• 제목/요약/키워드: Radiometric Control Points

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Adjustment of Exterior Orientation of the Digital Aerial Images using LiDAR Points

  • Yoon, Jong-Suk
    • 한국측량학회지
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    • 제26권5호
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    • pp.485-491
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    • 2008
  • LiDAR systems are usually incorporated a laser scanner and GPS/INS modules with a digital aerial camera. LiDAR point clouds and digital aerial images acquired by the systems provide complementary spatial information on the ground. In addition, some of laser scanners provide intensity, radiometric information on the surface of the earth. Since the intensity is unnecessary of registration and provides the radiometric information at a certain wavelength on the location of LiDAR point, it can be a valuable ancillary information but it does not deliver sufficient radiometric information compared with digital images. This study utilize the LiDAR points as ground control points (GCPs) to adjust exterior orientations(EOs) of the stereo images. It is difficult to find exact point of LiDAR corresponding to conjugate points in stereo images, but this study used intensity of LiDAR as an ancillary data to find the GCPs. The LiDAR points were successfully used to adjust EOs of stereo aerial images, therefore, successfully provided the prerequisite for the precise registration of the two data sets from the LiDAR systems.

Robust Radiometric and Geometric Correction Methods for Drone-Based Hyperspectral Imaging in Agricultural Applications

  • Hyoung-Sub Shin;Seung-Hwan Go;Jong-Hwa Park
    • 대한원격탐사학회지
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    • 제40권3호
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    • pp.257-268
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    • 2024
  • Drone-mounted hyperspectral sensors (DHSs) have revolutionized remote sensing in agriculture by offering a cost-effective and flexible platform for high-resolution spectral data acquisition. Their ability to capture data at low altitudes minimizes atmospheric interference, enhancing their utility in agricultural monitoring and management. This study focused on addressing the challenges of radiometric and geometric distortions in preprocessing drone-acquired hyperspectral data. Radiometric correction, using the empirical line method (ELM) and spectral reference panels, effectively removed sensor noise and variations in solar irradiance, resulting in accurate surface reflectance values. Notably, the ELM correction improved reflectance for measured reference panels by 5-55%, resulting in a more uniform spectral profile across wavelengths, further validated by high correlations (0.97-0.99), despite minor deviations observed at specific wavelengths for some reflectors. Geometric correction, utilizing a rubber sheet transformation with ground control points, successfully rectified distortions caused by sensor orientation and flight path variations, ensuring accurate spatial representation within the image. The effectiveness of geometric correction was assessed using root mean square error(RMSE) analysis, revealing minimal errors in both east-west(0.00 to 0.081 m) and north-south directions(0.00 to 0.076 m).The overall position RMSE of 0.031 meters across 100 points demonstrates high geometric accuracy, exceeding industry standards. Additionally, image mosaicking was performed to create a comprehensive representation of the study area. These results demonstrate the effectiveness of the applied preprocessing techniques and highlight the potential of DHSs for precise crop health monitoring and management in smart agriculture. However, further research is needed to address challenges related to data dimensionality, sensor calibration, and reference data availability, as well as exploring alternative correction methods and evaluating their performance in diverse environmental conditions to enhance the robustness and applicability of hyperspectral data processing in agriculture.

AVHRR MOSAIC IMAGE DATA SET FOR ASIAN REGION

  • Yokoyama, Ryuzo;Lei, Liping;Purevdorj, Ts.;Tanba, Sumio
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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    • pp.285-289
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    • 1999
  • A processing system to produce cloud-free composite image data set was developed. In the process, a fine geometric correction based on orbit parameters and ground control points and radiometric correction based on 6S code are applied. Presently, by using AVHRR image data received at Tokyo, Okinawa, Ulaanbaatar and Bangkok, data set of 10 days composite images covering almost whole Asian region.

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매핑을 위한 고해상 위성영상의 궤도요소 모델링 (Orbital Parameters Modeling of High Resolution Satellite Imagery for Mapping Applications)

  • 유환희;성재열;김동규;진경혁
    • 한국측량학회지
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    • 제18권4호
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    • pp.405-414
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    • 2000
  • IKONOS, SPOT-5, OrbView-3, 4와 같은 위성들은 기존의 위성들보다 향상된 방사영역과 기하학적으로 안정된 고해상력 위성영상을 갖게 될 것이며, 탑재된 GPS와 IMU, Star Trackers 등에 의해 고정밀의 궤도위치와 자세자료가 제공될 예정이다. 이러한 정보들은 지상기준점수를 줄일 수 있는 가능성을 보여주고 있으며, 더나가 지상기준점을 이용하지 않고 직접 위성영상을 이용하여 위치결정을 할 수 있다. 본 연구에서는 SPOT-3호와 KOMPSAT-1호 위성영상의 궤도요소계산을 위한 수학적 모델을 개발하였으며, 개발된 모델은 고해상위성영상의 활용이 현실화될 경우 이들 영상을 처리하기 위해 쉽게 확장될 것이다.

