• Journal of Korean Society for Geospatial Information Science
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• v.13 no.4 s.34
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• pp.27-32
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• 2005

DEM is needed for urban modeling, forecasting of floods and the analysis of slope and aspect. It has been generated using digital maps, aerial photos or satellite imageries. Recently, however, many studies on DEM generation from LiDAR data has been conducted because of its efficiency and accuracy. Filtering is said to be the process of making DEM by eliminating non-ground points from LiDAR data. In most researches, some input parameters such as the size of filter are required. The purpose of this investigation is to automatically obtain DEM by eliminating objects of various sizes without the knowledge of the objects' sizes. The experimental results show that most of objects on steep terrain are eliminated by the proposed method.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.4
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• pp.61-66
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• 2009

This Paper describes a new program called DEM Generator need to process DEM from LiDAR data or digital map data. It is difficult to generate raster DEM from LiDAR mass point data sets and digital maps too large to fit into memory. The DEM Generator was designed to process DEM and shaded relief image of GeoTiff format in order of streaming meshes; I/O minimize tag, delaunay triangle, natural neighborhood or TIN, temporary files and grid. It is expected that we can be improved the precision of DEM and solved the time consuming problem of DEM generating of a wider area.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.5
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• pp.545-553
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• 2009

Digital Elevation Models (DEM) is widely used in establishing the topographic profile in nation spatial information. Aerial Light Detection And Ranging (LiDAR) system is one of the well-known means to produce DEM. The system has fast data acquisition procedures and less weather-dependent restrictions compared to photogrammetric approaches. In this regards, LiDAR has been widely utilized and accepted in the process of nation spatial information generation due to its sufficient positional accuracy. However, the investigation of the accuracy of aerial LiDAR data over the area of forestation with various kinds of vegetations has been barely implemented in Korea. Hence, this research focuses on the investigation of the accuracy of aerial LiDAR data over the area of forestation and the evaluation of the acquired accuracy according to the characteristics of the vegetations. The study areas include land with shrubs and its adjacent forest area with mixed tree species. The spots for the investigation have been selected to be well-distributed over the whole study areas and their coordinates are surveyed by Global Positioning Systems (GPS). Then, the surveyed information and aerial LiDAR data have been compared with each other and the result accuracy has been evaluated. Conclusively, it is recommended that LiDAR data collection to be conducted after defoliation period, especially over the areas with broadleaf trees due to the possibility of significant outliers.

• Journal of Korean Society of Forest Science
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• v.106 no.3
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• pp.320-329
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• 2017

This study aims to evaluate whether the accuracy of LiDAR DEM is affected by the changes of the five input levels ('1','3','5','7' and '9') of median parameter ($F_{md}$), mean parameter ($F_{mn}$) of the Filtering Algorithm (FA) in the GroundFilter module and median parameter ($I_{md}$), mean parameter ($I_{mn}$) of the Interpolation Algorithm (IA) in the GridSurfaceCreate module of the FUSION in order to present the combination of parameter levels producing the most accurate LiDAR DEM. The accuracy is measured by the residuals calculated by difference between the field elevation values and their corresponding DEM elevation values. A multi-way ANOVA is used to statistically examine whether there are effects of parameter level changes on the means of the residuals. The Tukey HSD is conducted as a post-hoc test. The results of the multi- way ANOVA test show that the changes in the levels of $F_{md}$, $F_{mn}$, $I_{mn}$ have significant effects on the DEM accuracy with the significant interaction effect between $F_{md}$ and $F_{mn}$. Therefore, the level of $F_{md}$, $F_{mn}$, and the interaction between two variables are considered to be factors affecting the accuracy of LiDAR DEM as well as the level of $I_{mn}$. As the results of the Tukey HSD test on the combination levels of $F_{md}{\ast}F_{mn}$, the mean of residuals of the '$9{\ast}3$' combination provides the highest accuracy while the '$1{\ast}1$' combination provides the lowest one. Regarding $I_{mn}$ levels, the mean of residuals of the both '3' and '1' provides the highest accuracy. This study can contribute to improve the accuracy of the forest attributes as well as the topographic information extracted from the LiDAR data.

• 한국공간정보시스템학회:학술대회논문집
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• 2005.05a
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• pp.387-392
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• 2005

