• Title/Summary/Keyword: Space Images

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Comparative Study of GDPA and Hough Transformation for Linear Feature Extraction using Space-borne Imagery (위성 영상정보를 이용한 선형 지형지물 추출에서의 GDPA와 Hough 변환 처리결과 비교연구)

  • Lee Kiwon;Ryu Hee-Young;Kwon Byung-Doo
    • Korean Journal of Remote Sensing
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    • v.20 no.4
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    • pp.261-274
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    • 2004
  • The feature extraction using remotely sensed imagery has been recognized one of the important tasks in remote sensing applications. As the high-resolution imagery are widely used to the engineering purposes, need of more accurate feature information also is increasing. Especially, in case of the automatic extraction of linear feature such as road using mid or low-resolution imagery, several techniques was developed and applied in the mean time. But quantitatively comparative analysis of techniques and case studies for high-resolution imagery is rare. In this study, we implemented a computer program to perform and compare GDPA (Gradient Direction Profile Analysis) algorithm and Hough transformation. Also the results of applying two techniques to some images were compared with road centerline layers and boundary layers of digital map and presented. For quantitative comparison, the ranking method using commission error and omission error was used. As results, Hough transform had high accuracy over 20% on the average. As for execution speed, GDPA shows main advantage over Hough transform. But the accuracy was not remarkable difference between GDPA and Hough transform, when the noise removal was app]ied to the result of GDPA. In conclusion, it is expected that GDPA have more advantage than Hough transform in the application side.

3D Building Modeling Using Aerial LiDAR Data (항공 LiDAR 데이터를 이용한 3차원 건물모델링)

  • Cho, Hong-Beom;Cho, Woo-Sug;Park, Jun-Ku;Song, Nak-Hyun
    • Korean Journal of Remote Sensing
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    • v.24 no.2
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    • pp.141-152
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    • 2008
  • The 3D building modeling is one of crucial components in constructing 3D geospatial information. The existing methods for 3D building modeling depend mainly on manual photogrammetric processes, which indeed take great amount of time and efforts. In recent years, many researches on 3D building modeling using aerial LiDAR data have been actively performed to aim at overcoming the limitations of existing 3D building modeling methods. Either techniques with interpolated grid data or data fusion with digital map and images have been investigated in most of existing researches on 3D building modeling with aerial LiDAR data. The paper proposed a method of 3D building modeling with LiDAR data only. Firstly, octree-based segmentation is applied recursively to LiDAR data classified as buildings in 3D space until there are no more LiDAR points to be segmented. Once octree-based segmentation is completed, each segmented patch is thereafter merged together based on its geometric spatial characteristics. Secondly, building model components are created with merged patches. Finally, a 3D building model is generated and composed with building model components. The experimental results with real LiDAR data showed that the proposed method was capable of modeling various types of 3D buildings.

Fire Severity Mapping Using a Single Post-Fire Landsat 7 ETM+ Imagery (단일 시기의 Landsat 7 ETM+ 영상을 이용한 산불피해지도 작성)

  • 원강영;임정호
    • Korean Journal of Remote Sensing
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    • v.17 no.1
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    • pp.85-97
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    • 2001
  • The KT(Kauth-Thomas) and IHS(Intensity-Hue-Saturation) transformation techniques were introduced and compared to investigate fire-scarred areas with single post-fire Landsat 7 ETM+ image. This study consists of two parts. First, using only geometrically corrected imagery, it was examined whether or not the different level of fire-damaged areas could be detected by simple slicing method within the image enhanced by the IHS transform. As a result, since the spectral distribution of each class on each IHS component was overlaid, the simple slicing method did not seem appropriate for the delineation of the areas of the different level of fire severity. Second, the image rectified by both radiometrically and topographically was enhanced by the KT transformation and the IHS transformation, respectively. Then, the images were classified by the maximum likelihood method. The cross-validation was performed for the compensation of relatively small set of ground truth data. The results showed that KT transformation produced better accuracy than IHS transformation. In addition, the KT feature spaces and the spectral distribution of IHS components were analyzed on the graph. This study has shown that, as for the detection of the different level of fire severity, the KT transformation reflects the ground physical conditions better than the IHS transformation.

