• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.4D
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• pp.509-521
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• 2009

In modern society the architecture surface involves a lot of meaning other than having simple physical functions. The interface space generated by the surface characteristics among those becomes to have many significances in modern society, and plays a role of symbolic space of a city. The interface space is threshold space that connects two separate spaces and revitalize its states. Nowadays, people have many chances to communicate each other through the interface space and also settle urban problems caused by spacial and functional discontinuity through the interface space. However, the interface space in Korea could not be built up well due to rapid growth of cities, and a lot of different natures in space and viewpoint have been appeared accordingly, which gives rise to a problem of the discontinuity of urban spaces. Therefore, this study aims at the research on the characteristics of interface space through architecture surface composing the major factor of a city; architecture integument in Nam-po Dong, Jung Gu, Busan City as the object of the study.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.213-213
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• 2018

최근 기후변화로 인한 강우 패턴이 변화하고 있으며 강도가 큰 강우의 발생빈도가 높아짐에 따라 홍수의 위험성이 증가하고 있다. 또한, 강우발생의 공간적 이질성이 더욱 증가하는 실정이며, 지역적 강우특성은 각 유역의 지형적 특성과 맞물려 홍수특성을 나타낸다. 이러한 상황은 보다 상세한 지역적 특성을 반영하여 홍수를 대처하는 방어 체계가 요구되며, 행정구역간 강우의 특성을 분석하여 할 필요가 있다. 이와 관련하여 본 연구에서는 낙동강권역에 강우의 지역적 특성을 파악하기 위해, 행정구역별 강우에 대한 빈도분석을 실시하였다. 이를 위하여 과거 기상청의 홍수 예 경보 기준을 분석하였으며, 낙동강권역에 해당되는 70개 행정구역(시,군,구)에 해당되는 기상청 및 국토교통부의 강우관측소의 데이터를 사용하였다. 본 연구 결과는 같은 빈도에서 행정구역별로 강우의 크기가 상당히 달랐으며 특정시기에 발효된 호우특보와 해당 행정구역에 100년 빈도의 강우크기에 차이가 있는 것으로 나타났다. 행정구역별 홍수위험전망 매트릭스를 구축하는데 있어 행정구역별 홍수 위험의 크기를 결정하는데 본 연구 결과가 적용될 수 있다고 판단된다. 또한, 국가 홍수 재해 연구를 진행할 때 유역단위 및 행정구역별 홍수 방어방안을 활용함으로써 관련 연구들의 연구방안에 기본 자료로 활용될 수 있을 것으로 사료된다.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.33 no.4
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• pp.52-64
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• 2015

This study was carried out investigation of characteristics palace gardens representing historical background, political and cultural identity in Korea, China, and Japan. It had been done a comparative analysis in formation, location and site layout, site composition, landscape elements and planning, landscape technique and vista for palace gardens in East asia's three countries. In order to process this study, Changdeokgung Palace in Korea, Summer Palace in China and Sento Imperial Palace in Japan were selected based on similar status. therefore it provide theoretical foundation to investigate the identity of palace gardens in three countries. Furthermore the study determined homogeneity(similarity) and heterogeneity(differentiation) of the characteristics between palace gardens in three countries through the in-depth comparative analysis in order to investigate identity of palace gardens in three countries and to present the value of Korean palace garden. Homogeneity and heterogeneity between palace gardens in three countries deducted from the study were summarized as follows; First, it shows indigenous style of Korean garden throughout adapting natural terrain without natural destruction. Second, various symbolic elements which ie reflected East asian ideologies present in the gardens. Chinese thoughts and technique were influenced in the development of palace garden in Korea and implemented in similar ways of China. Homogeneity of utilizing waterscape could be found in three countries. Lastly, Palace garden in Changdeokgung had played a role as cultural place with taste for the arts rather than representing authority of the throne. It appears to be similar in China and Japan. The reason how Korea, China and Japan established their own independent style is that each palace garden had been developed to embrace indigenous culture with introduced elements even though they were closely bound up with culture.

