• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1058-1060
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• 2003

A ground control point (GCP) is a point on the surface of Earth where image coord inates and map coordinates can be identified. The GCP is useful for the geometric correction of systematic and unsystematic errors usually contained in a remotely sensed data. Especially in case of synthetic aperture radar (SAR) data, it has serious geometric distortions caused by inherent side looking geometry. In addition, SAR images are usually severely corrupted by speckle noises so that it is difficult to identify ground control points. We developed a ground point extraction algorithm that has an improved capability. An application of radargrammetry to Daejon area in Korea was studied to acquire the geometric information. For the ground control point extraction algorithm, an ERS SAR data with precise Delft orbit information and rough digital elevation model (DEM) were used. We analyze the accuracy of the results from our algorithm by using digital map and GPS survey data.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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• pp.442-447
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• 2002

When a SAR system operates in a full-polarimetic mode, the amount of the information one can extract is so complex that the effective presentation of the information is important. However, the information acquired from the polarimetric SAR data is often difficult to interpret by itself, because it is consisted of both the amplitude information and the phase information. Polarimetric parameters are the good way of representing the polarimetric SAR information in a quantitative manner. Also they can characterize the scattering behavior of the ground scatterer. In this research, extraction of polarimetric parameters, evaluation and interpretation of the scattering behavior of the ground with respect to polarimetric SAR signal are carried out. Using the NASA/JPL AIRSAR data, we estimated the polarimetric parameters and compared them in terms of the ground features. In general, extracted parameters well represent the characteristics of the different features on the ground.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 추계종합학술대회 논문집
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• pp.979-982
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• 1999

A new accurate as well as efficient multi-layer interconnect capacitance extraction method is presented. Since Multi-layer interconnects is too complicated to directly extract capacitances, it is simplified with virtual ground concept. To make the structure tractable, the shielding effects should be separately determined. Since the electric field shielding effects, and the solid-ground-based capacitance matrices can be readily determined from the layout geometry, the accurate as well as efficient quasi-3D capacitances concerned with an objective line can be readily determined. In order to demonstrate its efficiency and accuracy, the parameters and circuit responses were benchmarked with 3D-field-solver-based results.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2006년도 춘계학술발표회 논문집
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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.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.147-150
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• 2008

This study refers to develop a semi-automatic extraction of agricultural land use and vegetation information using high resolution satellite images. Data of IKONOS satellite image (May 25 of 2001) and QuickBird satellite image (May 1 of 2006) which resembles with the spatial resolution and spectral characteristics of KOMPSAT3. The precise agricultural land use classification was tried using ISODATA unsupervised classification technique and the result was compared with on-screen digitizing land use accompanying with field investigation. For the extraction of vegetation information, three crops of paddy, com and red pepper were selected and the spectral characteristics were collected during each growing period using ground spectroradiometer. The vegetation indices viz. RVI, NDVI, ARVI, and SAVI for the crops were evaluated. The evaluation process is under development using the ERDAS IMAGINE Spatial Modeler Tool.

• 대한공간정보학회지
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• 제19권3호
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• pp.41-47
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• 2011

원시 LiDAR 데이터는 벡터 구조이기 때문에 직접 활용 시 처리과정이 복잡해지지만, LiDAR 데이터를 필터링을 통해 정규 가상 격자 형태로 변환하면 데이터 용량이 감소되고 처리 속도가 빠르기 때문에 저가의 장비에서도 처리가 가능하다. 특히 Quadtree와 같은 영상 압축 처리 기법을 적용할 경우, 평활화를 통하여 비지면 요소인 자동차, 수목등이 제거되어 모델링에 유리하다는 장점이 있다. 따라서 본 연구에서는 대용량의 LiDAR 데이터로부터 Quadtree와 영역확장법을 활용하여 지면점을 자동 추출할 수 있는 알고리즘을 제시하였으며, 오차분류기법을 활용하여 정확도를 분석하였다. 그 결과, 지면점 분류 정확도는 98%이상으로 나타나, 지면점 추출에 유리함을 알 수 있었다. 또한 Quadtree와 영역확장법을 활용시 자동차, 수목등의 비지면 요소들을 효과적으로 제거할 수 있었다.

