• Title/Summary/Keyword: Geospatial Data Model

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Flood Damage Assessment According to the Scenarios Coupled with GIS Data (GIS 자료와 연계한 시나리오별 홍수피해액 분석)

  • Lee, Geun-Sang;Park, Jin-Hyeg
    • Journal of Korean Society for Geospatial Information Science
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    • v.19 no.4
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    • pp.71-80
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    • 2011
  • A simple and an improved methods for the assessment of flood damage were used in previous studies, and the Multi-Dimensional Flood Damage Assessment (MD-FDA) has been applied since 2004 in Korea. This study evaluated flood damage of dam downstream using considering MD-FDA method based on GIS data. Firstly, flood water level with FLDWAV (Flood Wave routing) model was input into cross section layer based on enforcement drainage algorithm, water depth grid data were created through spatial calculation with DEM data. The value of asset of building and agricultural land according to local government was evaluated using building layer from digital map and agricultural land map from landcover map. Also, itemized flood damage was calculated by unit price to building shape, evaluated value of housewares to urban type, unit cost to crop, tangible and inventory asset of company connected with building, agricultural land, flooding depth layer. Flood damage in rainfall frequency of 200 year showed 1.19, 1.30 and 1.96 times to flood damage in rainfall frequency of 100 year, 50 year and 10 year respectively by flood damage analysis.

Extraction of Spatial Information of Tree Using LIDAR Data in Urban Area (라이다 자료를 이용한 도시지역의 수목공간정보 추출)

  • Cho, Du-Young;Kim, Eui-Myoung
    • Journal of Korean Society for Geospatial Information Science
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    • v.18 no.4
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    • pp.11-20
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    • 2010
  • In situation that carbon dioxide emissions are being increased as urbanization, urban green space is being promoted as an alternative to find solution for these problems. In urban areas, trees have the ability to reduce carbon dioxide as well as to be aesthetic effect. In this study, we proposed the methodology which uses only LIDAR data in order to extract these trees information effectively. To improve the operational efficiency according to the extraction of trees, the proposed methodology was carried out using multiple data processing such as point, polygon and raster. Because the existing NDSM(Normalized Digital Surface Model) contains both the building and tree information, it has the problems of high complexity of data processing for extracting trees. Therefore, in order to improve these problems, this study used modified NDSM which was removed estimate regions of building. To evaluate the performance of the proposed methodology, three different zones which coexist buildings and trees within urban areas were selected and the accuracy of extracted trees was compared with the image taken by digital camera.

A Study on Optimal Site Selection for the Artificial Recharge System Installation Using TOPSIS Algorithm

  • Lee, Jae One;Seo, Minho
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.34 no.2
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    • pp.161-169
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    • 2016
  • This paper is intended to propose a novel approach to select an optimal site for a small-scaled artificial recharge system installation using TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) with geospatial data. TOPSIS is a MCDM (Multi-Criteria Decision Making) method to choose the preferred one of derived alternatives by calculating the relative closeness to an ideal solution. For applying TOPSIS, in the first, the topographic shape representing optimal recovery efficiency is defined based on a hydraulic model experiment, and then an appropriate surface slope is determined for the security of a self-purification capability with DEM (Digital Elevation Model). In the second phase, the candidate areas are extracted from an alluvial map through a morphology operation, because local alluvium with a lengthy and narrow shape could be satisfied with a primary condition for the optimal site. Thirdly, a shape file over all candidate areas was generated and criteria and their values were assigned according to hydrogeologic attributes. Finally, TOPSIS algorithm was applied to a shape file to place the order preference of candidate sites.

Scanner Calibration Method for Higher Accuracy at Acquisition of Digital Imagery Data in GSIS (지형공간정보체계에서 수치영상자료 취득의 정확도 향상을 위한 주사기의 검정 방법)

  • Choi, Chul-Sun
    • Journal of Korean Society for Geospatial Information Science
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    • v.1 no.2 s.2
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    • pp.153-158
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    • 1993
  • It is important to establish the transformational relation between scanned image coordinates and digital image coordinates because the coordinate system of digital image is transformed from scanned image coordinate system through scanning work. And, some researches are required in scanning works to correct the deformation that is due to the motion of scanner. In this study, some procedures are applied to determine the optimal calibration model equation which can calibrate the scanner. As a result the optimal calibration model equation for the object scanner is determined The procedure of this study can applied to the calibration of other types of scanner, because the procedures are done with the analysis of geometrical properties rather than the analysis of physical properties.

