• Korean Journal of Remote Sensing
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• v.33 no.6_2
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• pp.1061-1073
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• 2017

In this study, images were classified using convolutional neural network (CNN) - a deep learning technique - to investigate the feasibility of information production through a combination of artificial intelligence and spatial data. CNN determines kernel attributes based on a classification criterion and extracts information from feature maps to classify each pixel. In this study, a CNN network was constructed to classify materials with similar spectral characteristics and attribute information; this is difficult to achieve by conventional image processing techniques. A Compact Airborne Spectrographic Imager(CASI) and an Airborne Imaging Spectrometer for Application (AISA) were used on the following three study sites to test this method: Site 1, Site 2, and Site 3. Site 1 and Site 2 were agricultural lands covered in various crops,such as potato, onion, and rice. Site 3 included different buildings,such as single and joint residential facilities. Results indicated that the classification of crop species at Site 1 and Site 2 using this method yielded accuracies of 96% and 99%, respectively. At Site 3, the designation of buildings according to their purpose yielded an accuracy of 96%. Using a combination of existing land cover maps and spatial data, we propose a thematic environmental map that provides seasonal crop types and facilitates the creation of a land cover map.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.462-466
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• 2006

Close-to-nature stream evaluation is one of the processing to make the streams over in order to keep them natural. It is integral to evaluate and make an accurate analysis of them on the purpose of maintaining streams healthy. For many instances, there are, stream organization evaluation for restoration by German government, evaluation for ecosystem protection in natural preserves by New Zealand government, and stream-view evaluation for restoration by Britain government so on. In case of the country there are analysis and evaluation of stream physical organization by Cho, Yong-hyun, Close-to-nature stream evaluation for restoration by Kim, Dong-chan, evaluation of stream properties in korea by Park, Bong-jin. Close-to-nature evaluation by Lim, Chan-uk, that is advanced version of Park, Bong-jin's, shows form of stream including waterway curve, sand bar, diversity of flow, river bed material, diversity of minor bed, minor bed bank protection works, bank protection material. It also does environment of stream including side of minor bed vegetation, width of surface of the water/width of the river etc.. By the way, this evaluation does not have free access to apply those details above in the field, it often happens that you get various outcome from the one spot. so you must need more realistic testing method to obtain more accurate data. Remote sensing method is highly recommended because this is very useful for collecting realistic data of vegetation index. what is more, it can not only scan even the minimum area within its resolving power but also do obtain data anytime. Vegetation index indicates Ratio vegetation index, Normalized difference vegetation index, Soil adjusted vegetation index, Atmospherically resistant vegetation index etc.. The research is focusing on Cheokgwa stream which is the branch of Taehwa river and shows 19 sectioned Close-to-nature stream performed according to the method by Lim, chan-uk. Besides let you know vegetation index came from image data of satellite landsat 7 with the variation of buffering area, of the day 9. may. 2003. Of all, the outcome 0.758 at 200m buffer-zone of NDVI was the best we have got so far.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1522-1522
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• 2001

Beverages based on fruit juices are among the most popular commercially available drinks. There is an ever-increasing demand for these juices in the market. Orange juice is one of the most common as well as most favorite flavor. The fruit processing industries have a tremendous responsibility of quality control. For quality evaluation estimation of various components of the juice is necessary. Sucrose, glucose, fructose, citric acid and malic acid are the prime components of orange juice. Little information is available on analysis of orange juice. However, conventional and general wet chemistry procedures are currently being used which are no longer desired by the industry owing to the time involved, labor input and harmful chemicals required for each analysis. Need to replace these techniques with new, highly specific and automated sophisticated techniques viz. HPLC and spectroscopy has been realized since long time. Potential of Near Infrared Spectroscopy in quantitative analysis of different components of food samples has also been well established. A rapid, non-destructive and accurate technique based on Near Infrared Spectroscopy for determination of sugars and organic acids in orange juice will be highly useful. The current study is an investigation into the potential of Near Infrared Diffuse Reflectance Spectroscopy for rapid quantitative analysis of sucrose, glucose, fructose citric acid and malic acid in orange juice. All the Near Infrared measurements were peformed on a dispersive NIR spectrophotometer (ELICO 153) in diffuse reflectance mode. The spectral region from 1100 to 2500nm has been explored. The calibration has been performed on synthetic samples that are mixtures of sucrose, glucose, fructose, citric acid and malic acid in different concentration ranges typically encountered real orange juice. These synthetic samples are therefore considered to be representatives of natural juices. All the Near Infrared spectra of synthetic samples were subjected to mathematical analysis using Partial Least Square (PLS) algorithm. After the validation, calibration was applied to commercially available real samples and freshly squeezed natural juice samples. The actual concentrations were compared with those predicted from calibration curve. A good correlation is obtained between actual and predicted values as indicated by correlation coefficient ($R^2$) value, which is close to unity, showing the feasibility of the technique.

