• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.2D
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• pp.311-316
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• 2006

Despite geospatial information systems are widely used in many different fields as a powerful tool for spatial analysis and decision-making, their capabilities to handle realistic 3-D urban environment are very limited. The objective of this work is to integrate the recent developments in 3-D modeling and visualization into GIS to enhance its 3-D capabilities. To achieve a photorealistic view, building models are collected from a pair of aerial stereo images. Roof and wall textures are respectively obtained from ortho-rectified aerial image and ground photography. This study is implemented by using ArcGIS as the work platform and ArcObjects and Visual Basic as development tools. Presented in this paper are 3-D geometric modeling and its data structure, texture creation and its association with the geometric model. As the results, photorealistic views of Purdue University campus are created and rendered with ArcScene.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.4
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• pp.53-61
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• 2014

Landsat OLI satellite imagery can be applied to various remote sensing applications, such as generation of land cover map, urban area analysis, extraction of vegetation index and change detection, because it includes various multispectral bands. In addition, land cover map is an important information to monitor and analyze land cover using GIS. In this paper, land cover map is generated by using Landsat OLI and existing land cover map. First, training dataset is obtained using correlation between existing land cover map and unsupervised classification result by K-means, automatically. And then, spectral signatures corresponding to each class are determined based on training data. Finally, abundance map and land cover map are generated by using iterative spectral mixture model. The experiment is accomplished by Landsat OLI of Cheongju area. It shows that result by our method can produce land cover map without manual training dataset, compared to existing land cover map and result by supervised classification result by SVM, quantitatively and visually.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.2
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• pp.34-43
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• 2018

DEM(Digital Elevation Model) being fundamental data in geospatial domain is produced from different data and using various methods. As they are derived their precision varies and altering derivative in application. In this work, we compare two widely used DEMs namely(Advanced Land Observing Satellite World 3D 30m and Shuttle Radar Topography Mission Global 30m) around coastal islands in Gyeongsangnam-do, South Korea. First statistics of each DEM were calculated and later overlapped in Landsat image for visual comparison of areas below and above zero-meter elevation. As a result, it was found that DEMs were highly correlated with each other and had similar statistics. Besides having few high differences in hilly land area, they were able to represent the coastal lines. It has also been noted that they have many negative values and should carefully select study area covering full watershed in coastal regions to avoid negative elevation even after filling the sinks.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.1
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• pp.19-27
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• 2014

Kompsat-3 is an optical high-resolution earth observation satellite launched in May 2012. In addition to its 0.7m spatial resolution, Kompsat-3 is capable of in-track stereo acquisition enabling quality Digital Elevation Model(DEM) generation. Typical DEM generation procedure requires accurate control points well-distributed over the entire image region. But we often face difficult situations especially when the area of interests is oversea or inaccessible area. One solution to this is to use existing geospatial data even though they only cover a part of the image. This paper aimed to assess accuracy of DEM from Kompsat-3 with different scenarios including no control point, Rational Polynomial Coefficients(RPC) relative adjustment, and RPC adjustment with control points. Experiments were carried out for Kompsat-3 stereo data in USA. We used Digital Orthophoto Quadrangle(DOQ) and Shuttle Radar Topography Mission(SRTM) as control points sources. The generated DEMs are compared to a LiDAR DEM for accuracy assessment. The test results showed that the relative RPC adjustment significantly improved DEM accuracy without any control point. And comparable DEM could be derived from single control point from DOQ and SRTM, showing 7 meters of mean elevation error.

• Journal of Korean Society for Geospatial Information Science
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• v.25 no.1
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• pp.47-54
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• 2017

Recently, there are many studies related aerial mapping project and 3 dimensional shape and model reconstruction using UAV(unmanned aerial vehicle) system and images. In this study, we create 3D reconstruction point data using image matching technology of the UAV overlap images, detect shape change of structure and perform accuracy assessment of area($m^2$) and volume($m^3$) value. First, we build the test structure model data and capturing its images of shape change Before and After. Second, for post-processing the Before dataset is convert the form of raster format image to ensure the compare with all 3D point clouds of the After dataset. The result shows high accuracy in the shape change of more than 30 centimeters, but less is still it becomes difficult to apply because of image matching technology has its own limits. But proposed methodology seems very useful to detect illegal any structures and the quantitative analysis of the structure's a certain amount of damage and management.