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Application of Change Detection Techniques Using KOMPSAT-1 EOC Images

  • Kim, Youn-Soo;Lee, Kwang-Jae
    • 대한원격탐사학회지
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    • 제19권3호
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    • pp.263-269
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    • 2003
  • This research examined the capabilities of KOMPSAT-1 EOC images for the application of urban environment, including the urban changes of the study areas. This research is constructed in three stages: Firstly, for the application of change detection techniques, which utilizes multi-temporal remotely sensed data, the data normalization process is carried out. Secondly, the change detection method is applied for the systematic monitoring of land-use changes. Lastly, using the results of the previous stages, the land-use map is updated. Consequently, the patterns of land-use changes are monitored by the proposed scheme. In this research, using the multi-temporal KOMPSAT-1 EOC images and land-use maps, monitoring of urban growth was carried out with the application of land-use changes, and the potential and scope of the application of the EOC images were also examined.

Estimation of the Flood Area Using Multi-temporal RADARSAT SAR Imagery

  • Sohn, Hong-Gyoo;Song, Yeong-Sun;Yoo, Hwan-Hee;Jung, Won-Jo
    • Korean Journal of Geomatics
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    • 제2권1호
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    • pp.37-46
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    • 2002
  • Accurate classification of water area is an preliminary step to accurately analyze the flooded area and damages caused by flood. This step is especially useful for monitoring the region where annually repeating flood is a problem. The accurate estimation of flooded area can ultimately be utilized as a primary source of information for the policy decision. Although SAR (Synthetic Aperture Radar) imagery with its own energy source is sensitive to the water area, its shadow effect similar to the reflectance signature of the water area should be carefully checked before accurate classification. Especially when we want to identify small flood area with mountainous environment, the step for removing shadow effect turns out to be essential in order to accurately classify the water area from the SAR imagery. In this paper, the flood area was classified and monitored using multi-temporal RADARSAT SAR images of Ok-Chun and Bo-Eun located in Chung-Book Province taken in 12th (during the flood) and 19th (after the flood) of August, 1998. We applied several steps of geometric and radiometric calculations to the SAR imagery. First we reduced the speckle noise of two SAR images and then calculated the radar backscattering coefficient $(\sigma^0)$. After that we performed the ortho-rectification via satellite orbit modeling developed in this study using the ephemeris information of the satellite images and ground control points. We also corrected radiometric distortion caused by the terrain relief. Finally, the water area was identified from two images and the flood area is calculated accordingly. The identified flood area is analyzed by overlapping with the existing land use map.

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Application of Change Detection Techniques using KOMPSAT-1 EOC Images

  • Lee, Kwang-Jae;Kim, Youn-Soo
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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    • pp.222-227
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    • 2002
  • This research will examine into the capabilities of KOMPSAI-1 EOC image application in the field of urban environment and at the same time, with that as its foundation, come to understand the urban changes of the study areas. This research is constructed in three stages: Firstly, for application of change detection techniques, which utilizes multi-temporal remotely sensed data, the data normalization process is carried out. Secondly, change detection method is applied fur the systematic monitoring of land use changes, which utilizes multi-temporal EOC images. Lastly, by using the results of the application of land use changes, the existing land use map is updated. Consequently, the land-use change patterns are monitored, which utilize multi-temporal panchromatic EOC image data; and application potentials of ancillary data fur updating existing data can be presented. In this research, with the use of the land use change, monitoring of urban growth has been carried out, and the potential for the application of KOMPSAT-1 EOC images and the scope of application was examined. Henceforth, the future expansion of the scope of application of KOMPSAT-1 EOC image is anticipated.

