• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.2
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• pp.289-297
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• 2009

In the paper, we propose the methodology to extract training dataset automatically for supervised classification of road networks. For the preprocessing, we co-register the airborne photos, LIDAR data and large-scale digital maps and then, create orthophotos and intensity images. By overlaying the large-scale digital maps onto generated images, we can extract the initial training dataset for the supervised classification of road networks. However, the initial training information is distorted because there are errors propagated from registration process and, also, there are generally various objects in the road networks such as asphalt, road marks, vegetation, cars and so on. As such, to generate the training information only for the road surface, we apply the Expectation Maximization technique and finally, extract the training dataset of the road surface. For the accuracy test, we compare the training dataset with manually extracted ones. Through the statistical tests, we can identify that the developed method is valid.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.451-456
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• 2006

Shoreline changes its shape and attribution dynamically by natural, unnatural acts and is the most important information for defining a countries territory. These shorelines can apply to frame work of MGIS, and they are getting important because we can implement the data for creating monitoring systems around coastal areas. This study proposed an algorithm for extracting shorelines automatically using a new developed Lidar data which is applied in ocean and coastal areas. Its result was compared to shorelines which were derived from ground survey. It showed stable shorelines in both natural, and artificial coast areas. It showed the possibility of extracting shorelines with LiDAR data and proved the method was more efficient and economical compared to recent studies and methods.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.646-649
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• 2004

LiDAR(Light Detection and Ranging) system can record intensity data as well as range data. Recently, LiDAR intensity data is widely used for landcover classification, ancillary data of feature extraction, vegetation species identification, and so on. Since the intensity return value is associated with several factors, same features is not consistent for same flight or multiple flights. This paper investigated correlation between intensity and range data. Once the effects of range was determined, the single flight line normalization and the multiple flight line normalization was performed by an empirical function that was derived from relationship between range and return intensity

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.642-645
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• 2007

Mounted in aircraft, LiDAR (Light Detection And Ranging) technology uses pulses of light to collect data about the terrain below. The main objective of this study was to extract reliable the individual tree and analysis techniques to facilitate the used LiDAR data for estimating tree crown diameter by measuring individual trees identifiable on the three dimensional LiDAR surface. In addition, this study can be quantitative analysis of individual tree through the canopy parameter.

• Korean Journal of Remote Sensing
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• v.28 no.1
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• pp.11-19
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• 2012

Air-borne pollen, biogenically created aerosol particle, influences Earth's radiative balance, visibility impairment, and human health. The importance of pollens has resulted in numerous experimental studies aimed at characterizing their dispersion and transport, as well as health effects. There is, however, limited scientific information concerning the optical properties of airborne pollen particles contributing to total ambient aerosols. In this study, for the first time, optical characteristics of pollen such as aerosol backscattering coefficient, aerosol extinction coefficient, and depolarization ratio at 532 nm and their effect to the atmospheric aerosol were studied by lidar remotes sensing technique. Dual-Lidar observations were carried out at the Gwangju Institute of Science & Technology (GIST) located in Gwagnju, Korea ($35.15^{\circ}E$, $126.53^{\circ}N$) for a spring pollen event from 5 to 7 May 2009. The pollen concentration was measured at the rooftop of Gwangju Bohoon hospital where the building is located 1.0 km apart from lidar site by using Burkard trap sampler. During intensive observation period, high pollen concentration was detected as 1360, 2696, and $1952m^{-3}$ in 5, 6, and 7 May, and increased lidar return signal below 1.5km altitude. Pollen optical depth retrieved from depolarization ratio was 0.036, 0.021, and 0.019 in 5, 6, and 7 May, respectively. Pollen particles mainly detected in daytime resulting increased aerosol optical depth and decrease of Angstrom exponent.

• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.449-452
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• 2008

The building heights of big cities which charged with most space are 3-D information as relative vertical distance from ground control points, but they didn't know the heights using contour with maps as lose of skyline or building heights for downtown, practically continuously developed of many technology methods for implementation of 3-D spatial earth. So, For the view as stereos of variety earth form generated 3-D spatial and made terrain perspective map, 3-D simulated of regional and urban space as aviation images. In this papers, it composited geospatial informations and images by DEM generation, and developed and presented for techniques overlay of CAD data and photos captured at our surroundings uses. Particularly, The airborne LiDAR surveying which are very interesting trend have laser scanning sensor and determine the ground heights through detecting angle and range to the grounds, and then designated 3-D spatial composite and simulation from urban areas. Therefore in this papers are suggested ease selections on the users situation by compare as various simulations that its generation of 3-D spatial image by collective for downtown space and urban sub, and the implementation methods for more accurate, more select for the best images.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.3
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• pp.109-114
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• 2009

Although island is great worth in ecology, environmental conservation and important territory as a national land for developing the marine, the bottom of the sea and also ecological studying field for the ages to come, it has not been managed because of lack of a scientific surveying. In the case of a cadastral record, inaccessible islands have not been registered in current cadastral record because of the limit of surveying technology in 1910. Therefore, a scientific investigation and systematic management about unregistered islands are necessary. But, a airborne laser scanning system is possible to acquire an accurate positions with digital images about inaccessible islands. Therefore, scientific detection of unregistered islands became possible. This paper presented the results of the shoreline extraction around the Heuksan island using Lidar data and the detection of unregistered islands comparing the cadastral map to the ortho-image. Also, we presented the extraction technique of unregistered islands by calculating their positions and areas. As a result, we extracted effectively 16 unregistered islands around the Heuksan island.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.205-210
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• 2006

With the development of recent technology such as telematics, LBS, and ubiquitous, the applications of 3D GIS are rapidly increased. As 3D GIS is mainly based on urban models consisting of the realistic digital models of the objects existing in an urban area, demands for urban models and its continuous update is expected to be drastically increased. The purpose of this study is thus to propose more efficient and precise methods to construct urban models with its experimental verification. Applying the proposed methods, the terrain and sophisticated building models are constructed for the area of $270,600m^2$ with 23 buildings in the University of Seoul. For the terrain models, airborne imagery and LIDAR data is used, while the ground imagery is mainly used for the building models. It is found that the generated models reflect the correct geometry of the buildings and terrain surface. The textures of building surfaces, generated automatically using the projective transformation however, are not well-constructed because of being blotted out and shaded by objects such as trees, near buildings, and other obstacles. Consequently, the algorithms on the texture extraction should be improved to construct more realistic 3D models. Furthermore, the inside of buildings should be modeled for various potential applications in the future.

• Korean Journal of Geomatics
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• v.4 no.2
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• pp.39-45
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• 2004

Building reconstruction attempts to generate geometric and radiometric models of existing buildings usually from sensory data, which have been traditionally aerial or satellite images, more recently airborne LIDAR data, or the combination of these data. Extensive studies on building reconstruction from these data have developed some competitive algorithms with reasonable performance and some degree of automation. Nevertheless, the level of details and completeness of the reconstructed building models often cannot reach the high standards that is now or will be required by various applications in future. Hence, the use of terrestrial sensory data that can provide higher resolution and more complete coverage has been intensively emphasized. We developed a fusion framework for building reconstruction from terrestrial sensory data, that is, points from a laser scanner, images from digital camera, and absolute coordinates from a total station. The proposed approach was then applied to reconstructing a building model from real data sets acquired from a large complex existing building. Based on the experimental results, we assured that the proposed approach cam achieve high resolution and accuracy in building reconstruction. The proposed approach can effectively contribute in developing an operational system producing large urban models for 3D GIS with reasonable resources.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.4
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• pp.359-365
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• 2011

This study aims at filtering ALS points into ground and non-ground effectively through labeling and window based algorithm by utilizing 2D adjacency based on scan line. Firstly, points adjacency is constructed through minimal search based on scan line. Connected component labeling algorithm is applied to classify raw ALS points into ground and non-ground by utilizing the adjacency structure. Then, some small objects are removed by morphology filtering, and isolated ground points are restored by IDW estimation. The experimental results shows that the method provides good filtering performance( about 97% accuracy) for diverse sites, and the overall processing takes less time than converting raw data into TIN or raster grid.