• Korean Journal of Remote Sensing
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• v.34 no.1
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• pp.89-99
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• 2018

Spatial downscaling is often applied to coarse scale satellite products with high temporal resolution for environmental monitoring at a finer scale. An area-to-point regression kriging (ATPRK) algorithm is regarded as effective in that it combines regression modeling and residual correction with area-to-point kriging. However, an open source tool or package for ATPRK has not yet been developed. This paper describes the development and code organization of an R-based spatial downscaling tool, named R4ATPRK, for the implementation of ATPRK. R4ATPRK was developed using the R language and several R packages. A look-up table search and batch processing for computation of ATP kriging weights are employed to improve computational efficiency. An experiment on spatial downscaling of coarse scale land surface temperature products demonstrated that this tool could generate downscaling results in which overall variations in input coarse scale data were preserved and local details were also well captured. If computational efficiency can be further improved, and the tool is extended to include certain advanced procedures, R4ATPRK would be an effective tool for spatial downscaling of coarse scale satellite products.

• Journal of Korean Society for Atmospheric Environment
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• v.22 no.3
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• pp.383-391
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• 2006

In Korea, the major source of serious air pollution is motor vehicles. Air pollution from vehicles has been annually increased. Then the government will try to control the vehicle emission by applying the effective emission management policy for the manufactured and in-used car. It is necessary to correctly calculate the emission factor for successful propulsion of the vehicle emission control policy. In this study, correlation analysis of exhaust emissions from vehicles between CVS-75 mode and Korea mode was conducted. A total of 25 light-duty buses were tested on the chassis dynamometer system in order to measure CO, HC, NOx PM and fuel efficiency (F.E.). For the test modes, 10 different Korea modes and CVS-75 mode were used. As the result of correlation analysis between those modes, most of the correlation coefficients were higher than 0.90. On the basis of high correlation between those modes, correction factors by driving conditions were estimated. Through the results of this study, we obtained essential basic data to correct difference from those modes.

• Journal of KIBIM
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• v.10 no.4
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• pp.89-97
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• 2020

The purpose of this study is to identify the problems of the currently used 3D spatial information utilization system to realize a more accurate landscape and to establish a user-oriented environment to improve the utilization plan for future landscape evaluation. As citizens' interest in urban landscapes with strong public characteristics increases and the speed of urban development also increases, more suitable simulation methods for landscape management are required. Nevertheless, there are many cases of inconvenient correction according to development changes along with many errors in various steps for creating landscape simulation. Therefore, in performing landscape deliberation according to development, it is necessary to create more accurate and efficient landscape simulation, and if changes occur after the initial deliberation, a process that can quickly and conveniently correct and supplement data is needed. In addition, it is necessary to create landscape simulation so that the created modeling source can be used by being compatible with other application programs. In this study, a method of constructing a more accurate and efficient simulation at the time of initial deliberation and a method of creating a landscape simulation model for rapid response to a plan that is changed at the time of re-deliberation are described.

• Nuclear Engineering and Technology
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• v.56 no.1
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• pp.56-63
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• 2024

In high radiation fields, gamma cameras suffer from pulse pile-up, resulting in poor energy resolution, count losses, and image distortion. To overcome this problem, various methods have been introduced to reduce the size of the aperture or pixel, reject the pile-up events, and correct the pile-up events, but these technologies have limitations in terms of mechanical design and real-time processing. The purpose of this study is to develop a real-time gamma camera to evaluate the radioactive contamination in high radiation fields. The gamma camera is composed of a pinhole collimator, NaI(Tl) scintillator, position sensitive photomultiplier (PSPMT), signal processing board, and data acquisition (DAQ). The pulse pile-up is corrected in real-time with a field programmable gate array (FPGA) using the start time correction (STC) method. The STC method corrects the amplitude of the pile-up event by correcting the time at the start point of the pile-up event. The performance of the gamma camera was evaluated using a high dose rate ¹³⁷Cs source. For pulse pile-up ratios (PPRs) of 0.45 and 0.30, the energy resolution improved by 61.5 and 20.3%, respectively. In addition, the image artifacts in the ¹³⁷Cs radioisotope image due to pile-up were reduced.

