• 대한원격탐사학회지
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• 제28권6호
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• pp.661-670
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• 2012

Urban forests provide great ecosystem services to population in metropolitan areas even though they occupy little green space in a huge gray landscape. Unfortunately, urbanization inherently results in threatening the green infrastructure, and the recent urbanization trends drew great attention of scientists and policy makers on how to preserve or restore green infrastructure in metropolitan area. For this reason, mapping the spatial distribution of the green infrastructure is important in urban environments since the resulting map helps us identify hot green spots and set up long term plan on how to preserve or restore green infrastructure in urban environments. As a preliminary step for mapping green infrastructure utilizing multi-source remote sensing data in urban environments, the objective of this study is to map vegetation volume by fusing LiDAR and multispectral data in urban environments. Multispectral imageries are used to identify the two dimensional distribution of green infrastructure, while LiDAR data are utilized to characterize the vertical structure of the identified green structure. Vegetation volume was calculated over the metropolitan Chicago city area, and the vegetation volume was summarized over 16 NLCD classes. The experimental results indicated that vegetation volume varies greatly even in the same land cover class, and traditional land cover map based above ground biomass estimation approach may introduce bias in the estimation results.

• 한국안전학회지
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• 제32권6호
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• pp.137-142
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• 2017

This study deals with the relation between traffic accident and urban decline. The purpose of this study is to develop the regional accident models of elderly drivers. In order to develop the count data models, 2009-2015 traffic accident data from TAAS(traffic accident analysis system) and urban decline data from urban regeneration information system are collected. The main results are as follows. First, the null hypothesis that there is no difference in the accident number between elderly and non-elderly drivers is rejected. Second, 8 accident models which are all statistically significant have been developed. Finally, common variables between elderly and non-elderly are ratio of elderly people, elderly person living alone/1,000 persons and wholesale/retail employments/1,000 persons. This study could be expected to give many implications to making regional accident reduction policy.

• 한국측량학회지
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• 제25권6_1호
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• pp.499-505
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• 2007

A method of improving the correctness and confidence in land use classification as well as urban spatial structure analysis of local governments using GIS and satellite imagery is suggested. This study also compares and analyzes LSAS (Land Suitability Assessment System) results using two approaches-LSAS with priority classification, and LSAS using standard estimation factors without priority classification. The conclusions that can be drawn from this study are as follows. First, a method of maintaining up-to-date local government data by updating the LSAS database using high-resolution satellite imagery is suggested. Second, to formulate a scientific and reasonable land use plan from the viewpoint of territory development and urban management, a method of simultaneously processing the two described approaches is suggested. Finally, LSAS was constructed by using varieties of land information such as the cadastral map, the digital topographic map, varieties of thematic maps, and official land price data, and expects to utilize urban management plan establishment widely and effectively through regular data updating and problem resolution of data accuracy.

• 전기학회논문지
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• 제67권3호
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• pp.460-466
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• 2018

For the efficient energy consumption in an urban railway station, it is necessary to know the patterns of electrical loads for each usage in detail. The electrical loads in an urban railway station have different characteristics from other normal electrical load, such as the peak load timing during a day. The lighting, HVAC, communication, and commercial loads make up large amount of electrical load for equipment in an urban railway station, and each of them has the unique specificity. These loads for each usage were estimated without measuring device by the polynomial regression method with big data such as total amount of electrical load and weather data. In the simulation with real data, the optimal polynomial regression model was third order polynomial regression model with 9 or 10 independent variables.

• 대한원격탐사학회지
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• 제23권1호
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• pp.43-53
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• 2007

In this study, two standard specifications such as GML (Geography Markup Language) from OGC (Open Geo-spatial Consortium, Inc.) and X3D (extensible 3D) from Web3D consortium were dealt with for a web-based 3D urban application without using commercialized tools. In the first step of this study, DEM (Digital Elevation Model) and 3D GIS data sets were converted to GML structure with attribute schema. Then, these GML elements were projected onto a common coordinate system, and they were converted to the X3D format for visualization on web browser. In this work, a 3D urban data model, as a simple framework model, is extended to a framework model having further detailed information, depending upon application levels. Conclusively, this study is to demonstrate for practical uses of GML and X3D in 3D urban application and this approach can be applied to other application domains regarding system integrators and data sharing communities on distributed environments.

