• Journal of Korean Society for Geospatial Information Science
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• v.19 no.4
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• pp.109-118
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• 2011

In this research estimated accuracies that were results in all the area of filtering of the plane equation that was used by whole data set, and regional of filtering that was driven by the plane equation for each vertual Grid. All of this estimates were based by all the area of filtering that deduced the plane equation by multiple linear regression analysis that was used by ground data set. Therefore, accuracy of all the area of filtering that used whole data set has been dropped about 2~3% when average of accuracy of all the area of filtering was based on ground data set while accuracy of Regional of filtering dropped 2~4% when based on virtual Grid. Moreover, as virtual Grid which was set 3~4 cm was difference about 2% of accuracy from standard data. Thus, it leads conclusion of set 3~4 times bigger size in virtual Grid filtering over LiDAR scan gap will be more appropriated. Hence, the result of this research allow us to conclude that there was difference in average accuracy has been noticed when we applied each different approaches, I strongly suggest that it need to research more about real topography for further filtering accuracy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.9
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• pp.4192-4198
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• 2011

Terrestrial LiDAR is a high precision positioning technique to monitor the behavior and change of structures and natural slopes, but it has depended on subjective hand intensive tasks for the classification(surface and vegetation or structure and vegetation) of positioning data. Thus it has a couple of problems including lower reliability of data classification and longer operation hours due to the surface characteristics of various geographical and natural features. In order to solve those problems, the investigator developed a technique of using the NDVI, which is a major index to monitor the changes on the surface(including vegetation), to categorize land covers, combining the results with the terrestrial LiDAR data, and classifying the results according to items. The application results of the developed technique show that the accuracy of convergence was 94% even though there was a problem with partial misclassification of 0.003% along the boundaries between items. The technique took less time for data processing than the old hand intensive task and improved in accuracy, thus increasing its utilization across a range of fields.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.475-478
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• 2007

In this study, we estimated the effect of the traffic noise in urban area using the LiDAR data. The propagation of noise has a strong relationship between distance and shape of surface. Therefore, it is necessary to consider the distribution of buildings for estimating noise assessment in urban area because noise propagations will be affected by buildings. For this, we were developed DEM and DBM using the LiDAR data in order to analyze the propagation of traffic noise precisely in urban area. The level of traffic noise were calculated by investigating the real volume of traffic in study area. The SoundPLAN S/W and RLS90 algorithm was used for traffic noise assessment.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.157-160
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• 2010

Terrestrial LiDAR data contains outliers which do not need in processing purpose. That is inefficient in the aspect of productivity. These noise requires manual process to be removed, which causes inefficiency in aspect of productivity. The purpose of this research is to demonstrate a possibility of automatic outlier removal of LiDAR data using 3D Tensor Voting method. For this, we presented in this article about the procedure to perform the application of Tensor Voting algorithm to the real data from terrestrial LiDAR.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.327-327
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• 2017

최근 지구 온난화에 따른 기후변화로 인한 해수면 상승과 폭풍해일의 강도 및 발생빈도가 증가하고 고파랑 내습, 난개발 등으로 인한 연안 지역의 해안선 변화 및 연안 침식이 크게 문제화되고 있다. 연안 환경의 변화를 분석하는 방법에는 광파측거기를 이용한 해빈 측량, RTK-GPS를 이용한 측정, 항공사진 분석 등이 주된 연구 방법이지만 이러한 연구 방법으로는 미세한 지형 변화의 관찰은 어려움이 많았으며 세밀하고 정량적인 지형분석이 요구 되었다. 본 연구에서는 연구대상지역인 가곡천 하구부를 대상으로 지상 LiDAR를 이용해 장기간 정밀측량을 실시하였다. 자료를 바탕으로 가곡천 하구부의 부피와 면적을 비교분석하였으며, 해안선변화의 정량적 비교분석을 실시하였다.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.121-125
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• 2007

Recently, constructing and complementing the road network database are a main key in all social operation in our life. However it needs high expenses for constructing and complementing the data, and relies on many people for finishing the tasks. This study propose a novel method to extract urban road networks from 3-D LiDAR data automatically. This method integrates height, reflectance, and clustered road point information. Geometric information of general roads is also applied to cluster road points group correctly. The proposed method has been tested on various urban areas which contain complicated road networks. The results conclude that the integration of height, reflectance, and geometric information worked reliably to cluster road points.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.3
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• pp.97-104
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• 2010

The important factors in a flood simulation are hydrologic data (such as the rainfall and intensity), a threedimensional terrain model, and the hydrologic inundation calculation matrix. Should any of these factors lack accuracy, flood prediction data becomes unreliable and imprecise. The three-dimensional terrain model is constructed based on existing digital maps, current map updates, and airborne LiDAR data. This research analyzes and offers ways to improve the model's accuracy by comparing flood weakness areas selected according to the existing data on flood locations and design frequency.

