• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.3
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• pp.401-408
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• 2009

A study for 3D-reconstruction and providing the geospatial information is in progress to many fields recently. For efficient providing the geospatial information, the present information has to be updated and be revised and then the latest geospatial information needs to be acquired economically. Especially, LiDAR system utilized in many study has a advantage to collect the 3D spacial data easily and densely that is possible to supply to the geospatial information. The 3D data of LiDAR is very suitable as a data for presenting 3D space, but in case of using the data without converting, the high performance processor is needed for presenting 2D forms from point data composed by 3D data. In comparison, basically the raster data structure of 2D form is more efficient than vector structure in cheap devices because of a simple structure and process speed. The purpose of this study, in case of supplying LiDAR data as 3D data, present the method that reconstructs to 2D raster data and convert to compression data applied by th tree construction in detail.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2010.09a
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• pp.134-141
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• 2010

임분 단위의 재적 및 생체량은 LiDAR 자료의 높이 분포변수들로부터 추정될 수 있다. LiDAR 자료의 높이 분포변수들은 재적을 측정하는 임분고(stand height)와 임분평균 지하고(mean crown base height), 그리고 수관형태에 따른 평균수관장(mean crown depth) 등의 변수와 직 간접적인 연관성이 있다. 그러므로, 본 연구에서는 잣나무림의 샘플지역에서 반사된 LiDAR 자료의 높이분포변수를 이용하여 임분단위의 수간재적을 추정한 다음, 앞 세부연구에서 수행한 방법을 이용하여 임분의 생체량을 추정하였다. 변수는 임분 내에서 반사되는 LiDAR 자료의 평균높이, 최대 최소높이, 높이값들의 표준편차, 변이계수, 첨도, 왜도, 식생반사비율, 10분위 높이자료와 강도데이터의 기술통계량 등을 사용하였다. 그리고, 최종적인 임분수간재적은 다중회귀분석을 통하여 수행되었다. 다중회귀분석을 통하여 각 변수들은 임분수간재적과 가장 관련있는 2~3개의 변수들로 추려졌으며, 추정된 회귀식의 결정계수는 0.66으로 분석되었다. 또한 유보표본을 이용하여 검증한 결과의 결정계수는 0.59로 분석되어 LiDAR 자료의 높이분포변수들은 임분의 재적을 비교적 잘 설명할 수 있음이 밝혀졌다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.2
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• pp.73-81
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• 2015

The objective of this study is in investigating the research for more accurately quantify the information on mountain forest by using the data on high density LiDAR. For the quantitative analysis of mountain forest resources, we investigated the method to acquire the data on high density LiDAR and extract mountain forest resources. Consequently, the height and girth of a tree each mountain forest resources could be extracted by using the data on high density LiDAR. When using the data on low density LiDAR of 2.5points/m² in average used to produce digital map, it was difficult to extract the exact height and girth of mountain forest resources. If using the data on high density LiDAR of 7points/m² by considering topography, the property of mountain forest resources, data capacity and process velocity, etc, it was found that multitudinous entities could be extracted. It was found that mountain topography and mixed topography were generally denser than plane topography and multitudinous mountain forest resources could be extracted. Furthermore, it was also found that the entity at the border could not be extracted, when each partition was individually processed and the area should be subdivided and extracted by considering the process time and property of target area rather than processing wide area at once. We expect to be studied more profoundly the absorption quantity of greenhouse gas later by using information on mountain forest resources in the future.

• Korean Journal of Remote Sensing
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• v.31 no.2
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• pp.127-136
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• 2015

This study aims to quantify the stand-level above ground biomass in intact tropical rain forest of Brunei using airborne LiDAR data. Twenty four sub-plots with the size of 0.09ha ($30m{\times}30m$) were located in the 25ha study area along the altitudinal gradients. Field investigated data (Diameter at Breast Height (DBH) and individual tree position data) in sub-plots were used. Digital Surface Model (DSM), Digital Terrain Model (DTM) and Canopy Height Model (CHM) were constructed using airborne LiDAR data. CHM was divided into 24 sub-plots and 12 LiDAR height metrics were built. Multiple regression equation between the variables extracted from the LiDAR data and biomass calculated by using a allometric equation was derived. Stand-level biomass estimated from LiDAR data were distributed from 155.81 Mg/ha to 597.21 Mg/ha with the mean value of 366.48 Mg/ha. R-square value of the verification analysis was 0.84.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2D
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• pp.269-276
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• 2008

