• 대한원격탐사학회지
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• 제34권1호
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• pp.45-74
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• 2018

Landslide is a natural hazard that threats lives and properties in many areas around the world. Landslides are difficult to recognize, particularly in rainforest regions. Thus, an accurate, detailed, and updated inventory map is required for landslide susceptibility, hazard, and risk analyses. The inconsistency in the results obtained using different features selection techniques in the literature has highlighted the importance of evaluating these techniques. Thus, in this study, six techniques of features selection were evaluated. Very-high-resolution LiDAR point clouds and orthophotos were acquired simultaneously in a rainforest area of Cameron Highlands, Malaysia by airborne laser scanning (LiDAR). A fuzzy-based segmentation parameter (FbSP optimizer) was used to optimize the segmentation parameters. Training samples were evaluated using a stratified random sampling method and set to 70% training samples. Two machine-learning algorithms, namely, Support Vector Machine (SVM) and Random Forest (RF), were used to evaluate the performance of each features selection algorithm. The overall accuracies of the SVM and RF models revealed that three of the six algorithms exhibited higher ranks in landslide detection. Results indicated that the classification accuracies of the RF classifier were higher than the SVM classifier using either all features or only the optimal features. The proposed techniques performed well in detecting the landslides in a rainforest area of Malaysia, and these techniques can be easily extended to similar regions.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.141-144
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• 2008

Many studies have been conducted on extracting buildings from ALS(Airborne Laser Scanning) data. After segmentation or classification of building points, additional steps such as generalization is required to get straight boundary lines that better approximate the real ones. In much research, orthogonal constraints are used to improve accuracies and qualities. All the lines of the building boundaries are assumed to be either parallel or perpendicular mutually. However, this assumption is not valid in many cases and more complex shapes of buildings have been increased. A new algorithm is presented that is applicable to various complex buildings. It consists of three steps of boundary tracing, grouping, and regularization. The performance of our approach was evaluated by applying the algorithm to some buildings and the results showed that our proposed method has good potential for extracting building boundaries of various shapes.

• 대한공간정보학회지
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• 제14권4호통권38호
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• pp.37-44
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• 2006

최첨단 측량기술인 항공레이저측량, 항공사진측량, 대축척 수치지도의 도입 및 비약적 발달은 대규모 지역에 대해 일반 사용자가 실생활에 활용 가능한 수준의 대축척 영상정보 및 벡터정보들을 제공하는 주요한 수단이 되고 있다. 그러나 서로 각기 다른 측량기술, 센서들로부터 구축된 자료들을 의미 있는 지리정보로 활용하고 상호보완적인 가치를 창출하기 위해서는 이러한 자료들을 같은 좌표계 상에 표현할 수 있도록 기하보정 하는 과정이 선행되어야 한다.본 연구에서는 항공레이저측량 자료,항공사진, 대축척 수치지도를 이용하여 의미가 있는 지리정보를 생성하기 위한 전처리 과정으로써 위의 측량자료들을 공통의 좌표계 상에 기하보정하는 알고리즘을 제안하였다. 제안된 알고리즘은 선형기하요소를 기하보정의 기본요소로 이용하여 정확하고 효과적으로 기하보정을 수행하였다. 이를 위해 항공레이저측량 자료로부터 선형기하요소를 추출하기 위한 알고리즘을 개발하였으며 추출된 선형요소를 이용하여 항공사진의 단사진과 기하보정하기 위한 방법론을 개발하였고 또한 대축척 수치지도로부터 추출되는 선형요소와의 기하보정을 위한 방법론을 개발하였다. 마지막으로 연구를 위하여 수집된 실제 측량자료에 개발된 방법론들을 적용하고 도출된 결과에 대한 통계평가를 수행함으로써 연구결과의 효용성을 입증하였다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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• pp.530-535
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• 2002

An approach for quickly updating GIS building data using high resolution remotely sensed data is proposed in this paper. High resolution remotely sensed data could be aerial photographs, satellite images and airborne laser scanning data. Data from different types of sensors are integrated in building extraction. Based on the extracted buildings and the outdated GIS database, the change-detection-template can be automatically created. Then, GIS building data can be fast updated by semiautomatically processing the change-detection-temp late. It is demonstrated that this approach is quick, effective and applicable.