• Journal of Astronomy and Space Sciences
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• v.26 no.4
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• pp.567-588
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• 2009

Korea-Japan Joint VLBI Correlator (KJJVC) is being developed by collaborating KASI (Korea Astronomy and Space Science Institute), Korea, and NAOJ(National Observatory of Japan), Japan. In early 2010, KJJVC will work in normal operation. In this study, we developed the software correlator which is based on VCS (VLBI Correlation Subsystem) hardware specification as the core component of KJJVC. The main specification of software correlator is 8 Gbps, 8192 output channels, and 262,144-points FFT (Fast Fourier Transform) function same as VCS. And the functional algorithm which is same as specification of VCS and arithmetic register are adopted in this software correlator. To verify the performance of developed software correlator, the correlation experiments were carried out using the spectral line and continuum sources which were observed by VERA (VLBI Exploration of Radio Astrometry), NAOJ. And the experimental results were compared to the output of Mitaka FX correlator by referring spectrum shape, phase rate, and fringe detection and so on. Through the experimental results, we confirmed that the correlation results of software correlator are the same as Mitaka FX correlator and verified the effectiveness of it. In future, we expect that the developed software correlator will be the possible software correlator of KVN (Korean VLBI Network) with KJJVC by introducing the correlation post-processing and modifying the user interface as like GUI (Graphic User Interface).

• Geophysics and Geophysical Exploration
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• v.19 no.1
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• pp.11-19
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• 2016

Two representative residual static methods of traveltime decomposition and stack-power maximization are discussed in terms of application to land seismic data. For the model data with synthetic shot/receiver statics (time shift) applied and random noises added, continuities of reflection event are much improved by stack-power maximization method, resulting the derived time-shifts approximately equal to the synthetic statics. Optimal parameters (maximum allowable shift, correlation window, iteration number) for residual statics are effectively chosen with diagnostic displays of CSP (common shot point) stack and CRP (common receiver point) stack as well as CMP gather. In addition to removal of long-wavelength time shift by refraction statics, prior to residual statics, processing steps of f-k filter, predictive deconvolution and time variant spectral whitening are employed to attenuate noises and thereby to minimize the error during the correlation process. The reflectors including horizontal layer of reservoir are more clearly shown in the variable-density section through repicking the velocities after residual statics and inverse NMO correction.

• Korean Journal of Soil Science and Fertilizer
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• v.37 no.4
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• pp.259-265
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• 2004

A quicker method was developed for foliar analysis in diagnosis of nitrogen in apple trees based on multivariate calibration procedure using partial least squares regression (PLSR) and principal component regression (PCR) to establish the relationship between reflectance spectra in the near infrared region and nitrogen content of fresh- and dry-leaf. Several spectral pre-processing methods such as smoothing, mean normalization, multiplicative scatter correction (MSC) and derivatives were used to improve the robustness and performance of the calibration models. Norris first derivative with a seven point segment and a gap of six points on MSC gave the best result of partial least squares-1 PLS-1) model for dry-leaf samples with root mean square error of prediction (RMSEP) equal to $0.699g\;kg^{-1}$, and that the Savitzky-Golay first derivate with a seven point convolution and a quadratic polynomial on MSC gave the best results of PLS-1 model for fresh-samples with RMSEP of $1.202g\;kg^{-1}$. The best PCR model was obtained with Savitzky-Golay first derivative using a seven point convolution and a quadratic polynomial on mean normalization for dry leaf samples with RMSEP of $0.553g\;kg^{-1}$, and obtained with the Savitzky-Golay first derivate using a seven point convolution and a quadratic polynomial for fresh samples with RMSEP of $1.047g\;kg^{-1}$. The results indicate that nitrogen can be determined by the near infrared reflectance (NIR) technology for fresh- and dry-leaf of apple.

