• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1307-1309
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• 2003

The EO-1 spacecraft, launched November 21, 2000 into a sun synchronous orbit behind Landsat 7, hosts advanced technology demonstration instruments, whose capabilities are currently being assessed by the user community for future missions. A significant part of the EO-1 program is to perform data comparisons between Hyperion, ALI and Landsat 7 ETM+. In this paper, a comparison of forest classification results from Hyperion, ALI, and the ETM+ of Landsat-7 are provided for Wangqing Forest Bureau, Jilin Province, Northeast China. The data have been radiometrically corrected and geometrically resampled. Feature selection and statistical transforms are used to reduce the Hyperion feature space from 86 channels to 14 features. Classes chosen for discrimination included Larch, Spruce, Oak, Birch, Popular and Mixed forest and other landuses. Classification accuracies have been obtained for each sensor. Comparison of the classification results shows : Hyperion classification results were the best, ALI's were much better than ETM+.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.3
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• pp.289-297
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• 2006

The Land Cover/Land Use Map have been constructed from 1998, which has hierarchical structure according to land cover/land use system. Level 1 classification Map have done using Landsat satellite image over whole Korean peninsula. Level II classification Map have been digitized using IRS-1C, 1D, KOMPSAT and SPOT5 satellite images resolution-merged with low resolution color images. Level II Land Cover/Land Use Map construction by digitizing method, however, is consuming enormous expense for satellite image acquisition, image process and Land Cover/Land Use Map construction. In this paper, the possibility of constructing Level II Land Cover/Land Use Map using hyperspectral satellite image of EO-1 Hyperion, which is studied a lot recently, is studied. The comparison of classifications using Hyperion satellite image offering more spectral information and Landsat-7 ETM+ image is performed to evaluate the availability of Hyperion satellite image. Also, the algorithm of the optimal band selection is presented for effective application of hyperspectral satellite image.

• Korean Journal of Remote Sensing
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• v.29 no.4
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• pp.399-406
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• 2013

The quality of satellite imagery should be improved and stabilized to satisfy numerous users. The radiometric characteristics of an optical sensor can be a measure of data quality. In this study, a band aggregation technique and spectral response function of hyperspectral images are used to simulate multispectral images. EO-1 Hyperion and Landsat-8 OLI images acquired with about 30 minutes difference in overpass time were exploited to evaluate radiometric coefficients of OLI. Radiance values of the OLI and the simulated OLI were compared over three subsets covered by different land types. As a result, the index of agreement shows over 0.99 for all VNIR bands although there are errors caused by space/time and sensors.

• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.291-294
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• 2006

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1470-1472
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• 2003

Hyperion, as hyperspectral data, is carried on NASA’s EO-1 satellite, can be used in more subtle discrimination on forest cover, with 224 band in 360 ?2580 nm (10nm interval). In this study, Hyperion image is used to investigate the effects of topography on the classification of forest cover, and to assess whether the topographic correction improves the discrimination of species units for practical forest mapping. A publicly available Digital Elevation Model (DEM), at a scale of 1:25,000, is used to model the radiance variation on forest, considering MSR(Mean Spectral Ratio) on antithesis aspects. Hyperion, as hyperspectral data, is corrected on a pixel-by-pixel basis to normalize the scene to a uniform solar illumination and viewing geometry. As a result, the approach on topographic effect normalization in hyperspectral data can effectively reduce the variation in detected radiance due to changes in forest illumination, progress the classification of forest cover.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.576-578
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• 2003

Hyperspectral image divides VNIR region to over 200 bands which can show continuous spectrum with 10 nm spectral resolution. This property is useful in geology where a spectral feature which is decided by chemical compositions and crystalline structures is recorded well. While this field has been studied variously in foreign countries, the studies are in the early stage in Korea. In this study, characteristic materials associated with AMD were classified by using EO-1 HYPERION data which is a spaceborne hyperspectral image and topographical map and DEM and geochemical map were analyzed in conjunction with the image in order to examine that classified minerals are secondary minerals by AMD.