최근에는 LiDAR 시스템의 등장으로 기존의 항공사진측량에 비하여 효율적이고, 경제적으로 도시지역의 수치표고자료를 효과적으로 구축할 수 있게 되었으나, 도시지역에서는 다양한 형태의 객체들이 모두 포함된 DSM(Digital Surface Model) 형식의 자료를 취득하게 된다. 따라서, 홍수범람예측에 있어서의 인공지물의 영향 해석 등을 위하여 건물이 제거된 지형에 관한 상세한 정보를 제공하기 위해서는 DSM으로부터 DEM(Digital Elevation Model)을 추출하기 위한 전처리 과정이 필요하다. 본 연구는 LiOAR 시스템으로부터 취득된 도시지역에 대한 DSM으로부터 건물 등이 제거된 DEM을 추출하기 위한 연구로서 영상처리기법의 경계검출 알고리즘을 적용하여 건물 등의 지물들에 대한 경계를 추출하였으며, 선행연구에서 건물로 추출된 지역에 대하여 보간법을 적용함으로써 발생하는 원시 DSM 자료의 변형에 따른 대안으로써, 추출된 경계에 대여 평균값 필터링, 중간 값 필터링, 최소 값 필터링을 각각 적용함으로써 원시 DSM 자료의 변형을 최소화하여 건물 등의 지물들을 제거하였으며, LiDAR DSM으로부터 DEM을 제작하는 과정을 간략화, 자동화하였다.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.443-446
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• 2007

The major purpose of the present study is to gauge the general applicability of cadastral surveying and LiDAR surveying. LiDAR survey is the method which obtains Geospatial information of the terrain. We will get a most topographic models at Digital Elevation Model(DEM) using LiDAR survey data. Also, we will consider both the surface parcel partition and volume parcel as a part of Geospatial relationship model. This study will focus on enhancing the efficiency and analysis of continual cadastral map and LiDAR DEM. I would like to close by proposing that LiDAR surveying will contribute in cadastral surveying.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.5
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• pp.389-397
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• 2006

The purpose of the present paper is to offer an analysis of LiDAR data processing and three dimensional terrain for Geographic Information System (CIS) applications. Generally, LiDAR survey is the method which obtains quantitative and qualitative information of the terrain using airborne laser scanning (ALS). We will get a most topographic data at a Triangular Irregular Network (TIN), Digital Surface Model (DSM) and Digital Elevation Model (DEM) using LiDAR data. We examined many factors such as visibility, hillshade, aspect and slope using DEM and DSM. The analyzing results obtained from each item are thought to be regarded as leading factors in the terrain analysis. It is to be hoped that LiDAR survey will contribute a new approach to the terrain analysis.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.4
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• pp.3-9
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• 2007

Recently, the efforts of systematic understanding and utilization of geographic phenomenon for human life as a important factor among activity of mankind are increasing. It is necessary to express topography connected with space. Especially, the technology of geographic analysis using DEM can supply the information rapidly and accurately about elevation and terrain slope of the subject area under the necessity of high 3D quality geographic information. In this study, creating more precise DEM derived from LiDAR data, quantitative analysis on the subject area about elevation and terrain slope is done under comparison with Digital Topographic map Scale 1:1000. LiDAR data is more detailed than Digital Topographic map to express the elevation of the subject area ($39.89{\sim}77.48m$), and terrain slope by analysis using DEM derived from LiDAR data come out minutely about 90%. It can be concluded that the LiDAR data is very applicable and accurate for 3D topographic terrain slope analysis.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.4
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• pp.429-438
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• 2011

LiDAR technology is a combination of laser ranging, satellite positioning technology and digital image technology for study and determination with high accuracy of the true earth surface features in 3 D. Laser scanning data is typically a points cloud on the ground, including coordinates, altitude and intensity of laser from the object on the ground to the sensor (Wehr & Lohr, 1999). Data from laser scanning can produce products such as digital elevation model (DEM), digital surface model (DSM) and the intensity data. In Vietnam, the LiDAR technology has been applied since 2005. However, the application of LiDAR in Vietnam is mostly for topological mapping and DEM establishment using point cloud 3D coordinate. In this study, another application of LiDAR data are present. The study use the intensity image combine with some other data sets (elevation data, Panchromatic image, RGB image) in Bacgiang City to perform land cover classification using neural network method. The results show that it is possible to obtain land cover classes from LiDAR data. However, the highest accurate classification can be obtained using LiDAR data with other data set and the neural network classification is more appropriate approach to conventional method such as maximum likelyhood classification.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.469-473
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• 2006

In general, a classification process between ground data and non-ground data, which include building objects, is required prior to producing a DEM for a certain surface reconstruction from LiDAR data in which the DEM can be produced from the ground data, and certain objects like buildings can be reconstructed using non-ground data. Thus, an exact classification between ground and non-ground data from LiDAR data is the most important factor in the ground reconstruction process using LiDAR data. In particular, building objects can be largely used as digital maps, orthophotos, and urban planning regarding the object in the ground and become an essential to providing three dimensional information for certain urban areas. In this study, an entropy theory, which has been used as a standard of disorder or uncertainty for data used in the information theory, is used to apply a more objective and generalized method in the recognition and segmentation of buildings from raw LiDAR data. In particular, a method that directly uses the raw LiDAR data, which is a type of point shape vector data, without any changes, to a type of normal lattices was proposed, and the existing algorithm that segments LiDAR data into ground and non-ground data as a binarization manner was improved. In addition, this study proposes a generalized building extraction method that excludes precedent information for buildings and topographies and subsidiary materials, which have different data sources.