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A HIERARCHICAL APPROACH TO HIGH-RESOLUTION HYPERSPECTRAL IMAGE CLASSIFICATION OF LITTLE MIAMI RIVER WATERSHED FOR ENVIRONMENTAL MODELING

  • Heo, Joon;Troyer, Michael;Lee, Jung-Bin;Kim, Woo-Sun
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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    • pp.647-650
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    • 2006
  • Compact Airborne Spectrographic Imager (CASI) hyperspectral imagery was acquired over the Little Miami River Watershed (1756 square miles) in Ohio, U.S.A., which is one of the largest hyperspectral image acquisition. For the development of a 4m-resolution land cover dataset, a hierarchical approach was employed using two different classification algorithms: 'Image Object Segmentation' for level-1 and 'Spectral Angle Mapper' for level-2. This classification scheme was developed to overcome the spectral inseparability of urban and rural features and to deal with radiometric distortions due to cross-track illumination. The land cover class members were lentic, lotic, forest, corn, soybean, wheat, dry herbaceous, grass, urban barren, rural barren, urban/built, and unclassified. The final phase of processing was completed after an extensive Quality Assurance and Quality Control (QA/QC) phase. With respect to the eleven land cover class members, the overall accuracy with a total of 902 reference points was 83.9% at 4m resolution. The dataset is available for public research, and applications of this product will represent an improvement over more commonly utilized data of coarser spatial resolution such as National Land Cover Data (NLCD).

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Bar 타겟을 이용한 DMC 영상의 공간해상력 검증 (Verification of Spatial Resolution in DMC Imagery using Bar Target)

  • 이태윤;이재원;윤부열
    • 한국측량학회지
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    • 제30권5호
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    • pp.485-492
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    • 2012
  • 최근 디지털 항공영상 센서는 다양한 국가 공간정보기반구축에 큰 역할을 하고 있다. 하지만 고정밀의 신뢰성 있는 자료를 확보하기 위해서는 취득된 디지털영상에 대한 적절한 품질 평가 작업이 선행되어야 한다. 따라서 현재 관련분야의 연구가 국내외적으로 크게 주목을 받고 있다. 디지털카메라의 성능을 테스트하기 위한 영상해상력 검증용 테스트필드가 유럽과 미국 등에서 이미 설치 및 활용되고 있다. 이러한 테스트필드에는 카메라의 기하학적 성능분석을 위한 대공표지를 비롯하여 공간해상력 및 방사해상력 분석을 위한 다양한 형태의 타겟 역시 설치되어 있다. 본 연구에서는DMC 카메라의 공간해상력을 검증하기 위하여 영상에서 인식 가능한 크기의 바 타겟(bar target)을 제작 설치 후 항공촬영을 수행하였다. 연구에 사용된 DMC 영상의 이론적인 지상표본거리(GSD ; Ground Sample Distance)는 12cm 급으로, 촬영 비행방향과 비행방향의 직각방향에 대하여 보조영상과 집성영상에 대하여 각각 실제 해상력을 분석하였다. 연구결과 이론적인 해상력과 영상의 실제 해상력간의 차이는 약 0.6cm로 나타났으며, 블록의 가장자리에 위치한 영상에서 최대 1.5cm 정도로 나타났다.

농경지 지역 무인항공기 영상 기반 시계열 수치표고모델 표고 보정 (Elevation Correction of Multi-Temporal Digital Elevation Model based on Unmanned Aerial Vehicle Images over Agricultural Area)

  • 김태헌;박주언;윤예린;이원희;한유경
    • 한국측량학회지
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    • 제38권3호
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    • pp.223-235
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    • 2020
  • 본 연구에서는 무인항공기 영상 기반의 정밀농업(precision agricultural) 구현에 있어 핵심 데이터 중 하나인 수치표고모델의 표고를 보정하기 위한 수치표고모델 표고 보정 방법론을 제시한다. 먼저 정사영상에 방사보정을 수행한 다음 ExG (Excess Green)를 생성한다. ExG에 Otsu 기법을 적용하여 산출된 임계값을 기준으로 비식생지역을 추출한다. 이어서, 비식생지역의 위치에 대응되는 수치표고모델의 표고를 표고 보정을 위한 데이터인 EIFs(Elevation Invariant Features)로 추출한다. 추출된 EIFs 간 차이값을 기반으로 정규화된 Z-score를 산출하여 포함된 특이치를 제거한다. 그리고 선형회귀식을 구성하여 수치표고모델의 표고를 보정함으로써 지상기준점 데이터 없이 고품질의 수치표고모델을 제작한다. 총 10장의 수치표고모델을 활용하여 제안기법을 검증하기 위해 표고 보정 전과 후의 최대/최소값, 평균/표준편차를 비교분석하였다. 또한, 검사점을 선정하여 RMSE (Root Mean Square Error)를 산출한 결과, 정확도는 평균 RMSE 0.35m로 도출되었다. 이를 통해 지상기준점 데이터 없이 고품질의 수치표고모델을 제작할 수 있음을 확인하였다.