• Survey Research
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• v.10 no.3
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• pp.1-19
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• 2009

This study investigates the utilities of spatial analysis in the context of survey research using Geographical Information System(GIS) and Geographically Weighted Regression (GWR) which take account of spatial heterogeneity. Many social phenomena involve spatial dimension, and with the development of GIS, GPS receiver, and online location-based services, spatial information can be collected and utilized more easily, and thus application of spatial analysis in the survey research is getting easier. The traditional OLS regression models which assume independence of observations and homoscedasticity of errors cannot handle spatial dependence problem. GWR is a spatial analysis technique which utilizes spatial information as well as attribute information, and estimated using geographically weighted function under the assumption that spatially close cases are more related than distant cases. Residential survey data from a Primary Autonomous District are used to estimate a model of public service satisfaction. The findings show that GWR handles the problem of spatial auto-correlation and increases goodness-of-fit of model. Visualization of spatial variance of effects of the independent variables using GIS allows us to investigate effects and relationships of those variables more closely and extensively. Furthermore, GIS and GWR analyses provide us a more effective way of identifying locations where the effect of variable is exceptionally low or high, and thus finding policy implications for social development.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.1
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• pp.121-129
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• 2009

Today, it is difficult to re-use and share spatial information, because of the explosive growth of heterogeneous information and specific characters of spatial information accumulated by diverse local agency. A spatial analysis of subsurface spatial informa-tion, one of the National Spatial Data Infrastructure, needs related spatial information such as, topographical map, geologic map, underground facility map, etc. However, current methods using standard format or spatial datawarehouse cannot consider a se-mantic hetergenity. In this paper, the layered ontology model which consists of generic concept, measuremnt scale, spatial model, and subsurface spatial information has developed. Also, the current ontology building method pertained to human experts is a expensive and time-consuming process. We have developed the MDA-based metamodel(UML Profile) of ontology that can be a easy under-standing and flexiblity of environment change. The semantic quality of devleoped ontology model has evaluated by reasoning engine, Pellet. We expect to improve a semantic sharing, and strengthen capacities for developing GIS experts system using knowledge representation ability of ontology.

• Journal of the Korean Institute of Landscape Architecture
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• v.15 no.1
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• pp.39-67
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• 1987

The purpose of this thesis is to suggest objective basic data for the environmental design through the quantitative analysis of the visual quality included in the physical environment of forest landscape. For this, landscape values of forest landscape have been evaluated by using the Iverson method, the images structure of forest landscape's main utilizing space have been analysed by the factor analysis algorithm, degree of visual preferences have been pleasured mainly by questionnaries and SBE method, and finally these thesis can be summarized as fallow LCP with high values of Iverson factors I and IV yield high landscape value. Specifically, Iverson factor IV has been found to play the dominant. For all experimental points, significant seasonal variations in S.D. scale values have been observed. In natural parks, where artificial structures are complementary to the natural landscape, main factors of image are S.D. scales such as the visual sequence, the formal simplicity of structures, the emphasis, the unification of heterogeneous factors and the assimilation. Factors covering the spatial image of natural parks have been found to be the overall evaluation, the individual characteristics, the tidiness, the potentiality, the dignity, the intimacy and the space volume. For all seasons, factors such as the individual characteristics, the dignity, the tidiness, the potentiality, yield high factor scores. As for factors determining the degree of visual preference, variables such as the summit, the skyline, rocks, the water and the degree of natural destruction by artificial structures yield high values for all seasons.

• Ecology and Resilient Infrastructure
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• v.7 no.1
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• pp.1-14
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• 2020

