in surface temperature from 2008 to 2012 the average surface temperature observation images of changing areas were divided into space. The results of this study are as follows: Through analysis of satellite imagery, Seoul city surface temperature change due to extraction comfort indices were classified into four grades. The comfort index indicative of the temperature of Gangnam-gu, $23.7{\sim}27.2(^{\circ}C)$ range and Songpagu, a $22.7{\sim}30.6(^{\circ}C)$ respectively, the surface temperature of Yeouido $25.8{\sim}32.6(^{\circ}C)$ were in the range.

• Proceedings of the Korea Contents Association Conference
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• 2006.05a
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• pp.71-74
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• 2006

By the progress of Information Technology, spatial data have been recognizes as one of essential infrastructure. Now for the near future needs of urban simulation, management, u-City construction, etc. MOCT(Ministry Of Construction & Transportation) have been driving to construct the 3D Geo-spatial Data as one of National Spatial Data Information on a base of 2D GIS(Geographic Information System). In this study we tried to analysis the demands and the optimum implementation method of 3D Geo-spatial Data in local governments. As the result of study, the plan to utilize 3D Geo-spatial Data and to carry out its utilization, and the advanced vision of 3D GIS in for the public affairs of Local Governments and private business scope were proposed.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.1260-1264
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• 2009

Precipitation time series is a mixture of complicate fluctuation and changes. The monthly precipitation data of 61 stations during 36 years (1973-2008) in Korea are comprehensively analyzed using the EOFs technique and CSEOFs technique respectively. The main motivation for employing this technique in the present study is to investigate the physical processes associated with the evolution of the precipitation from observation data. The twenty-five leading EOF modes account for 98.05% of the total monthly variance, and the first two modes account for 83.68% of total variation. The first mode exhibits traditional spatial pattern with annual cycle of corresponding PC time series and second mode shows strong North South gradient. In CSEOF analysis, the twenty-five leading CSEOF modes account for 98.58% of the total monthly variance, and the first two modes account for 78.69% of total variation, these first two patterns' spatial distribution show monthly spatial variation. The corresponding mode's PC time series reveals the annual cycle on a monthly time scale and long-term fluctuation and first mode's PC time series shows increasing linear trend which represents that spatial and temporal variability of first mode pattern has strengthened. Compared with the EOFs analysis, the CSEOFs analysis preferably exhibits the spatial distribution and temporal evolution characteristics and variability of Korean historical precipitation.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.2
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• pp.40-51
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• 2021

The purpose of this study is to diagnose urban spatial structures using spatial modeling techniques for balanced urban development as part of sustainable urban growth management. Since urban spatial structure is an interaction of various activities, it is necessary to interpret the analysis results in conjunction with the analysis of changes in spatial structural elements. In this study, population and transportation were approached for research purposes. Population data were applied to the Getis-Ord G_i^* method, a spatial statistical technique, to analyze the concentration-decreasing region of the population. Traffic data analyzed the trend of centrality change by applying commuting traffic O-D data to Social Network Analysis techniques. The analysis showed that urban imbalance was growing, and the centrality of transportation was changing. The results of the analysis of spatial structure elements could be interpreted by linking the results of each factor to each neighborhood unit, predicting changes in urban spatial structure and suggesting directions for sustainable urban growth management.These results could also be used as a decision-making tool for various urban growth management policies introduced to cope with rapid urban development and uncontrollable development in many cities around the world.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.329-332
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• 2007

Annual vegetation growth patterns are determined by the intrinsic phenological characteristics of each land cover types. So, if typical growth patterns of each land cover types are well-estimated, and a NDVI time-series data of a certain area is compared to those estimated patterns, we can implement more advanced analyses such as a land surface-type classification or a land surface type change detection. In this study, we utilized Terra MODIS NDVI 250m data and compressed full annual NDVI time series data into several indices using the Harmonic Analysis of Time Series(HANTS) algorithm which extracts the most significant frequencies expected to be presented in the original NDVI time-series data. Then, we found these frequencies patterns, described by amplitude and phase data, were significantly different from each other according to vegetation types and these could be used for land cover classification. However, in spite of the capabilities of the HANTS algorithm for detecting and interpolating cloud-contaminated NDVI values, some distorted NDVI pixels of June, July and August, as well as the long rainy season in Korea, are not properly corrected. In particular, in the case of two or three successive NDVI time-series data, which are severely affected by clouds, the HANTS algorithm outputted wrong results.

• Journal of Digital Convergence
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• v.19 no.8
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• pp.33-42
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• 2021

As smartphone-based tourism platforms have become active, policy establishment and service enhancement using review data are being made in various fields. In the case of the preceding studies using tourism review data, most of the studies centered on domestic tourists were conducted, and in the case of foreign tourist studies, studies were conducted only on data collected in some languages and text mining techniques. In this study, 3,515 review data written by foreigners were collected by designating the "Daegu attractions" keyword through the online review site. And LDA-based topic modeling was performed to derive tourism topics. The spatial approach through global and local spatial autocorrelation analysis for each topic can be said to be different from previous studies. As a result of the analysis, it was confirmed that there is a global spatial autocorrelation, and that tourist destinations mainly visited by foreigners are concentrated locally. In addition, hot spots have been drawn around Jung-gu in most of the topics. Based on the analysis results, it is expected to be used as a basic research for spatial analysis based on local government foreign tourism policy establishment and topic modeling. And The limitations of this study were also presented.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.2
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• pp.64-77
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• 2021

The purpose of this study is to examine the spatial distribution of highly educated human capital and to identify key factors affecting their spatial distribution. We analyzed the spatial concentration and inequality using Gini's coefficient and exploratory spatial data analysis and identified the economic and amenity factors to affect the spatial concentration of highly educated human capital using spatial regression model. The findings show that the spatial pattern of highly educated human capital is concentrated, imbalanced, and clustered in Capital region and part of Chungcheong and Gangwon region. The spatial concentration were more affected by economic factor than by amenity factors. This study provides some implication on the regional economic strategies to attract the human capital.

• Spatial Information Research
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• v.23 no.5
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• pp.53-64
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• 2015

Several countries have built National Spatial Data Infrastructure (NSDI) for information sharing among various fields. One of the important factors of NSDI is framework data, which is the most commonly used geospatial data across various fields. Previous studies on the framework data suggest components based on frequency survey and case study. However, such research methods do not have objectivity in setting the components of the framework data. This research uses factor analysis with 104 medium-level layers from the most widely used National Base Map and 5 layers from the other sources including cadastre and aerial image. Each layer is scaled with usage level as four different patterns of 1) background data, 2) reference data, 3) base data, and 4) other data, respectively. The analysis results show that the layers are grouped into 5 to 7 factors according to the patterns. ANOVA reveals that the mean differences between the factors with high values and the other factors with low values under each pattern are statistically significant. Such high value factors under each pattern consist of similar layers, close to identical, with those under the other categories. This research proposes framework data system, including transportation, building, hydrography, elevation, administrative district, digital orthoimagery, geodetic control, and cadastral based on the analysis results. Proposed framework in this research will be a basis of establishing spatial data sharing system. For sharing proposed framework data in various fields, these data must be established and distributed as actual standard and also related future researches should be performed.