• Journal of the Korean Society for information Management
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• v.26 no.3
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• pp.213-237
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• 2009

Local culture is a cultural heritage that has come down from generation to generation in the natural environment of a region. It includes history, tradition, natural features, art, and historic relics. The Academy of Korean Studies has complied "The Encyclopedia of Korean Local Culture" using those local culture contents. Local culture content shave the features of documentary, such as authenticating the source, and managing hierarchy structure. Thus, to deal with local culture contents, a "circular knowledge information management system" is sought for that helps basic, fragmentary, and high-level information to circulate to create new knowledge information within the system. A user of this circular knowledge information management system is able not only to collect data directly in it, but also to fetch data from other database. Besides, processing the collected data helps to create new knowledge information. But, it's very difficult to sustain the features of the original hierarchy bearing meaning contained in the various kinds of local culture contents when building a new database. Moreover, this kind of work needs many times of correction over a long period of time. Therefore, a system in which compilation, correction, and service can be done simultaneously is needed. Therefore, in this study, focusing on the case of "The Encyclopedia of Korean Local Culture", I propose a XML-based digital compilation management system that can express hierarchy information and sustain the semantic features of the local culture contents containing lots of ancient documents, and introduce the expanded functions developed to manage contents in the system.

• Geophysics and Geophysical Exploration
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• v.17 no.3
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• pp.137-146
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• 2014

This study presents a procedure for discrimination of artificial events from earthquakes occurred in and around the Korean Peninsula using data set in the Wonju KSRS seismograph network, Korea. Two training sets representing natural and artificial earthquakes were constructed with 150 and 56 events, respectively, with high signal to noise ratio. A frequency band, Pg(4-6 Hz)/Lg(5-7 Hz), which is optimal for the discrimination of seismic sources was derived from the two-dimensional grid of Pg/Lg spectral amplitude ratio. The corrections for the effects of earthquake magnitude and hypocentral distance were carried out for improvement of discrimination capability. For correcting the effect of magnitude dependence due to the inverse proportionality of corner frequency to seismic moment, the Brune's source spectrum was subtracted from the observation spectrum. The spectrum was corrected using the optimal damping coefficient to remove damping effect with the hypocentral distance. The effect of locally varying spectrum ratio was cancelled correcting variation of wave propagation along the ray path. The performance in discrimination between training sets of natural and artificial events was compared using the Mahalanobis distance in each step of correction. The procedure of magnitude, distance, and path corrections show clear improvements of the discrimination results with increasing Mahalanobis distance, from 1.98 to 3.01, between two training sets.

• Geophysics and Geophysical Exploration
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• v.12 no.3
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• pp.225-232
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• 2009

As part of seismic experiments investigating crustal velocity structures of the Korean peninsula, permanent (fixed) seismographs of the Korea Meteorological Administration (KMA) network recorded seismic signals from four and eight large explosions in Korean Crustal Research Team (KCRT) profiles shot in 2004 and 2008, respectively. Among the seismograms recorded by 43 velocity sensors and 103 accelerometers at KMA stations distributed throughout the southern Korean Peninsula, 156 records with epicentral distances less than 120 km and high signal-to-noise ratios were analyzed to determine velocity anisotropy of the Pg phase. Relative elevation corrections of -101.6 to 105.3 ms were made using velocity information derived from the 2004 KCRT profile data and differences in elevation between the permanent KMA stations and the temporary stations in the KCRT profiles at the same source-receiver offsets. To remove site effects, receiver-station corrections of -89.6 to 192.2 ms were additionally made to the KMA station data by subtracting the average differences in traveltimes between KMA stations and portable stations at the same offsets for all available shots with different azimuths. With the exception of anomalously fast velocities along trends of the Chugaryeong fault zone and the Okchon fold belt and anomalously slow velocities in the regions of high terrestrial heat near Yeongduk and Ulsan, the analysis of crustal velocity anisotropy using the Pg phase indicates overall isotropy in the southern half of the Korean peninsula.

• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.39-55
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• 2019

In this study, we have proposed an improved method to detect forest fires by correcting the reflected signals of day images using the middle-wavelength infrared (MWIR) channel. The proposed method is allowed to remove the reflected signals only using the image itself without an existing data source such as a land-cover map or atmospheric data. It includes the processing steps for calculating a solar-reflected signal such as 1) a simple correction model of the atmospheric transmittance for the MWIR channel and 2) calculating the image-based reflectance. We tested the performance of the method using the MODIS product. When compared to the conventional MODIS fire detection algorithm (MOD14 collection 6), the total number of detected fires was improved by approximately 17%. Most of all, the detection of fires improved by approximately 30% in the high reflection areas of the images. Moreover, the false alarm caused by artificial objects was clearly reduced and a confidence level analysis of the undetected fires showed that the proposed method had much better performance. The proposed method would be applicable to most satellite sensors with MWIR and thermal infrared channels. Especially for geostationary satellites such as GOES-R, HIMAWARI-8/9 and GeoKompsat-2A, the short acquisition time would greatly improve the performance of the proposed fire detection algorithm because reflected signals in the geostationary satellite images frequently vary according to solar zenith angle.

• Korean Journal of Remote Sensing
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• v.21 no.4
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• pp.341-369
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• 2005

Hyperspectral images have emerged as a new and promising remote sensing data that can overcome the limitations of existing optical image data. This study was designed to provide a comprehensive review on definition, data processing methods, and applications of hyperspectral data. Various types of airborne, spaceborne, and field hyperspectral image sensors were surveyed from the available literatures and internet search. To understand the current status of hyperspectral remote sensing technology and research development, we collected several hundreds research papers from international journals (IEEE Transactions on Geoscience and Remote Sensing, International Journal of Remote Sensing, Remote Sensing of Environment and AVIRIS Workshop Proceedings), and categorized them by sensor types, data processing techniques, and applications. Although several hyperspectral sensors have been developing, AVIRIS has been a primary data source that the most hyperspectral remote sensing researches were relied on. Since hyperspectral data have very large data volume with many spectral bands, several data processing techniques that are particularly oriented to hyperspectral data have been developed. Although atmospheric correction, spectral mixture analysis, and spectral feature extraction are among those processing techniques, they are still in experimental stage and need further refinement until the fully operational adaptation. Geology and mineral exploration were major application in early stage of hyperspectral sensing because of the distinct spectral features of rock and minerals that could be easily observed with hyperspectral data. The applications of hyperspectral sensing have been expanding to vegetation, water resources, and military areas where the multispectral sensing was not very effective to extract necessary information.

• Geophysics and Geophysical Exploration
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• v.25 no.1
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• pp.26-37
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• 2022

Recently, multiple methods using small aircraft for geophysical exploration have been suggested as a result of the development of information and communication technology. In this study, we introduce the hybrid unmanned aircraft electromagnetic system of the Korea Institute of Geosciences and Mineral resources, which is under development. Additionally, data processing and interpretation methods are suggested via the analysis of datasets obtained using the system under development to verify the system. Because the system uses a three-component receiver hanging from a drone, the effects of rotation on the obtained data are significant and were therefore corrected using a rotation matrix. During the survey, the heights of the source and the receiver and their offsets vary in real time and the measured data are contaminated with noise. The noise makes it difficult to interpret the data using the conventional method. Therefore, we developed a recurrent neural network (RNN) model to enable rapid predictions of the apparent resistivity using magnetic field data. Field data noise is included in the training datasets of the RNN model to improve its performance on noise-contaminated field data. Compared with the results of the electrical resistivity survey, the trained RNN model predicted similar apparent resistivities for the test field dataset.