In fluvial and riparian ecosystems, biogeomorphological research has considered the complex, multi-way relationships between biological and hydro-geomorphological components over a wide range of spatial and temporal scales. In this review, we discussed the scope and processes of fluvial biogeomorphology by explaining (1) the multi-lateral interactions between organisms and hydrogeomorphic conditions, (2) the relationships between biodiversity and habitat heterogeneity, and (3) the effects of disturbance on ecosystem patterns. Over time, an organism-landform complex along streams transitions in the sequences of geomorphic, pioneer, biogeomorphic, and ecological stages. Over space, water flow and sediment distributions interact with vegetation to modify channel topography. It is the habitat heterogeneity in streams that enhances riparian biodiversity. However, in the areas downstream of a dam, habitat types and conditions are substantially damaged and biodiversity should be reduced. In South Korea, riparian vegetation flourishes in general and, in particular, invasive species actively colonize in accordance with the changes in the fluvial conditions driven by local disturbances and global climate change. Therefore, the importance of understanding reciprocal relationships between living organisms and hydrogeomorphic conditions will ever increase in this era of rapid climate change and anthropogenic pressure. The fluvial biogeomorphic framework reviewed in this article will contribute to the ecological management and restoration of streams in Korea.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.4
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• pp.73-81
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• 2013

Ordinary least squares (OLS) regression is the primary statistical method in previous studies for vegetation distribution patterns in relation to landform. However, this global regression lacks the ability to uncover some local-specific relationships and spatial autocorrelation in model residuals. This study employed geographically weighted regression (GWR) to examine the spatially varying relationships between NDVI (Normalized Difference Vegetation Index) patterns and changing trends of landform (elevation, slope) and solar intensity (insolation and duration of sunshine) in Mt Geum-gang of North-Korea. Results denoted that GWR was more powerful than OLS in interpreting relationships between NDVI patterns and landform/solar intensity, since GWR was characterized by higher adjusted R2, and reduced spatial autocorrelations in model residuals. Unlike OLS regression, GWR allowed the coefficients of explanatory variables to differ by locality by giving relatively more weight to NDVI patterns which are affected by local landform and solar factors. The strength of the regression relationships in the GWR increased significantly, by showing regression coefficient of higher than 70% (0.744) in the southern ridge of the experimental area. It is anticipated that this research output will serve to increase the scientific and objective vegetation monitoring in relation to landform and solar intensity by overcoming serious constraints suffered from the past non-GWR-based approach.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.611-620
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• 2018

With the revitalization of alley market area becoming a major goal of the urban regeneration project, an understanding on customer characteristics that affect the sales of alley market areas is needed. As spatial heterogeneity appears to exist in alley market areas, the use of GWR (Geographically Weighted Regression) is required as an alternative to OLS (Ordinary Least Squares) regression. This study analyzes effects of customer characteristics on sales of 1007 alley market areas in Seoul. Comparing R squared and AICc, results show that GWR is better than OLS regression. According to OLS regression, the ratio of female, the ratio of 40's and 50's, the number of employees, the opening rate of establishment, the density of building and the size of alley market area have positive effects on sales, while the ratio of 20's and 30's, the distance of bus stop and that of subway station have negative effects. As a result of comparing local regression coefficients of geographically weighted regression analysis, the ratio of female customers has the greatest effect on the northwestern region, followed by the southwestern region, the central region and the northeastern region. The ratio of 20's and 30's and that of 40's and 50's effect on the southeastern and northeastern regions, and then the southwestern region. It is expected that this study will help to identify marketing target for each alley market area.

• The KIPS Transactions:PartD
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• v.18D no.5
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• pp.385-392
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• 2011

Recently, the concern of IT-in-Agriculture convergence technology that combines information technology and agriculture is increasing rapidly. Especially, the crop cultivation related prediction services by spatial data mining (SDM) can play an important role in reducing the damage of natural disaster and enhancing crop productivity. However, the data conversion and integration procedure to acquire the learning dataset of SDM for the prediction service need a lot of effort and time, because of their heterogeneity between distributed data. In addition, calculating spatial neighborhood relationships between spatial and non-spatial data necessitates requires the complicated calculation procedure for large dataset. In this paper, we suggest a SOA-based data integration framework that can effectively integrate distributed heterogeneous data by treating each data source as a service unit and support to find the optimal prediction service by improving productivity of learning dataset for SDM. In our experiment, we confirmed that our framework can be effectively applied to find the optimal prediction service for the frost damage area, by considering the case of peach crop cultivation in Icheon in Korea.