• Korean Journal of Remote Sensing
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• v.35 no.6_4
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• pp.1327-1339
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• 2019

Surface reflectance obtained by absolute atmospheric correction from satellite images is useful for scientific land applications and analysis ready data (ARD). For Landsat and Sentinel-2 images, many types of radiometric processing methods have been developed, and these images are supported by most commercial and open-source software. However, in the case of KOMPSAT 3/3A images, there are currently no tools or open source resources for obtaining the reflectance at the top-of-atmosphere (TOA) and top-of-canopy (TOC). In this study, the atmospheric correction module of KOMPSAT 3/3A images is newly implemented to the optical calibration algorithm supported in the Orfeo ToolBox (OTB), a remote sensing open-source tool. This module contains the sensor model and spectral response data of KOMPSAT 3A. Aerosol measurement properties, such as AERONET data, can be used to generate TOC reflectance image. Using this module, an experiment was conducted, and the reflection products for TOA and TOC with and without AERONET data were obtained. This approach can be used for building the ARD database for surface reflection by absolute atmospheric correction derived from KOMPSAT 3/3A satellite images.

• Geophysics and Geophysical Exploration
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• v.22 no.4
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• pp.210-224
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• 2019

Surface wave (SW) surveys, which have been applied to numerous application fields ranging from micro-scale ultrasonic analysis to geological scale analysis, are widely used to monitor near-surface stability. The survey method is basically made through analysis on dispersion of SW propagating along the earth surface, in order to delineate shear velocity structure of subsurface. SW survey data are inverted with assuming one-dimensional (1D) layered-earth in order to recover shear wave velocities of each layer, after being analyzed to make the dispersion curve that shows phase velocity of SW with respect to frequency. This study reviews surface wave surveys with explaining the basic theory including the characteristics of dispersion and the procedure of general data processing. Even though surface wave surveys can be categorized into active and passive methods, this paper focuses only on active surface wave methods which includes continuous SW (CSW), spectral analysis of SW (SASW) and multichannel analysis of SW (MASW). Passive method will be reviewed in the subsequent paper.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.5
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• pp.544-555
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• 2002

The aim of this study is to develop the $^1H$-MRS data postprocessing software for both single-voxel and multi-voxel technique, which plays and important role as a diagnostic tool in clinical field. This software is based on graphical user interface(GUI) under windows operating system of personal computer(PC). In case of single-voxel MRS, both of raw data in time-domain and spectrum data in frequency-domain are simultaneously displayed in a screen. Several functions such as DC correction, zero filling, line broadening, Lorentz-Gauss filtering and phase correction, etc. are included to increase the quality of spectrum data. In case of multi-voxel analysis, spectroscopic image reconstructed by 3-D FFT was displayed as a spectral grid and overlapped over previously obtained T1- or T2-weighted image for the spectra to be spatially registered with the image. The analysis of MRS peaks were performed by obtaining the ratio of peak area. In single-voxel method, statistically processed peak-area ratios of MRS data obtained from normal human brain are presented. Using multi-voxel method, MR spectroscopic image and metabolite image acquired from brain tumor are demonstrated.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.3
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• pp.66-80
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• 2012

It is necessary to normalize spectral image values derived from multi-temporal satellite data to a common scale in order to apply remote sensing methods for change detection, disaster mapping, crop monitoring and etc. There are two main approaches: absolute radiometric normalization and relative radiometric normalization. This study focuses on the multi-temporal satellite image processing by the use of relative radiometric normalization. Three scenes of KOMPSAT-2 imagery were processed using the Multivariate Alteration Detection(MAD) method, which has a particular advantage of selecting PIFs(Pseudo Invariant Features) automatically by canonical correlation analysis. The scenes were then applied to detect disaster areas over Sendai, Japan, which was hit by a tsunami on 11 March 2011. The case study showed that the automatic extraction of changed areas after the tsunami using relatively normalized satellite data via the MAD method was done within a high accuracy level. In addition, the relative normalization of multi-temporal satellite imagery produced better results to rapidly map disaster-affected areas with an increased confidence level.