• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1055-1057
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• 2003

In this research, the concrete with paint film was classified using hyper-spectral remote sensing. First, spectral characteristics of concrete and concrete with some kinds of paint films were investigated with a spectrometer. Second, using reflectance and first order derivative, spectral characteristics of the normal concrete and the concrete with paint film were classified. By using hyper-spectral remote sensing, not only extraction of crack but also inspection of paint film distribution is possible.

• 대한원격탐사학회지
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• 제25권3호
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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).

• 대한원격탐사학회지
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• 제26권6호
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• pp.693-703
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• 2010

High spectral resolution of hyperspectral data enables analysis of complex natural phenomena that is reflected on the data nonlinearly. Although many manifold learning methods have been developed for such problems, most methods do not consider the spatial correlation between samples that is inherent and useful in remote sensing data. We propose a manifold learning method which directly combines the spatial proximity and the spectral similarity through kernel PCA framework. A gain factor caused by spatial proximity is first modelled with a heat kernel, and is added to the original similarity computed from the spectral values of a pair of samples. Parameters are tuned with intelligent grid search (IGS) method for the derived manifold coordinates to achieve optimal classification accuracies. Of particular interest is its performance with small training size, because labelled samples are usually scarce due to its high acquisition cost. The proposed spatial kernel PCA (KPCA) is compared with PCA in terms of classification accuracy with the nearest-neighbourhood classification method.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1400-1402
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• 2003

The objective of this paper is to determine the suitable spectral bands for monitoring growth status change during a long period. The long-term ground-level reflectance spectra as well as LAI and biomass were obtained in xiaotangshan area, Beijing, 2001. The narrow-band NDVI type spectral indices by all possible two bands were calculated their correlation coefficients R$^2$ with biomass and LAI. The best NDVIs must have higher R$^2$ with both biomass and LAI. The reasonable band centers and band widths were determined by a systematically increasing bandwidth centered over a wavelength. In addition, the first 19 bands of MODIS were simulated and investigated. Each developed spectral indices was then validated by the biomass and LAI time series using the generalized vector angle. It turned out that six new NDVI type indices within 750-1400nm were developed. NDVI(811_10,957_10) and NDVI(962_10,802_10) performed best. No satisfactory conventional NDVI formed by red and NIR bands were found effective. MODIS_NDVI(band19, band17) and MODIS_NDVI(band19, band2) were much better than MODIS_NDVI(band2,band1) for growth monitoring.

• 대한원격탐사학회지
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• 제23권1호
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• pp.21-32
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• 2007

Fire fuel map is one of the most critical factors for planning and managing the fire hazard and risk. However, fuel mapping is extremely difficult because fuel properties vary at spatial scales, change depending on the seasonal situations and are affected by the surrounding environment. Remote sensing has potential to reduce the uncertainty in mapping fuels and offers the best approach for improving our abilities. Especially, Hyperspectral sensor have a great potential for mapping vegetation properties because of their high spectral resolution. The objective of this paper is to evaluate the potential of mapping fuel properties using Hyperion hyperspectral remote sensing data acquired in April, 2002. Fuel properties are divided into four broad categories: 1) fuel moisture, 2) fuel green live biomass, 3) fuel condition and 4) fuel types. Fuel moisture and fuel green biomass were assessed using canopy moisture, derived from the expression of liquid water in the reflectance spectrum of plants. Fuel condition was assessed using endmember fractions from spectral mixture analysis (SMA). Fuel types were classified by fuel models based on the results of SMA. Although Hyperion imagery included a lot of sensor noise and poor performance in liquid water band, the overall results showed that Hyperion imagery have good potential for wildfire fuel mapping.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.565-565
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• 2004

• 대한원격탐사학회지
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• 제21권4호
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• pp.341-369
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• 2005