Potential Effects of Land-Use Change on the Local climete (토지이용 변화가 국지기후에 미치는 영향)

  • 이현영
    • Korean Journal of Remote Sensing
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    • v.11 no.3
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    • pp.83-100
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    • 1995
  • The land-use has changed rapidly during the last two decades in accordance with urbanization in the Seoul Metropolitan Region. As a result of these changes, the local climate has undergone changes as well. This study intends to define the land-use changes, and then to show how they have brought in significant changes in the local climates. Land-use changes in the study area so repidly that up-to date maps and documents are not available at present. Therefore, Landsat data for land-use classification and NOAA AVHRR thermal data for the temperature fields were analyzed. Additionary, to visualize the effect of the land-use on the local climate, computer-enhanced brightness temperatures, Green Belt and city boundaries were overlaid on land-use patterns obtained from satellite images using GIS techniques. The results of analysis demonstrate that Green Space in the Seoul Metropolitan Region decreased from 94% to 62% while urban land-use increased ten times, from 4% to 39% for the period of 1972-1992. The resulting disappearance of biomass caused by land-use changes may have implications for the local-and micro-climate. The results show that the local climate of the study area became drier and warmer. This study also suggests a need for further studies of man's effects on local climate to minimize adverse influences and hazardous pollution and efficacious ways for urban planning.

ROUTE/DASH-SRD based Point Cloud Content Region Division Transfer and Density Scalability Supporting Method (포인트 클라우드 콘텐츠의 밀도 스케일러빌리티를 지원하는 ROUTE/DASH-SRD 기반 영역 분할 전송 방법)

  • Kim, Doohwan;Park, Seonghwan;Kim, Kyuheon
    • Journal of Broadcast Engineering
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    • v.24 no.5
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    • pp.849-858
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    • 2019
  • Recent developments in computer graphics technology and image processing technology have increased interest in point cloud technology for inputting real space and object information as three-dimensional data. In particular, point cloud technology can accurately provide spatial information, and has attracted a great deal of interest in the field of autonomous vehicles and AR (Augmented Reality)/VR (Virtual Reality). However, in order to provide users with 3D point cloud contents that require more data than conventional 2D images, various technology developments are required. In order to solve these problems, an international standardization organization, MPEG(Moving Picture Experts Group), is in the process of discussing efficient compression and transmission schemes. In this paper, we provide a region division transfer method of 3D point cloud content through extension of existing MPEG-DASH (Dynamic Adaptive Streaming over HTTP)-SRD (Spatial Relationship Description) technology, quality parameters are further defined in the signaling message so that the quality parameters can be selectively determined according to the user's request. We also design a verification platform for ROUTE (Real Time Object Delivery Over Unidirectional Transport)/DASH based heterogeneous network environment and use the results to validate the proposed technology.

Estimation of Leaf Area Index Based on Machine Learning/PROSAIL Using Optical Satellite Imagery (광학위성영상을 이용한 기계학습/PROSAIL 모델 기반 엽면적지수 추정)

  • Lee, Jaese;Kang, Yoojin;Son, Bokyung;Im, Jungho;Jang, Keunchang
    • Korean Journal of Remote Sensing
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    • v.37 no.6_1
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    • pp.1719-1729
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    • 2021
  • Leaf area index (LAI) provides valuable information necessary for sustainable and effective management of forests. Although global high resolution LAI data are provided by European Space Agency using Sentinel-2 satellite images, they have not considered forest characteristics in model development and have not been evaluated for various forest ecosystems in South Korea. In this study, we proposed a LAI estimation model combining machine learning and the PROSAIL radiative transfer model using Sentinel-2 satellite data over a local forest area in South Korea. LAI-2200C was used to measure in situ LAI data. The proposed LAI estimation model was compared to the existing Sentinel-2 LAI product. The results showed that the proposed model outperformed the existing Sentinel-2 LAI product, yielding a difference of bias ~ 0.97 and a difference of root-mean-square-error ~ 0.81 on average, respectively, which improved the underestimation of the existing product. The proposed LAI estimation model provided promising results, implying its use for effective LAI estimation over forests in South Korea.

Dose Distribution Comparison between Arc Radiation Therapy and Tomotherapy (아크치료기법과 토모테라피치료의 선량분포 비교)

  • Kim, Ji-Yoon;Lee, Seung-Chul;Cheon, Geum-Seong;Kim, Young-Jae
    • Journal of the Korean Society of Radiology
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    • v.15 no.5
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    • pp.723-730
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    • 2021
  • This study tries to compare dose distribution between arc radiation therapy and Tomotherapy, which are main radiation therapy modalities. The subjects of this study are lung cancer patients. For planning target volume (PTV), a dose of 60.0 Gy was set as a basis. The PTVmean of Arc was 61.04 Gy, and that of Tomotherapy was 58.50 Gy. The total lung capacities of Arc and Tomotherapy were 3.0 Gy and 4.24 Gy, respectively. The mean heart doses of Arc and Tomotherapy were 0.13 and 0.34, respectively; the mean trachea dose of Arc and Tomotherapy were 1.35 and 2.58, respectively; the mean esophagus dose of Arc and Tomotherapy were 0.41 and 0.86, respectively; the mean spinal cord dose of Arc and Tomotherapy were 3.65 and 4.68, respectively. With regard to the appropriateness of therapeutic effect in DHV, both modalities seemed appropriate. Tomotherapy protected normal tissues better than Arc radiation therapy. In Tomotherapy, patients need to have treatment long in a limited space. If such a point is overcome, Tomotherapy is better. Otherwise, Arc radiation therapy can be applied. This study was conducted with treatment planning images. Therefore, the results of this study are different from actual treatment results. If more research is conducted to overcome the limitation, the effects of radiation therapy are expected to increase further.