• ETRI Journal
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• 제25권2호
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• pp.109-120
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• 2003

Though the airborne laser scanning (ALS) technique is becoming more popular in many applications, horizontal accuracy of points scanned by the ALS is not yet satisfactory when compared with the accuracy achieved for vertical positions. One of the major reasons is the drift that occurs in the inertial measurement unit (IMU) during the scanning. This paper presents an algorithm that adjusts for the error that is introduced mainly by the drift of the IMU that renders systematic differences between strips on the same area. For this, we set up an observation equation for strip-wise adjustments and completed it with tie point and control point coordinates derived from the scanned strips and information from aerial photos. To effectively capture the tie points, we developed a set of procedures that constructs a digital surface model (DSM) with breaklines and then performed feature-based matching on strips resulting in a set of reliable tie points. Solving the observation equations by the least squares method produced a set of affine transformation equations with 6 parameters that we used to transform the strips for adjusting the horizontal error. Experimental results after evaluation of the accuracy showed a root mean squared error (RMSE) of the adjusted strip points of 0.27 m, which is significant considering the RMSE before adjustment was 0.77 m.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.210-212
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• 2003

Active sensors are rapidly conquering a share on the remote sensing market and offer among others new possibilities toward automatically acquiring 3D building data. Better dissemination of information about new technological developments can possibly be achieved by short distance-learning courses. The paper describes the didactic and technical aspects of a course we have designed and conducted on airborne laser scanning and interferometric SAR. The building extraction application is a good example to illustrated the added value of short electronic-learning courses above simply publishing (digital) papers.

• 지구물리
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• 제9권1호
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• pp.7-19
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• 2006

Laser scanning is a new technology for obtaining Digital Surface Models(DSM) of the earth surface.It is a fast method for sampling the earth surface with high density and high point accuracy. This paper is for buildings extraction from LiDAR points data. The core part of building construction is based on a parameters filter for distinguishing between terrain and non-terrain laser points. The 3D geometrical properties of the building facades are obtained based on plane fitting using least-squares adjustment. The reconstruction part of the procedure is based on the adjacency among the roof facades. Primitive extraction and facade intersections are used for building reconstruction. For overcome the difficulty just reconstruct of laser points data used with digital camera images. Also, 3D buildings of city area reconstructed using digital map. Finally, In this paper show 3D building Modeling using digital map and LiDAR data.

• 대한공간정보학회지
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• 제17권3호
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• pp.109-114
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• 2009

섬은 생태 환경보전가치가 뛰어나고 후세를 위한 생태학습장 및 해상 해저개발 등에 있어 국가영역으로서 중요한 영토임에도 불구하고 체계적인 조사 미비로 인하여 관리 자체가 이루어지지 않고 있다. 지적공부의 경우 1910 년대 측량기술의 한계로 인해 접근이 불가능한 섬들은 현재의 지적공부에 등록되어 있지 않아 미등록 섬에 대한 과학적인 조사와 체계적인 관리가 시급한 실정이다. 반면, 항공라이다측량은 최신 측량기법으로 접근이 불가능한 무인도서에 대해 정확한 위치정보와 함께 영상정보의 획득이 가능해 졌기 때문에 미등록 섬의 탐지를 과학적으로 접근이 가능하게 되었다. 이에 본 연구에서는 항공라이다측량 데이터를 이용하여 흑산도 주변 섬의 해안선을 추출하고 지적도 및 정사영상과 비교하여 미등록 섬을 탐지하였다. 또한 위치 및 면적 산출하여 미등록 섬을 추출하는 방안을 제시하였다. 그 결과 흑산도 주변에 대해 총 16개의 미등록 섬을 효과적으로 추출하였다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.241-243
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• 2003

This paper presents an algorithm that automatically extracts buildings among many different features on the earth surface by fusing LIDAR data with panchromatic aerial images. The proposed algorithm consists of three stages such as point level process, polygon level process, parameter space level process. At the first stage, we eliminate gross errors and apply a local maxima filter to detect building candidate points from the raw laser scanning data. After then, a grouping procedure is performed for segmenting raw LIDAR data and the segmented LIDAR data is polygonized by the encasing polygon algorithm developed in the research. At the second stage, we eliminate non-building polygons using several constraints such as area and circularity. At the last stage, all the polygons generated at the second stage are projected onto the aerial stereo images through collinearity condition equations. Finally, we fuse the projected encasing polygons with edges detected by image processing for refining the building segments. The experimental results showed that the RMSEs of building corners in X, Y and Z were ${\pm}$8.1㎝, ${\pm}$24.7㎝, ${\pm}$35.9㎝, respectively.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1374-1376
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• 2003

NASA, NSF and USGS jointly conducted a LIDAR survey over several sites in the Antarctic Dry Valleys and its vicinity, acquiring numerous surface points by NASA's Airborne Topographic Mapper (ATM) conical laser scanning altimetry system. The data set have high blunder ratio, and the conical scanning pattern resulted large variation of the point densities. Hence, to reduce the undesirable effects due to these characteristics and process the huge number of points with reasonable time and resources, we developed a novel approach to generate large-scale and high-resolution DEMs in robust, efficient and nearly automatic manners. Based on this approach we produced DEMs and then verified them with reference data.