• Journal of the Korean Association of Geographic Information Studies
• /
• v.16 no.4
• /
• pp.16-28
• /
• 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.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.15 no.3
• /
• pp.52-65
• /
• 2012

The net biomass accumulation (or net primary production, NPP) and gross primary production (GPP) have closely related with carbon accumulations(or carbon exchange) in vegetation. There are many approaches to estimate biomass using remote sensing techniques. The vegetation indices (VIs) can be a methodology to estimate biomass which assumes total chlorophyll contents. Various VIs were characterized with difference development conditions as vegetation species, input datasets. The hyperspectral data have also different spatial/spectral resolutions for aerial surveying. Additionally they need particular spectral bands selection difficulty to calculate the VIs. The objective of this study is to evaluate the correlations with airborne hyperspectral data (compact airborne spectrographic imager, CASI) and spectral unmixing model (or spectral mixture analysis, SMA) to characterize vegetation indices in forest area. The spectral mixture analysis was used to model the spectral purity of each pixel as an endmember. The endmembers are the fraction components derived from hyperspectral data through the SMA. In this study, we choose three endmembers represented vegetation pixels in the hyperspectral data. These endmembers were compared with 9 VIs by the Pearson's correlation coefficient. The results show MTVI1 and TVI have same correlation coefficient with 0.877. The MCARI, especially has very high relationship with vegetation endmembers as 0.9061 at less vegetation and soil distributed site. The MTVI1 and TVI have high correlations with the vegetation endmembers as 0.757 in whole test sites.

• Speech Sciences
• /
• v.9 no.3
• /
• pp.3-16
• /
• 2002

We examined some problems in speaker identification procedures: transformation of acoustic parameters into auditory scales, invalid measurement values, and comparability of spectral energy values across the frequency range. To resolve those problems, we analyzed the acoustic spectral energy of three Korean numbers produced by ten female students from narrow-band spectrograms at 19 proportional time points of each voiced segment. Then, cells of the first five spectral matrices were averaged to form a matrix model for each speaker. The correlation coefficients and sum of the absolute amplitude difference in each pair of the spectral models of the ten subjects were obtained. Also, some individual matrix models were compared to those of the same subject or the other subject with a similar spectral model. Results showed that in numbers '2' and '9' subjects could not be clearly distinguished from the others but in number '4' it shed some possibility of setting threshold values for speaker identification if we employed the coefficients and the sum of absolute difference. Further studies would be desirable on various combinations of the range of long-term average spectra and the degree of signal pre-emphasis.

• Journal of Advanced Marine Engineering and Technology
• /
• v.39 no.9
• /
• pp.903-910
• /
• 2015

The purpose of this research is to develop a full-spectral fatigue analysis program, based on rigid-body ship motion analysis, in order to perform a full-spectral fatigue analysis that considers hydroelasticity effects. To gain credibility, fatigue analysis results of two ship types, performed by the developed program, were compared with those of a classification society, and it was found that both are identical. Full-spectral fatigue analysis considering hydroelasticity effects would be developed in further studies by including flexible-body ship motion analysis results and by supplementing the developed program with a wide-band fatigue damage model.

• Korean Journal of Geomatics
• /
• v.5 no.1
• /
• pp.27-34
• /
• 2005

Unsupervised classification is an important area of research in image processing because supervised classification has the disadvantages such as long task-training time and high cost and low objectivity in training information. This paper focuses on unsupervised classification, which can extract ground object information with the minimum 'Spectral Angle Distance' operation on be behalf of 'Spectral Euclidian Distance' in the clustering process. Unlike previous studies, our algorithm uses the unit vector, not the spectral distance, to compute the cluster mean, and the Single-Pass algorithm automatically determines the seed points. Atmospheric correction for more accurate results was adapted on the Hyperion data and the results were analyzed. We applied the algorithm to the Hyperion and ETM+ data and compared the results with K-Means and the former USAM algorithm. From the result, USAM classified the water and dark forest area well and gave more accurate results than K-Means, so we believe that the 'Spectral Angle' can be one of the most accurate classifiers of not only multispectral images but hyperspectral images. And also the unit vector can be an efficient technique for characterizing the Remote Sensing data.

• The Bulletin of The Korean Astronomical Society
• /
• v.41 no.1
• /
• pp.56.1-56.1
• /
• 2016

Surface mineralogy of asteroids are inferred from photometric and spectroscopic observations with the wide range of wavelengths spanning from far-ultraviolet to mid-infrared. We classify mineralogy of those objects based on their spectral absorption features and spectral slopes. Based on overall spectral shapes, mineralogical classes are divided into three broad complexes; silicates (S), carbonaceous (C) and Vestoids (V), and the end-members that do not fit within the S, C and V broad-complexes. Each of them is subdivided into individual classes. Spectral classification of asteroidal objects has been simply represented by a combination of photometric colors. For a decade, photometric data of asteroids have been grouped and classified according to their SDSS colors converted from the spectral taxonomy. However, systematic studies for asteroid taxonomy based on Johnson-Cousins filters is few, and were conducted only with a small number of objects. In this paper, we present our preliminary results for taxonomic classification of Main Belt asteroids based on KMTNet Johnson-Cousins photometric color system.