GEO-KOMPSAT-2A AMI Best Detector Select Map Evaluation and Update (천리안위성2A호 기상탑재체 Best Detector Select 맵 평가 및 업데이트)

  • Jin, Kyoungwook;Lee, Sang-Cherl;Lee, Jung-Hyun
    • Korean Journal of Remote Sensing
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    • v.37 no.2
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    • pp.359-365
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    • 2021
  • GEO-KOMPSAT-2A (GK2A) AMI (Advanced Meteorological Imager) Best Detector Select (BDS) map is pre-determined and uploaded before the satellite launch. After the launch, there is some possibility of a detector performance change driven by an abrupt temperature variation and thus the status of BDS map needs to be evaluated and updated if necessary. To investigate performance of entire elements of the detectors, AMI BDS analyses were conducted based on a technical note provided from the AMI vendor (L3HARRIS). The concept of the BDS analysis is to investigate the stability of signals from detectors while they are staring at targets (deep space and internal calibration target). For this purpose, Long Time Series (LTS) and Output Voltage vs. Bias Voltage (V-V) methods are used. The LTS for 30 secs and the V-V for two secs are spanned respectively for looking at the targets to compute noise components of detectors. To get the necessary data sets, these activities were conducted during the In-Orbit Test (IOT) period since a normal operation of AMI is stopped and special mission plans are commanded. With collected data sets during the GK2A IOT, AMI BDS map was intensively examined. It was found that about 1% of entire detector elements, which were evaluated at the ground test, showed characteristic changes and those degraded elements are replaced by alternative best ones. The stripping effects on AMI raw images due to the BDS problem were clearly removed when the new BDS map was applied.

Improvement of Ortho Image Quality by Unmanned Aerial Vehicle (UAV에 의한 정사영상의 품질 개선 방안)

  • Um, Dae-Yong;Park, Joon-Kyu
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.11
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    • pp.568-573
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    • 2018
  • UAV(Unmanned Aerial Vehicle) is widely used in space information construction, agriculture, fisheries, weather observation, communication, and entertainment fields because they are cheaper and easier to operate than manned aircraft. In particular, UAV have attracted much attention due to the speed and cost of data acquisition in the field of spatial information construction. However, ortho image images produced using UAVs are distorted in buildings and forests. It is necessary to solve these problems in order to utilize the geospatial information field. In this study, fixed wing, rotary wing, vertical take off and landing type UAV were used to detect distortions of ortho image of UAV under various conditions, and various object areas such as construction site, urban area, and forest area were captured and analysed. Through the research, it was found that the redundancy of the unmanned aerial vehicle image is the biggest factor of the distortion phenomenon, and the higher the flight altitude, the less the distortion phenomenon. We also proposed a method to reduce distortion of orthoimage by lowering the resolution of original image using DTM (Digital Terrain Model) to improve distortion. Future high-quality unmanned aerial vehicles without distortions will contribute greatly to the application of UAV in the field of precision surveying.

Performance Comparison of Matching Cost Functions for High-Quality Sea-Ice Surface Model Generation (고품질 해빙표면모델 생성을 위한 정합비용함수의 성능 비교 분석)

  • Kim, Jae-In;Kim, Hyun-Cheol
    • Korean Journal of Remote Sensing
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    • v.34 no.6_2
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    • pp.1251-1260
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    • 2018
  • High-quality sea-ice surface models generated from aerial images can be used effectively as field data for developing satellite-based remote sensing methods but also as analysis data for understanding geometric variations of Arctic sea-ice. However, the lack of texture information on sea-ice surfaces can reduce the accuracy of image matching. In this paper, we analyze the performance of matching cost functions for homogeneous sea-ice surfaces as a part of high-quality sea-ice surface model generation. The matching cost functions include sum of squared differences (SSD), normalized cross-correlation (NCC), and zero-mean normalized cross-correlation (ZNCC) in image domain and phase correlation (PC), orientation correlation (OC), and gradient correlation (GC) in frequency domain. In order to analyze the matching performance for texture changes clearly and objectively, a new evaluation methodology based on the principle of object-space matching technique was introduced. Experimental results showed that it is possible to secure reliability and accuracy of image matching only when optimal search windows are variably applied to each matching point in textureless regions such as sea-ice surfaces. Among the matching cost functions, NCC and ZNCC showed the best performance for texture changes.