• Journal of Korean Society for Geospatial Information Science
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• v.25 no.1
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• pp.71-78
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• 2017

Many studies have been implemented to manage solar plant being supplied widely in recent years. This study analyzed heat emission of solar cell using unmanned aerial vehicle(UAV)-based thermal infrared sensor, and major conclusions are as belows. Firstly, orthomosaic image and digital surface model(DSM) data were acquired using UAV-based RGB sensor, and solar light module layer necessary to analyze the heat emission of solar cell was constructed by these data. Also as a result of horizontal error into validation points using virtual reference service(VRS) survey for evaluating the location accuracy of solar light module layer, higher location accuracy could be acquired like standard error of $dx={\pm}2.4cm$ and $dy={\pm}3.2cm$. And this study installed rubber patch to test the heat emission of solar cell and could analyzed efficiently the location of rubber patch being emitted heat using UAV-based thermal infrared sensor. Also standard error showd as ${\pm}3.5%$ in analysis between calculated cell ratio by rubber patch and analyzed cell ratio by UAV-based thermal infrared sensor. Therefore, it could be efficiently analyzed to heat emission of solar cell using UAV-based thermal infrared sensor. Also efficient maintenance of solar plant could be possible through extracting the code of solar light module being emitted of heat automatically.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.1
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• pp.21-35
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• 2009

KOMPSAT-2 is the seventh high-resolution image satellite in the world that provides both 1m-grade panchromatic images of the GSD and 4m-grade multispectral images of the GSD. It's anticipated to be used across many different areas including mapping, territory monitoring and environmental watch. However, due to the complexity and security concern involved with the use of the MSC, the use of KOMPSAT-2 images are limited in terms of geometric images, such as satellite orbits and detailed mapping information. Therefore, this study aims to produce DEM and orthoimage by using the stereo images of KOMPSAT-2, and to explore the applicability of geo-spatial information with KOMPSAT -2. Orientation interpretations were essential for the production of DEM and orthoimage using KOMPSAT-2 images. In the study, they are performed by utilizing both RPC and GCP. In this study, the orientation interpretations are followed by the generation of DEM and orthoimage, and the analysis of their accuracy based on a 1:5,000 digital map. The accuracy analysis of DEM is performed and the results indicate that their altitudes are, in general, higher than those obtained from the digital map. The altitude discrepancies on plains, hills and mountains are calculated as 1.8m, 7.2m, and 11.9m, respectively. In this study, the mean differences between horizontal position between the orthoimage data and the digital map data are found to be ${\pm}3.081m$, which is in the range of ${\pm}3.5m$, within the permitted limit of a 1:5,000 digital map. KOMPSAT-2 images are used to produce DEM and orthoimage in this research. The results suggest that DEM can be adequately used to produce digital maps under 1:5,000 scale.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.3
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• pp.23-29
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• 2015

Due to the characteristics of landslide disasters including debris flow, the rapid speed to downward and difficulty to respond or evacuate from them, it is imperative to identify their potential hazards and prepare the reduction plans. However, the current landslide hazards generated by a variety of methods has been raised its accuracy because of the complexity of input data and their analyses, and the simplification of the landslide model. The main objective of this study is, therefore, to evaluate the preliminary landslide hazard based on the identification of geomorphological features. Especially, two methodologies based on the statistics of the directional data, Vector dispersion and Planarity analyses, are used to find some relationships between geomorphological characteristics and the landslide hazard. Results show that both methods well discriminate geomorphological features between stable and unstable domains in the landslide areas. Geomorphological features are closely related to the landslide hazard and it is imperative to maximize their characteristics by adapting multiple models rather than individual model only. In conclusions, the mechanism of landslide is not determined solely by a simple cause but the complex natural phenomenon caused by the interactions of the numerous factors and it is of primary importance to require additional researches for the outbreaking mechanism that are based on various methodologies.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.3
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• pp.77-84
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• 2015

The key objective of this research is to review the effectiveness of spatial regression to identify the influencing factors of spatial distribution patterns of floating population. To this end, global and local spatial autocorrelation test were performed using seoul floating population survey(2014) data. The result of Moran's I and Getis-Ord $Gi^*$ as used in the analysis derived spatial heterogeneity and spatial similarities of floating population patterns in a statistically significant range. Accordingly, Geographically Weighted Regression was applied to identify the relationship between land use attributes and population floating. Urbanization area, green tract of land of micro land cover data were aggregated in to $400m{\times}400m$ grid boundary of Seoul. Additionally public transportation variables such as intersection density transit accessibility, road density and pedestrian passage density were adopted as transit environmental factors. As a result, the GWR model derived more improved results than Ordinary Least Square(OLS) regression model. Furthermore, the spatial variation of applied local effect of independent variables for the floating population distributions.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.4
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• pp.3-11
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• 2014

Recently, rapid urbanization has necessitated continuous updates in digital map to provide the latest and accurate information for users. However, conventional aerial photogrammetry has some restrictions on periodic updates of small areas due to high cost, and as-built drawing also brings some problems with maintaining quality. Alternatively, this paper proposes a scheme for efficient and accurate update of digital map using point cloud data acquired by Terrestrial Laser Scanner (TLS). Initially, from the whole point cloud data, the building sides are extracted and projected onto a 2D image to trace out the 2D building footprints. In order to register the footprint extractions on the digital map, 2D Affine model is used. For Affine parameter estimation, the centroids of each footprint groups are randomly chosen and matched by means of a modified RANSAC algorithm. Based on proposed algorithm, the experimental results showed that it is possible to renew digital map using building footprint extracted from TLS data.