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A Study on the Photo-realistic 3D City Modeling Using the Omnidirectional Image and Digital Maps (전 방향 이미지와 디지털 맵을 활용한 3차원 실사 도시모델 생성 기법 연구)

  • Kim, Hyungki;Kang, Yuna;Han, Soonhung
    • Korean Journal of Computational Design and Engineering
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    • v.19 no.3
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    • pp.253-262
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    • 2014
  • 3D city model, which consisted of the 3D building models and their geospatial position and orientation, is becoming a valuable resource in virtual reality, navigation systems, civil engineering, etc. The purpose of this research is to propose the new framework to generate the 3D city model that satisfies visual and physical requirements in ground oriented simulation system. At the same time, the framework should meet the demand of the automatic creation and cost-effectiveness, which facilitates the usability of the proposed approach. To do that, I suggest the framework that leverages the mobile mapping system which automatically gathers high resolution images and supplement sensor information like position and direction of the image. And to resolve the problem from the sensor noise and a large number of the occlusions, the fusion of digital map data will be used. This paper describes the overall framework with major process and the recommended or demanded techniques for each processing step.

GIS-supported Evaluation System for Road Traffic-related Air Pollution (도로교통관련 대기오염평가 GIS지원시스템)

  • Pior, Myoung-Young
    • Journal of Korean Society for Geospatial Information Science
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    • v.8 no.1 s.15
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    • pp.13-25
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    • 2000
  • Road traffic-related environment problems has become now serious problem common in the urban life throughout the world. In this study, a GIS-supported evaluation system has been developed for dealing with the road traffic-related environment problems, especially focusing on air Pollution in the urban areas. The developed system consists lof three essential parts: GIS; traffic-related air pollution simulation model; and the database for potential strategies. In establishing the simulation model, a GIS-supported environment can provide a useful tool for handling a wide range of data characterizing study areas and for preparing more accurate estimation on real locations. Such roles of the GIS-supported system can be helpful to more efficient analysis and more reasonable decision-makings. As a preliminary stage in developing the system, the metropolitan area of Cairo in Egypt was applying into being as a Pilot study to test the Potentiality of the prototype system.

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Automatic Building Reconstruction with Satellite Images and Digital Maps

  • Lee, Dong-Cheon;Yom, Jae-Hong;Shin, Sung-Woong;Oh, Jae-Hong;Park, Ki-Surk
    • ETRI Journal
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    • v.33 no.4
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    • pp.537-546
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    • 2011
  • This paper introduces an automated method for building height recovery through the integration of high-resolution satellite images and digital vector maps. A cross-correlation matching method along the vertical line locus on the Ikonos images was deployed to recover building heights. The rational function models composed of rational polynomial coefficients were utilized to create a stereopair of the epipolar resampled Ikonos images. Building footprints from the digital maps were used for locating the vertical guideline along the building edges. The digital terrain model (DTM) was generated from the contour layer in the digital maps. The terrain height derived from the DTM at each foot of the buildings was used as the starting location for image matching. At a preset incremental value of height along the vertical guidelines derived from vertical line loci, an evaluation process that is based on the cross-correlation matching of the images was carried out to test if the top of the building has reached where maximum correlation occurs. The accuracy of the reconstructed buildings was evaluated by the comparison with manually digitized 3D building data derived from aerial photographs.

