• Title/Summary/Keyword: hyperion

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The Virtual Environment Control using Real-time Graphic Deformation Algorithm (실시간 그래픽 디포메이션 알고리즘을 이용한 가상환경젱어)

  • 강원찬;김남오;최창주
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.53 no.5
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    • pp.309-314
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    • 2004
  • In the established virtual-reality system, although it is possible to transact a faculty of sensation and graphic in a single PC, virtual object forcibly treated with rigid body for the reason of the huge amount of calculation, and the number of polygon is restricted. Furthermore, there is some difficulty in the financial aspect and a program field, because the existing virtual-reality system needs at least two workstations or super computers. In this study, the new force-reflecting algorithm called as "Proxy" and a finite element method of Hyperion are applied to this system in order to transact in real-time. Consequently, though the number of polygon, which brings about an obstacle is increased in the real-time graphic transaction, this system makes it possible to transact in the real-time, not being influenced by the size of the virtual object.

The Endmember Analysis for Sub-Pixel Detection Using the Hyperspectral Image

  • Kim, Dae-Sung;Cho, Young-Wook;Han, Dong-Yeob;Kim, Young-Il
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.732-734
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    • 2003
  • In the middle -resolution remote sensing, the Ground Sampled Distance(GSD) sensed and sampled by the detector is generally larger than the size of objects(or materials) of interest, in which case several objects are embedded in a single pixel and cannot be detected spatially. This study is intended to solve this problem of a hyperspectral data with high spectral resolution. We examined the detection algorithm, Linear Spectral Mixing Model, and also made a test on the Hyperion data. To find class Endmembers, we applied two methods, Spectral Library and Geometric Model, and compared them with each other.

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Usefulness of Canonical Correlation Classification Technique in Hyper-spectral Image Classification (하이퍼스펙트럴영상 분류에서 정준상관분류기법의 유용성)

  • Park, Min-Ho
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.5D
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    • pp.885-894
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    • 2006
  • The purpose of this study is focused on the development of the effective classification technique using ultra multiband of hyperspectral image. This study suggests the classification technique using canonical correlation analysis, one of multivariate statistical analysis in hyperspectral image classification. High accuracy of classification result is expected for this classification technique as the number of bands increase. This technique is compared with Maximum Likelihood Classification(MLC). The hyperspectral image is the EO1-hyperion image acquired on September 2, 2001, and the number of bands for the experiment were chosen at 30, considering the band scope except the thermal band of Landsat TM. We chose the comparing base map as Ground Truth Data. We evaluate the accuracy by comparing this base map with the classification result image and performing overlay analysis visually. The result showed us that in MLC's case, it can't classify except water, and in case of water, it only classifies big lakes. But Canonical Correlation Classification (CCC) classifies the golf lawn exactly, and it classifies the highway line in the urban area well. In case of water, the ponds that are in golf ground area, the ponds in university, and pools are also classified well. As a result, although the training areas are selected without any trial and error, it was possible to get the exact classification result. Also, the ability to distinguish golf lawn from other vegetations in classification classes, and the ability to classify water was better than MLC technique. Conclusively, this CCC technique for hyperspectral image will be very useful for estimating harvest and detecting surface water. In advance, it will do an important role in the construction of GIS database using the spectral high resolution image, hyperspectral data.

Change Detection Using Spectral Unmixing and IEA(Iterative Error Analysis) for Hyperspectral Images (IEA(Iterative Error Analysis)와 분광혼합분석기법을 이용한 초분광영상의 변화탐지)

  • Song, Ahram;Choi, Jaewan;Chang, Anjin;Kim, Yongil
    • Korean Journal of Remote Sensing
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    • v.31 no.5
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    • pp.361-370
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    • 2015
  • Various algorithms such as Chronochrome(CC), Principle Component Analysis(PCA), and spectral unmixing have been studied for hyperspectral change detection. Change detection by spectral unmixing offers useful information on the nature of the change compared to the other change detection methods which provide only the locations of changes in the scene. However, hyperspectral change detection by spectral unmixing is still in an early stage. This research proposed a new approach to extract endmembers, which have identical properties in temporally different images, by Iterative Error Analysis (IEA) and Spectral Angle Mapper(SAM). The change map obtained from the difference of abundance efficiently showed the changed pixels. Simulated images generated from Compact Airborne Spectrographic Imager (CASI) and Hyperion were used for change detection, and the experimental results showed that the proposed method performed better than CC, PCA, and spectral unmixing using N-FINDR. The proposed method has the advantage of automatically extracting endmembers without prior information, and it could be applicable for the real images composed of many materials.