• 한국BIM학회 논문집
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• 제9권1호
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• pp.22-31
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• 2019

In this paper, we construct a prototype model for city data prediction by using time series data of floating population, and use machine learning to analyze urban data of complex structure. A correlation prediction model was constructed using three of the 10 data (total flow population, male flow population, and Monday flow population), and the result was compared with the actual data. The results of the accuracy were evaluated. The results of this study show that the predicted model of the floating population predicts the correlation between the predicted floating population and the current state of commerce. It is expected that it will help efficient and objective design in the planning stages of architecture, landscape, and urban areas such as tree environment design and layout of trails. Also, it is expected that the dynamic population prediction using multivariate time series data and collected location data will be able to perform integrated simulation with time series data of various fields.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.41-43
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• 2015

Urban Informatics, the application of data science methodologies to the urban development and planning domain, has been increasingly adopted to improve the management and efficiency of cities. This paper introduces state of the art use cases in major cities including New York, London, Seoul and Amsterdam. It also introduces recent advances in using Big Data by multi-lateral institutions for poverty reduction, and startups utilizing open data initiatives to create new value and insights. Preliminary research performed on using Seoul's open data such as building permit data and health code violations are also introduced to demonstrate opportunities in this relatively new but promising area of research.

• 산경연구논집
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• 제7권3호
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• pp.27-36
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• 2016

Purpose - Considering the importance of housing needs to real estate market, domestic studies on real estate prices from the perspective of demand are basically based on macro-data, but relatively few are associated with micro-data of urban real estate demand. We try to find a reliable relation of elasticity of demand and commercial housing market. Research design, data, and methodology - In this paper, we have derived housing demand theoretic method and have utilized micro-data of residential family housing survey of downtown area in Kunming City in October, 2015 to estimate income elasticity and price elasticity of housing demand respectively and make a comparative analysis. Results - The results indicate that income elasticity and price elasticity of families with owner-occupied housing are both larger than those of families with rental housing. Income elasticity of housing demand of urban residential families in Kunming is far below the foreign average and eastern coastal cities level, however, the corresponding price elasticity is far higher. Conclusions - We suggest that housing affordability of urban families in western China are constrained by the level of economic development, and the current housing price level has exceeded the economic affordability and psychological expectation of ordinary residents. Furthermore, noticing the great rigidity of housing demand, the expansion space of housing market for improvement and for commodity is limited.

• Spatial Information Research
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• 제7권1호
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• pp.103-117
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• 1999

도시지역에서 지하수 산출특성, 흐름 및 오염현상은 인위적인 양수, 지하구조물, 다양한 오염원 지면 포장으로 인한 지하수 함양의 국지적 변동 등의 영향을 받는 매우 복잡한 특성을 가진다. 서울지역 지하수시스템을 분석하기 위해 지리정보시스템 환경에서 수문지질학적 데이터베이스를 구축하였다. 지하수 수위변화의 주요인은 한강수계, 지하철 지형, 강우 등이고 이들을 이용하여 지하수시스템에 대한 영향을 분석하였다. 그리고 그 자료와 분석결과를 ARC/INFO에 데이터 베이스로 저장하고 실세계의 현상과 비구 분석하였다. 구축된 내용은 지하수 오염원의 분포, 대수층의 수리상수, 한강수위 변화에 대한 지하수 영향간 지하철 역사의 대규모 양수로 인한 지하수시스템의 변화 둥이다. 자료의 특성에 맞는 자료 형태로 저장하고 표현할 수 있도록 하였다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.587-590
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• 2007

The demand for more accurate and realistic 3D urban models has been increasing more and more. Many studies have been conducted to extract 3D features from remote sensing data such as satellite images, aerial photos, and airborne laser scanning data. In this paper a technique is presented to extract and reconstruct 3D buildings in urban areas using airborne laser scanning data. Firstly all points in a building were divided into some groups by height difference. From segmented laser scanning data of irregularly distributed points we generalized and regularized building boundaries which better approximate the real boundaries. Then the roof points which are subject to the same groups were classified using pre-defined models by least squares fitting. Finally all parameters of the roof surfaces were determined and 3D building models were constructed. Some buildings with complex shapes were selected to test our presented algorithms. The results showed that proposed approach has good potential for reconstructing complex buildings in detail using only airborne laser scanning data.