• Title/Summary/Keyword: Airborne remote sensing

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Detection of The Pine Trees Damaged by Pine Wilt Disease using High Resolution Satellite and Airborne Optical Imagery

  • Lee, Seung-Ho;Cho, Hyun-Kook;Lee, Woo-Kyun
    • Korean Journal of Remote Sensing
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    • v.23 no.5
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    • pp.409-420
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    • 2007
  • Since 1988, pine wilt disease has spread over rapidly in Korea. It is not easy to detect the damaged pine trees by pine wilt disease from conventional remote sensing skills. Thus, many possibilities were investigated to detect the damaged pines using various kinds of remote sensing data including high spatial resolution satellite image of 2000/2003 IKONOS and 2005 QuickBird, aerial photos, and digital airborne data, too. Time series of B&W aerial photos at the scale of 1:6,000 were used to validate the results. A local maximum filtering was adapted to determine whether the damaged pines could be detected or not at the tree level from high resolution satellite images, and to locate the damaged trees. Several enhancement methods such as NDVI and image transformations were examined to find out the optimal detection method. Considering the mean crown radius of pine trees, local maximum filter with 3 pixels in radius was adapted to detect the damaged trees on IKONOS image. CIR images of 50 cm resolution were taken by PKNU-3(REDLAKE MS4000) sensor. The simulated CIR images with resolutions of 1 m, 2 m, and 4 m were generated to test the possibility of tree detection both in a stereo and a single mode. In conclusion, in order to detect the pine tree damaged by pine wilt disease at a tree level from satellite image, a spatial resolution might be less than 1 m in a single mode and/or 1 m in a stereo mode.

Development and Verification of the Compact Airborne Imaging Spectrometer System

  • Lee, Kwang-Jae;Yong, Sang-Soon;Kim, Yong-Seung
    • Korean Journal of Remote Sensing
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    • v.24 no.5
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    • pp.397-408
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    • 2008
  • A wide variety of applications of imaging spectrometer have been proved using data from airborne systems. The Compact Airborne Imaging Spectrometer System (CAISS) was jointly designed and developed as the airborne hyperspectral imaging system by Korea Aerospace Research Institute (KARI) and ELOP inc., Israel. The primary mission of the CAISS is to acquire and provide full contiguous spectral information with high spatial resolution for advanced applications in the field of remote sensing. The CAISS consists of six physical units; the camera system, the gyro-stabilized mount, the jig, the GPS/INS, the power inverter and distributor, and the operating system. These subsystems are to be tested and verified in the laboratory before the flight. Especially the camera system of the CAISS has to be calibrated and validated with the calibration equipments such as the integrating sphere and spectral lamps. To improve data quality and its availability, it is the most important to understand the mechanism of imaging spectrometer system and the radiometric and spectral characteristics. The several performance tests of the CAISS were conducted in the camera system level. This paper presents the major characteristics of the CAISS, and summarizes the results of performance tests in the camera system level.

Study of Airborne Remote Sensing for Water Quality Monitoring (수질오염 감시에의 활용을 위한 항공원격탐사의 적용연구)

  • 김광은;이태섭
    • Spatial Information Research
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    • v.2 no.1
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    • pp.65-74
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    • 1994
  • Recently, as remote sensing is widely used for environmental monitoring, more precise quantitative analysis of remote sensing data is required. In this paper, themat ic maps of water qual i ty factors such as chlorophyll-a, transparency, and suspended sediments were presented from the high resoltion airborne remote sensing data of HapCheon Dam. Though it was difficult to explicitly correlate remote sensing data with water quality factors due to the insufficient number of ground teuth data, the presented water quality maps showed very well the overall spatial distribution of water pollution in the Lake.

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ANALYSIS OF OCEAN WAVE BY AIRBORNE PI-SAR X-BAND IMAGES

  • Yang, Chan-Su;Ouchi, Kazuo
    • Proceedings of the KSRS Conference
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    • 2008.10a
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    • pp.240-242
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    • 2008
  • In the present article, we analyze airborne Pi-SAR (Polarimetric-Interferometric SAR) X-band images of ocean waves around the Miyake Island at approximately 180 km south from Tokyo, Japan. Two images of a same scene were produced at approximately 40 min. interval from two directions at right angles. One image shows dominant range travelling waves, but the other image shows a different wave pattern. This difference can be caused by the different image modulations of RCS and velocity bunching. We have estimated the dominant wavelength from the image of range waves, and from the wave phase velocity computed from the dispersion relation (though no wave height data were available), the image intensity is computed by using the velocity bunching model. The comparison of the result with the second image at right angle strongly suggests the evidence of velocity bunching.