이 연구는 새로운 광학원격탐사자료로 대두되고 있는 초분광영상의 기본적 특성과 용어에 관한 정의를 검토하고, 지금까지 초분광영상과 관련된 주요 처리기법 및 활용분야를 광범위하게 검토하여 국내에서 초분광영상 기술의 활용을 위한 기초 자료를 제공하고자 한다. 먼저 문헌자료와 인터넷 검색을 통하여 항공기 및 위성탑재 센서와 지상용 카메라 등 현존하는 초분광센서의 종류 및 특성을 제시하였다 초분광영상과 관련된 연구 현황을 분석하기 위하여 원격탐사와 관련된 주요 국제학술지와 초분광영상 관련 학술발표회에서 발표된 논문들을 선정하여 센서별, 영상처리기법별, 주요 활용분야별로 나누어 정리하였다. 현재 항공기 및 위성 탑재 초분광영상 센서의 종류가 증가하고 있는 추세지만, 지금까지 초분광영상과 관련된 연구의 주된 부분은 미국 항공우주국에서 개발된 AVIRIS영상자료를 토대로 하고 있다. 기존의 다중분광영상에 보다 많은 분광밴드를 가진 초분광영상의 특성을 최대한 이용할 수 있는 영상처리기법이 개발되고 있다. 대기보정, 분광혼합분석, 특징추출 등이 초분광영상처리와 관련된 중요한 분야로 대두되고 있으나, 아직까지 보편적인 초분광영상 처리기술로 자리 잡기까지는 보다 많은 연구가 필요한 실정이다. 초분광영상이 가지고 있는 분광특성 정보를 최대한 이용하기에 적합한 암석 및 광물탐사가 초기의 주된 활용분야였으나, 식물의 물리화학적 정보 추출, 수질, 군용목표물 탐지 등 초분광영상의 활용은 기존의 다중분광영상의 한계를 극복하는 측면에서 확대될 전망이다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1998년도 Proceedings of International Symposium on Remote Sensing
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• pp.370-375
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• 1998

Spectral reflectance signatures of upland crops at OSMI bands were collected and evaluated for the feasibility of crop discrimination knowledge-based on crop calendar. Effective bands and their ratio values for discriminating corn from two other legumes were defined with OSMI equivalent bands and their ratio values. June 22 among measurements dates was the best date for corn discrimination from two other legumes, peanut and soybean, because all OSMI equivalent bands and their ratio values in June 22 were highly significant for corn separability. Phenological growth stage of a silage corn (rs510) could be estimated as a function of spectral reflectance signatures in vegetative stage. Five growth stage prediction models were generated by the SAS procedures REG and STEPWISE with OSMI equivalent bands and their ratio values in vegetative stage.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.573-575
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• 2003

In satellite spectra, Though the magnitude varies with intensity of sunstroke, dip angle of land so on, the shape is less deformed with these effects. from this point of view, we have developed a spectral shape-dependent analysis utilizing a normalization procedure by the spectral integral and applied it to Landsat/TM spectra. Inevitable topographic and atmospheric effects can be suppressed. The correction algorithm is very simple and timesaving and the suppression of topographic effects is especially effective. Normalized band 4 is almost linear to NDVI values, and is available to the vegetation index.

• Agricultural and Biosystems Engineering
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• 제7권1호
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• pp.27-41
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• 2006

Assessment of nitrogen and chlorophyll content from crop leaves can help growers adjust N fertilizer rates to meet the demands of the crop. Numerous researchers have presented their studies about spectral signature of plant leaves to characterize the plant features. However, interrelational review and summary were limited and a communication gap exists between the plant science and optical engineering. Understanding the mechanism of leaf interaction to electromagnetic radiation and factors affecting spectrophotometric measurements can enhance the foundation of optical remote sensing technologies. This paper provides extensive review of previous works in optical sensing and explains the basics of plant optics, spectral measurements for plant stress, factors that affect sensitivity to spectral analysis, and applications that deploy optical remote sensing technologies.