• Journal of the Korean Society of Safety
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• v.31 no.1
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• pp.105-110
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• 2016

Mountainous disasters such as landslides and debris flow are difficult to forecast. Debris flow in particular often flows along the valley until it reaches the road or residential area, causing casualties and huge damages. In this study, the researchers selected Seoraksan National Park area located at Inje County (Inje-gun), Gangwon Province-where many mountainous disasters occur due to localized torrential downpours-for the damage reduction and cause analysis of the area experiencing frequent mountainous disasters every year. Then, the researchers conducted the field study and constructed geospatial information data by GIS method to analyze the characteristics of the disaster-occurring area. Also, to extract more precise geographic parameters, the researchers scanned debris flow triggering area through terrestrial LiDAR and constructed 3D geographical data. LiDAR geographical data was then compared with the existing numerical map to evaluate its precision and made the comparative analysis with the geographic data before and after the disaster occurrence. In the future, it will be utilized as basic data for risk analysis of mountainous disaster or disaster reduction measures through a fine-grid topographical map.

• Proceedings of the KSRS Conference
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• 2008.03a
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• pp.95-100
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• 2008

3차원으로 구성되어 있는 실세계를 보다 효과적이고 신속하게 모니터링하기 위해서는 변화된 지역의 정확한 위치정보 획득과 변화 결과의 빠른 도출을 위한 자동화 방안이 필요하다. 일반적으로 변화탐지를 위해 사용되어 온 항공사진이나 위성영상은 자료 획득에 있어 날씨와 같은 자연환경의 영향을 많이 받으며, 자동으로 변화탐지를 수행하는데 많은 문제점을 안고 있다. 반면에 항공 LiDAR 시스템은 영상시스템과는 달리 날씨 등에 영향을 상대적으로 적게 받으며, 지형지물에 대한 3차원 좌표 정보를 직접 획득하기 때문에 자동으로 처리하기에 매우 효율적이다. 본 연구에서는 항공 LiDAR 데이터만을 이용하여 도시지역의 시공간적 변화를 자동으로 탐지하는 방법을 연구 하였다. 변화탐지의 대상이 도시지역이므로 객체를 기반으로 다양한 변수를 사용하여 변화탐지를 수행하였다. 연구에 사용된 데이터는 서로 다른 시기에 획득된 항공 LiDAR 데이터이며, 두 데이터간의 변화탐지를 위해 먼저 상호정합을 수행하였으며, 개별 객체를 추출하기 위해 필터링과 Grouping 과정을 수행하였다. 마지막으로 Grouping된 객체를 대상으로 모양, 면적, 높이 변화를 비교하여 변화를 탐지하였다. 객체의 외곽선과 내부 영역의 모양을 표현하는 형상계수를 사용하므로 수평방향의 객체에 대한 기하학적인 모양 변화를 탐지할 수 있었으며, 객체의 높이값을 비교함으로써 수직방향으로의 변화도 탐지할 수 있었다. 본 연구에서 수행한 객체 기반의 변화탐지 방법은 91.67%의 전체 정확도를 획득하였다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.3
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• pp.323-332
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• 2012

An airborne LiDAR system performs several observations on flight routes to collect data of targeted regions accompanying with discrepancies between the collected data strips of adjacent routes. This paper aims to present an automatic error correction technique using modified ICP as a way to remove relative errors from the observed data of strip data between flight routes and to make absolute correction to the control data. A control point data from the existing digital topographic map were created and the modified ICP algorithm was applied to perform the absolute automated correction on the relatively adjusted airborne LiDAR data. Through such process we were able to improve the absolute accuracy between strips within the average point distance of airborne LiDAR data and verified the possibility of automation in the geometric corrections using a large scale digital map.