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Forest Canopy Density Estimation Using Airborne Hyperspectral Data

  • Kwon, Tae-Hyub;Lee, Woo-Kyun;Kwak, Doo-Ahn;Park, Tae-Jin;Lee, Jong-Yoel;Hong, Suk-Young;Guishan, Cui;Kim, So-Ra
    • Korean Journal of Remote Sensing
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    • v.28 no.3
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    • pp.297-305
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    • 2012
  • This study was performed to estimate forest canopy density (FCD) using airborne hyperspectral data acquired in the Independence Hall of Korea in central Korea. The airborne hyperspectral data were obtained with 36 narrow spectrum ranges of visible (Red, Green, and Blue) and near infrared spectrum (NIR) scope. The FCD mapping model developed by the International Tropical Timber Organization (ITTO) uses vegetation index (VI), bare soil index (BI), shadow index (SI), and temperature index (TI) for estimating FCD. Vegetation density (VD) was calculated through the integration of VI and BI, and scaled shadow index (SSI) was extracted from SI after the detection of black soil by TI. Finally, the FCD was estimated with VD and SSI. For the estimation of FCD in this study, VI and SI were extracted from hyperspectral data. But BI and TI were not available from hyperspectral data. Hyperspectral data makes the numerous combination of each band for calculating VI and SI. Therefore, the principal component analysis (PCA) was performed to find which band combinations are explanatory. This study showed that forest canopy density can be efficiently estimated with the help of airborne hyperspectral data. Our result showed that most forest area had 60 ~ 80% canopy density. On the other hand, there was little area of 10 ~ 20% canopy density forest.

Change Detection of Buildings Using High Resolution Remotely Sensed Data

  • Zeng, Yu;Zhang, Jixian;Wang, Guangliang
    • Proceedings of the KSRS Conference
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    • 2002.10a
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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.

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High Resolution Remote Sensing Research of Climatic Change of Luobupo Saline During Past 2000 Years

  • Xie, Lian-wen;Zheng, Qi-sen
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.1319-1322
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    • 2003
  • According to the evolutive theory of saline, combined with field survey data, the authors have discussed the theoretical model of recording past climatic change of Luobupo saline. After interpreted and analyzed the causes of the ringy image, the authors have mapped high resolution climatic changing graph of Luobupo saline during past 2000 years by using remote sensing method. Contrast to the known results, it is proved that the research results have comparability and continuity. The resolution of special climatic event can reach in one year, and in general, the resolution of climatic change can reach in ten to twenty years.

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Support Vector Machine and Spectral Angle Mapper Classifications of High Resolution Hyper Spectral Aerial Image

  • Enkhbaatar, Lkhagva;Jayakumar, S.;Heo, Joon
    • Korean Journal of Remote Sensing
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    • v.25 no.3
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    • pp.233-242
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    • 2009
  • This paper presents two different types of supervised classifiers such as support vector machine (SVM) and spectral angle mapper (SAM). The Compact Airborne Spectrographic Imager (CASI) high resolution aerial image was classified with the above two classifier. The image was classified into eight land use /land cover classes. Accuracy assessment and Kappa statistics were estimated for SVM and SAM separately. The overall classification accuracy and Kappa statistics value of the SAM were 69.0% and 0.62 respectively, which were higher than those of SVM (62.5%, 0.54).

Local Detection of Road Using Mathematical Morphology On Airborne SAR Image

  • Yang, Jin-Hyun;Moon, Wooil-M.
    • Proceedings of the KSRS Conference
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    • 2002.10a
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    • pp.17-22
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    • 2002
  • This paper is concerned with a local detection of road on an airborne SAR image. The roads can be characterized by their geometry and radiometry. Roads are assumed as linear, thin, and elongated objects that are darker than their surroundings on an airborne SAR image. With these assumptions, a series of morphological filters are applied and tested successively. This approach is simple and almost non parametric and has been successfully applied to an airborne SAR image.

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3D BUILDING RECONSTRUCTION FROM AIRBORNE LASER SCANNING DATA

  • Lee, Jeong-Ho;Han, Soo-Hee;Yu, Ki-Yun;Kim, Yong-Il
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.587-590
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    • 2007
  • The demand for more accurate and realistic 3D urban models has been increasing more and more. Many studies have been conducted to extract 3D features from remote sensing data such as satellite images, aerial photos, and airborne laser scanning data. In this paper a technique is presented to extract and reconstruct 3D buildings in urban areas using airborne laser scanning data. Firstly all points in a building were divided into some groups by height difference. From segmented laser scanning data of irregularly distributed points we generalized and regularized building boundaries which better approximate the real boundaries. Then the roof points which are subject to the same groups were classified using pre-defined models by least squares fitting. Finally all parameters of the roof surfaces were determined and 3D building models were constructed. Some buildings with complex shapes were selected to test our presented algorithms. The results showed that proposed approach has good potential for reconstructing complex buildings in detail using only airborne laser scanning data.

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