Flux of Volatile Organic Compounds from Wastewater Treatment Plant (하수처리장에서 휘발성유기화합물의 FLUX)

  • Kim, Jong O;Chang, Daniel P.Y.;Lee, Woo Bum
    • Journal of Korean Society of Environmental Engineers
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    • v.22 no.1
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    • pp.91-101
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    • 2000
  • The emission sources of volatile organic compounds (VOCs) are wastewater treatment plants. sanitary landfills, automobile industries, and so on. The VOCs are harmful to human beings because of their toxicity and carcinogenicity, and cause the serious air pollution problem producing ozone ($O_3$) as a result of photochemical reaction. To investigate the emission of VOCs from wastewater treatment plant, aeration basins at the City of Los Angeles' Hyperion Treatment Plant were selected and measured flux was compared with calculated flux. For compounds commonly associated with wastewater (DCM, TCM, PCE, UM, DCB, UND) and not expected in vehicle exhaust or ambient air coming off the ocean, concentrations immediately downwind of the aeration basins were a factor of ten or higher than those measured in the upwind air. The airborne flux of less degradable or non-biodegradable compounds, e.g., DCE, DCM, TCA, DCA, TCM, PCE, DCB, through an imaginary plane at the downwind side of the aeration basins was in agreement with the estimated flux from measured liquid phase concentrations. Henry's constant. aeration rate, and an assumption of bubble saturation. For several compounds (PCE, DCE, TCA), the ratio (measured flux/calculated flux) is almost unity.

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The Development of Major Tree Species Classification Model using Different Satellite Images and Machine Learning in Gwangneung Area (이종센서 위성영상과 머신 러닝을 활용한 광릉지역 주요 수종 분류 모델 개발)

  • Lim, Joongbin;Kim, Kyoung-Min;Kim, Myung-Kil
    • Korean Journal of Remote Sensing
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    • v.35 no.6_2
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    • pp.1037-1052
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    • 2019
  • We had developed in preceding study a classification model for the Korean pine and Larch with an accuracy of 98 percent using Hyperion and Sentinel-2 satellite images, texture information, and geometric information as the first step for tree species mapping in the inaccessible North Korea. Considering a share of major tree species in North Korea, the classification model needs to be expanded as it has a large share of Oak(29.5%), Pine (12.7%), Fir (8.2%), and as well as Larch (17.5%) and Korean pine (5.8%). In order to classify 5 major tree species, national forest type map of South Korea was used to build 11,039 training and 2,330 validation data. Sentinel-2 data was used to derive spectral information, and PlanetScope data was used to generate texture information. Geometric information was built from SRTM DEM data. As a machine learning algorithm, Random forest was used. As a result, the overall accuracy of classification was 80% with 0.80 kappa statistics. Based on the training data and the classification model constructed through this study, we will extend the application to Mt. Baekdu and North and South Goseong areas to confirm the applicability of tree species classification on the Korean Peninsula.

Absolute Radiometric Calibration for KOMPSAT-3 AEISS and Cross Calibration Using Landsat-8 OLI

  • Ahn, Hoyong;Shin, Dongyoon;Lee, Sungu;Choi, Chuluong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.35 no.4
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    • pp.291-302
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    • 2017
  • Radiometric calibration is a prerequisite to quantitative remote sensing, and its accuracy has a direct impact on the reliability and accuracy of the quantitative application of remotely sensed data. This paper presents absolute radiometric calibration of the KOMPSAT-3 (KOrea Multi Purpose SATellite-3) and cross calibration using the Landsat-8 OLI (Operational Land Imager). Absolute radiometric calibration was performed using a reflectance-based method. Correlations between TOA (Top Of Atmosphere) radiances and the spectral band responses of the KOMPSAT-3 sensors in Goheung, South Korea, were significant for multispectral bands. A cross calibration method based on the Landsat-8 OLI was also used to assess the two sensors using near simultaneous image pairs over the Libya-4 PICS (Pseudo Invariant Calibration Sites). The spectral profile of the target was obtained from EO-1 (Earth Observing-1) Hyperion data over the Libya-4 PICS to derive the SBAF (Spectral Band Adjustment Factor). The results revealed that the TOA radiance of the KOMPSAT-3 agree with Landsat-8 within 5.14% for all bands after applying the SBAF. The radiometric coefficient presented here appears to be a good standard for maintaining the optical quality of the KOMPSAT-3.

The radiation shielding competence and imaging spectroscopic based studies of Iron ore region of Kozhikode district, Kerala

  • S. Arivazhagan;K.A. Naseer;K.A. Mahmoud;S.A. Bassam;P.N. Naseef Mohammed;N.K. Libeesh;A.S. Sachana;M.I. Sayyed;Mohammed S. Alqahtani;E. El Shiekh;Mayeen Uddin Khandaker
    • Nuclear Engineering and Technology
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    • v.55 no.7
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    • pp.2380-2387
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    • 2023
  • Hyperspectral data and its ability to explore the minerals and their associated rocks have a remarkable application in mineral exploration and lithological characterization. The present study aims to explore the radiation shielding aspects of the iron ore in Kerala with the aid of the Hyperion hyperspectral dataset. The reflectance-spectra obtained from the laboratory conditions as well as from the image show various absorptions. The results from the spectra are validated with geochemical data and GPS points. The Monte Carlo simulation employed to evaluate the radiation shielding ability. Raising the oxygen ions caused a noteworthy decrease in the µ values of the studied rocks which is accompanied by an increase in Δ0.5 and Δeq values. The Δ0.5 and Δeq values increased by factors of approximately 77 % with raising the oxygen ions between 44.32 and 47.57 wt.%. The µ values varies with the oxygen concentrations, where the µ values decreased from 2.531 to 0.925 cm-1 (at 0.059 MeV), from 0.381to 0.215 cm-1 (at 0.662 MeV), and from 0.279 to 0.158 cm-1 (at 1.25 MeV) with raising the oxygen ions from 44.32 to 47.43 wt.%.