Recently, constructing the database of road network is a main key in various social operation as like the transportation, management, security, disaster assesment, and the city plan in our life. However it need high expenses for constructing the data, and relies on many people for finishing the tasks. This study proposed the classification method for discriminating between the road and building points using the entropy theory, then detects the classes as a expecting road from the classified point group using the standard reflectance intensity of road and the characteristics restricted by raw. Hence the main object of this study is to develop a method which can detect the road in urban area using only the LiDAR data.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.1 s.31
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• pp.19-25
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• 2005

Nowadays, it is possible to construct the DEMs of urban area effectively and economically by LiDAR system. But the data from LiDAR system has form of DSM which is included various objects as trees and buildings. So the preprocess is necessary to extract the DEMs from LiDAR DSMs for particular purpose as effects analysis of man-made objects for flood prediction. As this study is for extracting DEM from LiDAR DSM of urban area, we detected the edges of various objects using edge detecting algorithm of image process. And, we tried mean value filtering, median value filtering and minimum value filtering or detected edges instead of interpolation method which is used in the previous study and could be modified the source data. it could minimize the modification of source data, and the extracting process of DEMs from DSMs could be simplified and automated.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2005.11a
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• pp.81-104
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• 2005

Accurate 3D models in urban areas are essential for a variety of applications, such as virtual visualization, CIS, and mobile communications. LiDAR(Light Detection and Ranging) is a relatively new technology for directly obtaining 3D points. Because Manual 3D data reconstruction from LiDAR data is very costly and time consuming, many researchs is focused on the automatic extraction of the useful data. In this paper, we classified ground and non-ground points data from LiDAR data by using filtering, and we reconstructed the DTM(Digital Terrain Model) using ground points data, buildings using nonground points data. After the reconstruction, we assessed the accuracy of the DTM and buildings. As a result of, DTM from LiDAR data were 0.16m and 0.59m in high raised apartments areas and low house areas respectively, and buildings were matched with the accuracy of a l/5,000 digital map.

• Spatial Information Research
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• v.18 no.3
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• pp.1-11
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• 2010

Recently, the construction of three dimensional spatial information of Dam reservoir area is very important part in Dam management work such as sediment survey, but it is difficult to acquire detailed terrain data because totalstation and single beam echo sounder are applied to terrain survey. This study presented method to construct detailed terrain data of Dam reservoir area using LiDAR and multi beam echo sounder. First, LiDAR survey was carried out in land zone and calibration process was applied by ground control point. And also the DEM of land zone was constructed by using algorithm, which eliminated building and vegetation class. As the result of validation of LiDAR DEM using GPS terrain survey, it was possible to construct three dimensional terrain data that was satisfied with the tolerance error of LiDAR, which was the standard error of LiDAR DEM showed as 0.108m. Also multi beam echo sounder was applied to the survey of water zone and it could construct spatial information that was satisfied with bathymetry surveying tolerance error of International Hydrographic Organization by validation with terrain survey data. And LiDAR and multi beam echo sounder data were integrated and it was possible to construct three dimensional spatial imagery information that can be applied to Dam management work such as the estimation of sediment amounts or the monitoring of terrain change by linking with high resolution orthophoto.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.3
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• pp.174-187
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• 2011

The flowed soil is able to be estimated from topographic data of before and after the debris flow. However, it is often difficult to obtain airborne LiDAR data before the debris flow area. Thus, this study tries to develop a topographic restoration method that can provide spatial distribution of flowed soil and reconstruct the topography before the debris flow using airborne LiDAR data. The topographic restoration method can express a numerical formula induced from a Gaussian mixture model after extracting the cross sections of linear or non-linear in debris flowed area. The topographic restoration method was verified by two ways using airborne LiDAR data of before and after the debris flow. First, each cross section extracted from the debris flow sites to restore the topography was compared with airborne LiDAR data of before the debris flow. Also, the topographic data produced after the topographic restoration method applied to the debris flow sites was verified by airborne LiDAR DEM. Verifying the results of the topographic restoration method, overall fitting accuracy showed high accuracy close to 0.5m.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.3
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• pp.257-263
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• 2011

There are many previous researches such as verification of accuracy, application, and change detection of discrete return LiDAR data, but no researches for full waveform LiDAR data. In this study, we selected the forest area and urban area as case study areas and compared the height accuracy of full waveform LiDAR data with field surveying data. As a result, we got an RMSE of 3.lcm in urban area, 4.7cm in forest area, and it is verified that height accuracy of full waveform LiDAR is high. We think that it is very usefull in aerial photogrammetry.