• Phonetics and Speech Sciences
• /
• v.11 no.3
• /
• pp.23-29
• /
• 2019

This study acoustically examines the quality of fricatives produced by ten dysarthric speakers with cerebral palsy. Previous similar studies tend to focus only on sibilants, but to obtain a better understanding of how dysarthria affects fricatives we selected a range of samples with different places of articulation and voicing. The Universal Access (UA) Speech database was used to select thirteen words beginning with one of the English fricatives (/f/, /v/, /s/, /z/, /ʃ/, /ð/). The following four measurements were taken for both dysarthric and healthy speakers: phoneme duration, mean spectral peak, variance and skewness. Results show that even speakers with mild dysarthria have significantly longer fricatives and a lower mean spectral peak than healthy speakers. Furthermore, mean spectral peak and variance showed significant group effects for both healthy and dysarthric speakers. Mean spectral peak and variance was also useful for discriminating several places of articulation for both groups. Lastly, spectral measurements displayed important group differences when taking severity into account. These findings show that in general there is a degradation in the production of fricatives for dysarthric speakers, but difference will depend on the severity of dysarthria along with the type of measurement taken.

• Journal of information and communication convergence engineering
• /
• v.21 no.3
• /
• pp.208-215
• /
• 2023

Deep learning techniques provide powerful solutions to several pattern-recognition problems, including Raman spectral classification. However, these networks require large amounts of labeled data to perform well. Labeled data, which are typically obtained in a laboratory, can potentially be alleviated by data augmentation. This study investigated various data augmentation techniques and applied multiple deep learning methods to Raman spectral classification. Raman spectra yield fingerprint-like information about chemical compositions, but are prone to noise when the particles of the material are small. Five augmentation models were investigated to build robust deep learning classifiers: weighted sums of spectral signals, imitated chemical backgrounds, extended multiplicative signal augmentation, and generated Gaussian and Poisson-distributed noise. We compared the performance of nine state-of-the-art convolutional neural networks with all the augmentation techniques. The LeNet5 models with background noise augmentation yielded the highest accuracy when tested on real-world Raman spectral classification at 88.33% accuracy. A class activation map of the model was generated to provide a qualitative observation of the results.

• Earthquakes and Structures
• /
• v.25 no.5
• /
• pp.325-342
• /
• 2023

The damping modification factor (DMF) is used to modify the 5%-damped response spectrum to produce spectral values that correspond to other necessary damping ratios for seismic design. The DMF has been the subject of numerous studies, and it has been discovered that seismological parameters like magnitude and distance can have an impact on it. However, DMF formulations incorporating these seismological parameters cannot be directly applied to seismic design because these parameters are not specified in the present seismic codes. The goal of this study is to develop a formulation for the DMF that can be directly applied in seismic design and that takes the effects of magnitude, distance, and site conditions into account. To achieve this goal, 16660 ground motions with magnitudes ranging from 4 to 9 and epicentral distances ranging from 10 to 200 km are used to systematically study the effects of magnitude, distance, and site conditions on the DMF. Furthermore, according to the knowledge that magnitude and distance affect the DMF primarily by changing the spectral shape, a spectral shape factor is adopted to reflect influences of magnitude and distance, and a new formulation for the DMF incorporating the spectral shape factor is developed. In comparison to the current formulations, the proposed formulation provides a more accurate prediction of the DMF and can be employed directly in seismic design.

• Phonetics and Speech Sciences
• /
• v.13 no.1
• /
• pp.37-44
• /
• 2021

While recent acoustic studies have reported associations of fronted sibilants (fricatives /s s⁎/ and affricates /tɕ tɕ⁎/) with gender in Seoul Korean, there have not been any studies examining the relationship of the variants with adult speakers' ages. The current study analyzes sibilant productions from 39 adult speakers born between 1942 and 2008 (19 females) in terms of spectral peak frequencies (SPFs) in frication, an acoustic index of place of articulation (POA). The results indicate some phonetic contexts where higher sibilant SPFs, i.e., fronter POAs, are associated with younger adults and those fronted variants are realized in a gender-differentiated manner -- tense affricates and word-initial tense fricatives before /i/ in the females' productions, and word-medial tense fricatives before /a/ in the males' productions. The findings confirm that the distributions of the fronted sibilants are accounted for not only by the speakers' gender but also by their ages, indicating that the fronted variants are innovative forms of realizing sibilants in Seoul Korean. In addition, the current results convincingly show that the fronted sibilant variants are not mere reflections of individuals' physiological differences since they are not observed across all of the examined phonetic contexts.