• Title/Summary/Keyword: Hyperspectral image (HSI)

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An Adequate Band Selection for Vegetation Index of CASI-1500 Airborne Hyperspectral Imagery Using Image Differencing and Spectral Derivative (차연산과 분광미분을 이용한 항공 초분광영상의 식생지수 산출 적절밴드 선택)

  • Kim, Tae-Woo;We, Gwang-Jae;Suh, Yong-Cheol
    • Journal of the Korean Association of Geographic Information Studies
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    • v.16 no.4
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    • pp.16-28
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    • 2013
  • Recently the various applications and spectral indices development of airborne hyperspectral imagery(A-HSI) has been increased. Especially the vegetation indices (VIs) were used to verify stress and vigor of vegetation. The VIs needs two or more spectral bands selectively to calculate as NIR(near infrared) and red wavelength. The A-HIS has specific band characteristics as narrow, continues and many. The A-HIS has narrow, continues and many specific band characteristics. That could be make it confuse which of bands could be explained for appropriate vegetation characteristics. If the A-HIS bands is not the same the wavelength with VIs' development band setting, then it need a selection adequate for spectral characteristics of target vegetation. Therefore we set 4 substitute bands for NIR and red wavelength respectively and calculated two VIs combined with substitute bands such as NDVI(normalized difference vegetation index) and MSRI(modified simple ratio index). To consider the variation of each VIs, we adapted the image differencing method of change detection technique. Also, we used spectral derivative to identify appropriate bands for spectral characteristics of digital forest cover type map. The result of adequate bands for two VIs selected red #3 as 680.2nm and NIR #2 as 801.7nm. This wavelength was good for any forest type in low variations.

A Study on the building of the Basic library by using Hyperspectral Image Based Algal Medium (초분광영상 기반 조류 배양액을 이용한 기초라이브러리 구축에 대한 연구)

  • Kim, Gwang Soo;Kim, Young Do;You, Ho Jun;Kim, Dong Su
    • Proceedings of the Korea Water Resources Association Conference
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    • 2020.06a
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    • pp.48-48
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    • 2020
  • 최근 이상기후변화로 인해 수환경 변화가 일어나고 있다. 그로 인해 국내에서 조류의 과대성장이 빈번히 발생되고 있으다. 이로 인해 유해남조류 등 조류가 생산하는 독성물질, 이취미 물질은 수질을 악화시키고 있으며, 생태계에 큰영향을 미친다. 조류는 하천에서 넓은 분포로 발생하게 되는데 이러한 조류 모니터링에는 많은 인력과 시간이 소요된다. 국내에선 인력과 시간을 줄이기 위해 최근 원격탐사 기법을 이용한 조류 모니터링에 대한 연구가 많이 진행되고 있다. 본 연구에서는 녹조류, 남조류 5종을 이용해 실험을 진행하였다. 사용된 초분광 센서는 CORNING사의 microHSITM 410 SHARK를 이용하였으며 파장 400-1000 nm에서 NIR(visNIR)파장을 분석할 수 있으며, 초분광 센서를 정사로 영상을 촬영하기 위해 짐벌을 이용하여 영상을 수집하였다. 영상을 촬영 전 방사보정을 하기 위해 시료와 동일 선상에 99% 반사율을 갖는 백색반사판을 같이 촬영하여 방사보정을 진행하였다. 본 연구에서는 시기와 상관없이 조류에 대한 연구를 하기위해 조류배양액을 이용하였으며, 남조의 경우 470 nm에서 분광 특성을 나타내었으며, 녹조의 경우 477-510 nm에서 분광 특성을 나타났다. 초분광영상을 통해 기초라이브러리를 구축하고 구축된 라이브러리를 통해 조류의 분광특성을 분석하고 제시하여 하천에 적용하고자 한다.

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Airborne Hyperspectral Imagery availability to estimate inland water quality parameter (수질 매개변수 추정에 있어서 항공 초분광영상의 가용성 고찰)

  • Kim, Tae-Woo;Shin, Han-Sup;Suh, Yong-Cheol
    • Korean Journal of Remote Sensing
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    • v.30 no.1
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    • pp.61-73
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    • 2014
  • This study reviewed an application of water quality estimation using an Airborne Hyperspectral Imagery (A-HSI) and tested a part of Han River water quality (especially suspended solid) estimation with available in-situ data. The estimation of water quality was processed two methods. One is using observation data as downwelling radiance to water surface and as scattering and reflectance into water body. Other is linear regression analysis with water quality in-situ measurement and upwelling data as at-sensor radiance (or reflectance). Both methods drive meaningful results of RS estimation. However it has more effects on the auxiliary dataset as water quality in-situ measurement and water body scattering measurement. The test processed a part of Han River located Paldang-dam downstream. We applied linear regression analysis with AISA eagle hyperspectral sensor data and water quality measurement in-situ data. The result of linear regression for a meaningful band combination shows $-24.847+0.013L_{560}$ as 560 nm in radiance (L) with 0.985 R-square. To comparison with Multispectral Imagery (MSI) case, we make simulated Landsat TM by spectral resampling. The regression using MSI shows -55.932 + 33.881 (TM1/TM3) as radiance with 0.968 R-square. Suspended Solid (SS) concentration was about 3.75 mg/l at in-situ data and estimated SS concentration by A-HIS was about 3.65 mg/l, and about 5.85mg/l with MSI with same location. It shows overestimation trends case of estimating using MSI. In order to upgrade value for practical use and to estimate more precisely, it needs that minimizing sun glint effect into whole image, constructing elaborate flight plan considering solar altitude angle, and making good pre-processing and calibration system. We found some limitations and restrictions such as precise atmospheric correction, sample count of water quality measurement, retrieve spectral bands into A-HSI, adequate linear regression model selection, and quantitative calibration/validation method through the literature review and test adopted general methods.