• 한국컴퓨터정보학회논문지
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• 제16권3호
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• pp.1-7
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• 2011

무장 전투기와 같은 공격용 항공기는 정밀한 공대공 또는 공대지 공격을 위해 표적의 정확한 위치 정보를 필요로 한다. 본 논문에서는 레이더나 FLIR과 같은 표적추적센서 없이 공대공 유도탄의 seeker head를 조종사의 머리가 가리키는 방향으로 유도하는 장비인 HMD만을 사용하여 공대지 표적의 위치정보를 획득하는 방법을 제시한다. 시뮬레이션 실험을 행한 결과 HMD를 수동 센서로 사용할 경우 다른 표적추적센서와의 연동 없이 HMD 만으로도 높은 정밀도의 표적 위치 정보를 획득할 수 있음을 발견하였다.

• 대한원격탐사학회지
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• 제19권5호
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• pp.393-402
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• 2003

In times of the civil uses of commercialized high-resolution satellite imagery, applications of remote sensing have been widely extended to the new fields or the problem solving beyond traditional application domains. Transportation application of this sensor data, related to the automatic or semiautomatic road extraction, is regarded as one of the important issues in uses of remote sensing imagery. Related to these trends, this study focuses on automatic road extraction using Gradient Direction Profile Algorithm (GDPA) scheme, with IKONOS panchromatic imagery having 1 meter resolution. For this, the GDPA scheme and its main modules were reviewed with processing steps and implemented as a prototype software. Using the extracted bi-level image and ground truth coming from actual GIS layer, overall accuracy evaluation and ranking error-assessment were performed. As the processed results, road information can be automatically extracted; by the way, it is pointed out that some user-defined variables should be carefully determined in using high-resolution satellite imagery in the dense or low contrast areas. While, the GDPA method needs additional processing, because direct results using this method do not produce high overall accuracy or ranking value. The main advantage of the GDPA scheme on road features extraction can be noted as its performance and further applicability. This experiment study can be extended into practical application fields related to remote sensing.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.637-641
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• 2007

Airborne LIDAR (Light Detection and Ranging) technology has reached a degree of the required accuracy in mapping professions, and advanced LIDAR systems are becoming increasingly common in the various fields of application. LiDAR data constitute an excellent source of information for reconstructing the Earth's surface due to capability of rapid and dense 3D spatial data acquisition with high accuracy. However, organizing the LIDAR data and extracting information from the data are difficult tasks because LIDAR data are composed of randomly distributed point clouds and do not provide sufficient semantic information. The main reason for this difficulty in processing LIDAR data is that the data provide only irregularly spaced point coordinates without topological and relational information among the points. This study introduces an efficient and robust method for automatic extraction of building footprints using airborne LIDAR data. The proposed method separates ground and non-ground data based on the histogram analysis and then rearranges the building boundary points using convex hull algorithm to extract building footprints. The method was implemented to LIDAR data of the heavily built-up area. Experimental results showed the feasibility and efficiency of the proposed method for automatic producing building layers of the large scale digital maps and 3D building reconstruction.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.79-82
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• 2005

Recently the necessity of road data is still being increased in industrial society, so there are many repairing and new constructions of roads at many areas. According to the development of government, city and region, the update and acquisition of road data for GIS (Geographical Information System) is very necessary. In this study, the fusion method with range data(3D Ground Coordinate System Data) and Intensity data in stand alone LiDAR data is used for road extraction and then digital image processing method is applicable. Up to date Intensity data of LiDAR is being studied. This study shows the possibility method for road extraction using Intensity data. Intensity and Range data are acquired at the same time. Therefore LiDAR does not have problems of multi-sensor data fusion method. Also the advantage of intensity data is already geocoded, same scale of real world and can make ortho-photo. Lastly, analysis of quantitative and quality is showed with extracted road image which compare with I: 1,000 digital map.