Orthophoto and DEM Generation in Small Slope Areas Using Low Specification UAV (저사양 무인항공기를 이용한 소규모 경사지역의 정사영상 및 수치표고모델 제작)

  • Park, Jin Hwan;Lee, Won Hee
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.34 no.3
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    • pp.283-290
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    • 2016
  • Even though existing methods for orthophoto production in traditional photogrammetry are effective in large areas, they are inefficient when dealing with change detection of geometric features and image production for short time periods in small areas. In recent years, the UAV (Unmanned Aerial Vehicle), equipped with various sensors, is rapidly developing and has been implemented in various ways throughout the geospatial information field. The data and imagery of specific areas can be quickly acquired by UAVs at low costs and with frequent updates. Furthermore, the redundancy of geospatial information data can be minimized in the UAV-based orthophoto generation. In this paper, the orthophoto and DEM (Digital Elevation Model) are generated using a standard low-end UAV in small sloped areas which have a rather low accuracy compared to flat areas. The RMSE of the check points is σH = ±0.12 m on a horizontal plane and σV = ±0.09 m on a vertical plane. As a result, the maximum and mean RMSE are in accordance with the working rule agreement for the airborne laser scanning surveying of the NGII (National Geographic Information Institute) on a 1/500 scale digital map. Through this study, we verify the possibilities of the orthophoto generation in small slope areas using general-purpose low specification UAV rather than a high cost surveying UAV.

Estimation of Monthly Precipitation in North Korea Using PRISM and Digital Elevation Model (PRISM과 상세 지형정보에 근거한 북한지역 강수량 분포 추정)

  • Kim, Dae-Jun;Yun, Jin-I.
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.13 no.1
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    • pp.35-40
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    • 2011
  • While high-definition precipitation maps with a 270 m spatial resolution are available for South Korea, there is little information on geospatial availability of precipitation water for the famine - plagued North Korea. The restricted data access and sparse observations prohibit application of the widely used PRISM (Parameter-elevation Regressions on Independent Slopes Model) to North Korea for fine-resolution mapping of precipitation. A hybrid method which complements the PRISM grid with a sub-grid scale elevation function is suggested to estimate precipitation for remote areas with little data such as North Korea. The fine scale elevation - precipitation regressions for four sloping aspects were derived from 546 observation points in South Korea. A 'virtual' elevation surface at a 270 m grid spacing was generated by inverse distance weighed averaging of the station elevations of 78 KMA (Korea Meteorological Administration) synoptic stations. A 'real' elevation surface made up from both 78 synoptic and 468 automated weather stations (AWS) was also generated and subtracted from the virtual surface to get elevation difference at each point. The same procedure was done for monthly precipitation to get the precipitation difference at each point. A regression analysis was applied to derive the aspect - specific coefficient of precipitation change with a unit increase in elevation. The elevation difference between 'virtual' and 'real' surface was calculated for each 270m grid points across North Korea and the regression coefficients were applied to obtain the precipitation corrections for the PRISM grid. The correction terms are now added to the PRISM generated low resolution (~2.4 km) precipitation map to produce the 270 m high resolution map compatible with those available for South Korea. According to the final product, the spatial average precipitation for entire territory of North Korea is 1,196 mm for a climatological normal year (1971-2000) with standard deviation of 298 mm.

Application and development of a machine learning based model for identification of apartment building types - Analysis of apartment site characteristics based on main building shape - (머신러닝 기반 아파트 주동형상 자동 판별 모형 개발 및 적용 - 주동형상에 따른 아파트 개발 특성분석을 중심으로 -)

  • Sanguk HAN;Jungseok SEO;Sri Utami Purwaningati;Sri Utami Purwaningati;Jeongseob KIM
    • Journal of the Korean Association of Geographic Information Studies
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    • v.26 no.2
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    • pp.55-67
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    • 2023
  • This study aims to develop a model that can automatically identify the rooftop shape of apartment buildings using GIS and machine learning algorithms, and apply it to analyze the relationship between rooftop shape and characteristics of apartment complexes. A database of rooftop data for each building in an apartment complex was constructed using geospatial data, and individual buildings within each complex were classified into flat type, tower type, and mixed types using the random forest algorithm. In addition, the relationship between the proportion of rooftop shapes, development density, height, and other characteristics of apartment complexes was analyzed to propose the potential application of geospatial information in the real estate field. This study is expected to serve as a basic research on AI-based building type classification and to be utilized in various spatial and real estate analyses.