• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1591-1604
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• 2020

This study is a study on classifying land cover by applying high-resolution satellite images to deep learning algorithms and verifying the performance of algorithms for each spatial object. For this, the Fully Convolutional Network-based algorithm was selected, and a dataset was constructed using Kompasat-3 satellite images, land cover maps, and forest maps. By applying the constructed data set to the algorithm, each optimal hyperparameter was calculated. Final classification was performed after hyperparameter optimization, and the overall accuracy of DeeplabV3+ was calculated the highest at 81.7%. However, when looking at the accuracy of each category, SegNet showed the best performance in roads and buildings, and U-Net showed the highest accuracy in hardwood trees and discussion items. In the case of Deeplab V3+, it performed better than the other two models in fields, facility cultivation, and grassland. Through the results, the limitations of applying one algorithm for land cover classification were confirmed, and if an appropriate algorithm for each spatial object is applied in the future, it is expected that high quality land cover classification results can be produced.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1339-1348
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• 2020

Phytoplankton controls marine ecosystems in terms of nutrients, photosynthetic rate, carbon cycle, etc. and the degree of its influence on the marine environment depends on their physical size. Many studies have been attempted to identify marine phytoplankton size classes using the remote sensing techniques. One of successful approach was the three-component model which estimates the chlorophyll concentrations of three phytoplankton size classes (micro-phytoplankton; >20 ㎛, nano-; 2-20 ㎛ and pico-; <2 ㎛) as a function of total chlorophyll. Here, we examined the applicability of Geostationary Ocean Colour Imager (GOCI) to the mapping of the phytoplankton size class distribution in the East Sea. A fit of the three-component model to a biomarker pigment dataset collected in the study area for some years including a large harmful algal bloom period has been carried out to derive size-fractioned chlorophyll concentration (CHL). The tuned three-component model was applied to the hourly GOCI images to identify the fractions of each phytoplankton size class for the entire CHL. Then, we investigated the distribution of phytoplankton community in terms of the size structure in the East Sea during the harmful Cochlodinium polykrikoides blooms in the summer of 2013.

• Journal of the Korean Geophysical Society
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• v.9 no.2
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• pp.129-134
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• 2006

Recently, spillways are need to control stable water level for supporting main dams because of floods by unusual change of weather such as Typhoon Rusa. This study has been focused on the amount of leakage through the rock mass distributed fractures and joints under the opened emergency spillway. It is very important to evaluate the amount of leakage as these affect stability of spillway by interaction between effective stress and pore pressure. The commercial program MAFIC has been used for analyzing groundwater flow in fractured rock mass. The results showed that the values of range, average and deviation of leakage were 2.85∼3.79×10-1, 3.32×10-1 and 1.70×10-2 m3/day/m2 respectively. Secondary, we have estimated the effect of grouting after the transmissivity(Tf) of joint 1 as main pathway of leakage known from above results was changed from 1.78×10-7 to 1.59×10-9 m2/s. The results showed that the values of range, average and deviation of leakage were 7.80×10-4∼1.53×10-3, 1.18×10-3 and 1.32×10-4 m3/day/m2 respectively. As the result, the amount of leakage after grouting has been decreased by a ratio of 1 to 277.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.493-502
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• 2021

Recently, because of changes in temperature and rising water temperatures due to increased pollution sources, many algae have been produced in the water system. Therefore, there has been a lot of research using satellite images for the generation and monitoring of green algae. However, in prior studies, it is difficult to consider the optical properties of the local water system by using only a single index, and by using medium and low-resolution satellite images to conduct large-scale algae detection, there is a problem of accuracy in narrow, broad rivers. Therefore, in this work, we utilize high-resolution images of Sentinel-2 satellites to perform green algae detection on a single index (NDVI, SEI, FGAI) and development index (NDVI & SEI, FGAI & SEI) that mixes single indices. In this study, POD, FAR, and PC values were utilized to evaluate the accuracy of green algae detection algorithms, and the FGAI & SEI index showed the highest accuracy with 98.29% overall accuracy PC.