• Korean Journal of Remote Sensing
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• v.23 no.1
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• pp.7-14
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• 2007

Atmospheric correction is one of critical procedures to extract quantitative information related to biophysical variables from hyperspectral imagery. Most atmospheric correction algorithms developed for hyperspectral data have been based upon atmospheric radiative transfer (RT) codes, such as MODTRAN. Because of the difficulty in acquisition of atmospheric data at the time of image capture, the complexity of RT model, and large volume of hyperspectral data, atmospheric correction can be very difficult and time-consuming processing. In this study, we attempted to develop an efficient method for the atmospheric correction of EO-1 Hyperion data. This method uses the pre-calculated look-up-table (LUT) for fast and simple processing. The pre-calculated LUT was generated by successive running of MODTRAN model with several input parameters related to solar and sensor geometry, radiometric specification of sensor, and atmospheric condition. Atmospheric water vapour contents image was generated directly from a few absorption bands of Hyperion data themselves and used one of input parameters. This new atmospheric correction method was tested on the Hyperion data acquired on June 3, 2001 over Seoul area. Reflectance spectra of several known targets corresponded with the typical pattern of spectral reflectance on the atmospherically corrected Hyperion image, although further improvement to reduce sensor noise is necessary.

• Korean Journal of Remote Sensing
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• v.24 no.6
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• pp.631-639
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• 2008

This study presents an approach to synthesize hyperspectral images of lower resolution at a higher resolution using the high resolution images acquired from a sensor of commercial satellites. The proposed method was applied to the reconstruction of EO-1 Hyperion images using the images acquired from IKONOS sensor. Based on the FitPAN-Mod pansharpening technique (Lee, 2008b), the hyperspectral images of 30m resolution were reconstructed at 1m resolution of IKONOS panchromatic image. In this study, the synthesized hyperspectral images of 50 bands, whose wavelengths range in the wavelength of panchromatic sensor, were generated from the three stages of high resolution reconstruction using FitPAN-Mod. The experimental results show that the proposed method effectively integrates the spatial detail of the panchromatic modality as well as the spectral detail of the hyperspectral one into the synthesized image. It indicates the proposed method has a potential as a technique to produce alternative images for the images that would have been observed from a hyperspectral sensor at the high resolution of commercial satellite images.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.1
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• pp.63-70
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• 2015

An Image fusion, or Pansharpening is a methodology of increasing the spatial resolution of image with low-spatial resolution using high-spatial resolution images. In this paper, we have performed an image fusion of hyperspectral imagery by using panchromatic image with high-spatial resolution, multispectral and hyperspectral images with low-spatial resolution, which had been acquired by ALI and Hyperion of EO-1 satellite sensors. The study has been mainly focused on evaluating performance of fusion process following to the image fusion methodology of the block association, which had applied to ALI and Hyperion dataset by considering spectral characteristics between multispectral and hyperspectral images. The results from experiments have been identified that the proposed algorithm efficiently improved the spatial resolution and minimized spectral distortion comparing with results from a fusion of the only panchromatic and hyperspectral images and the existing block-based fusion method. Through the study in a proposed algorithm, we could concluded in that those applications of airborne hyperspectral sensors and various hyperspectral satellite sensors will be launched at future by enlarge its usages.

• Proceedings of the KSRS Conference
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• 2008.03a
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• pp.219-223
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• 2008

초분광 영상은 기존의 다중분광 영상보다 많은 파장대의 영상을 취득하기 때문에 다양한 분야의 연구에 이용되고 있다. 하지만 밴드별로 취득하는 파장대가 짧고 밴드수가 많아, 밴드간의 높은 상관관계 및 노이즈 밴드가 존재한다. 이로 인해 기존에 알려진 분석기법의 적용결과가 제대로 도출되지 않는다. 따라서 초분광 영상을 이용할 경우, 노이즈가 많이 포함된 밴드를 제거한 후 영상분석을 하는 것이 보다 효율적이다. 본 연구에서는 초분광 영상(Hyperspectral Image)의 전처리 과정 중 노이즈 밴드 제거에 초점을 맞추었으며, 이를 위해 프랙탈 차원을 이용하였다. 프랙탈 차원 측정방법 중 삼각기둥 표면적 기법을 이용하였다. 프랙탈 차원을 측정하고, Continuum Removal 기법을 이용하여 경향을 살펴보았다. 경험적으로 구한 임계값을 통해 상대적으로 정보량이 적은 밴드를 노이즈 밴드로 판단하여 제거하였다. 실험 영상으로는 EO-1 위성에서 취득되는 Hyperion 초분광 영상을 사용하였다. 실험 결과 프랙탈 분석을 통해 Hyperion 초분광 영상의 노이즈 밴드를 자동으로 추출하여 제거할 수 있음을 확인하였다.