• The Bulletin of The Korean Astronomical Society
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• v.35 no.1
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• pp.46.1-46.1
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• 2010

APT(Asian-Pacific Telecommunity)는 아시아-태평양지역 국가의 공동이익을 도모하기 위하여 결성된 아-태지역 전파협의체 조직으로, WRC(세계전파통신회의)회의에서의 아-태지역 주관청의 공동이익을 얻기 위해 APG(APT Conference Preparatory Group for WRC)회의를 연간 1회의 비율로 개최하고 있다. WRC-12회의에 대비하여 결성된 APG-12 회의가 2010년 3월 태국 방콕에서 개최되었으며, 전파천문업무 보호 및 22 GHz 대역 달탐사, 38 GHz 대역 Space-VLBI운용대역과 관련된 WRC-12 의제 1.6, 1.11, 1.12 등에 대해 활발한 토론이 있었다. WRC-12 의제 1.6은 수동업무(전파천문업무, 지구탐사위성 및 우주연구업무)를 능동업무의 유해혼신으로부터 보호하기 위하여 제정한 전파규칙 각주 5.565조의 개정 검토와 관련된 의제이다. 따라서 한국천문연구원에서는 275 GHz 이상 대역에서의 전파천문업무의 원활한 운용을 위해, WRC회의에서 최종적인 규정개정을 함에 있어서 필요한 아-태지역 국가의 공동의견을 창출하기 위한 APT회의에서 주도적인 역할을 담당하고 있다. 본 발표에서는 APG-12 3차 회의에 제출한 우리나라의 기고서 제출 결과 및 동 회의에서의 최종결과 및 향후 대응책에 대해서도 알아보고자 한다.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.134.1-134.1
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• 2011

APT(Asian-Pacific Telecommunity)는 아시아-태평양지역 국가의 공동이익을 도모하기 위하여 결성된 아-태지역 전파협의체 조직으로, WRC(세계전파통신회의)회의에서의 아-태 지역 주관청의 공동이익을 얻기 위해 APG(APT Conference Preparatory Group for WRC)회의를 연간 1회의 비율로 개최하고 있다. 2012년의 WRC-12회의에 대비하여 아태지역 회원국의 최종 공동의견서를 작성하기 위해, APG-12 5차회의가 2011년 8월 29일-9월 3일 부산에서 개최되었으며, 전파천문업무 보호 및 22 GHz 대역 달탐사, 38 GHz 대역 Space-VLBI운용대역과 관련된 WRC-12 의제 1.6, 1.11, 1.12 등에 대한 회의가 있었다. WRC-12 의제 1.6은 수동업무(전파천문업무, 지구탐사위성 및 우주연구업무)를 능동업무의 유해혼신으로부터 보호하기 위하여 제정한 전파규칙 각주 5.565조의 개정 검토와 관련된 의제이다. 따라서 한국천문연구원에서는 275 GHz 이상 대역에서 전파천문업무의 원활한 운용을 위해, APG-12 5차회의에 참석하여 WRC-12회의에 제출하기 위한 아-태지역 국가의 공동의견서 작성에 주도적인 역할을 담당하였다. 본 발표에서는 APG-12 5차 회의에 제안한 우리나라의 기고서 제안 내용 및 동 회의에서 의 최종 아태지역 회원국 공동의견서 결과 및 향후 대응책에 대해서도 알아보고자 한다.

• Korean Journal of Remote Sensing
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• v.29 no.2
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• pp.161-172
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• 2013

The construction of hyperspectral test-bed dataset is essential for the effective performance of hyperspectral image for various applications. In this study, we analyzed the technical points for generating of optimal hyperspectral test-bed site for hyperspectral sensors and the efficiency of hyperspectral test-bed site. In this regard regions we analyzed existing construction techniques for generating test-bed site in domestic and foreign, and designed the test-bed site to acquire images from the airborne hyperspectral sensor. To produce a reference data from the image of constructed test-bed site, this study applied vicarious correction as a pre-processing and analyzed its efficiency. The result presented that it was ideal to use tarp for the vicarious correction, but it is possible to use the materials with constant spectral reflectance or with relatively low variance of spectral reflectance. The test-bed data taken in this study can be employed as the reference of domestic and foreign studies for hyperspectral image processing.

• The Journal of Information Systems
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• v.14 no.2
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• pp.277-292
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• 2005

This paper uses a data mining approach to develop bankruptcy prediction models suitable for traditional (off-line) companies and electronic (on-line) companies. It observes the differences in the composition prediction models between these two types of companies and provides interpretation of bankruptcy classifications. The bankruptcy prediction models revealed the major variables in predicting bankruptcy to be 'cash flow to total assets' and 'gross value-added to net sales' for traditional off-line companies while 'cash flow to liabilities','gross value-added to net sales', and 'current ratio' for electronic companies. The accuracy rates of final prediction models for traditional off-line and electronic companies were found to be $84.7\%\;and\;82.4\%$, respectively. When the model for traditional off-line companies was applied for electronic companies, prediction accuracy dropped significantly in the case of bankruptcy classification (from $70.4\%\;to\;45.2\%$) at the level of a blind guess ($41.30\%$). Therefore, the need for different models for traditional off-line and electronic companies is justified.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.851-861
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• 2022

In this study, we analyzed the effects of trees planted in urban areas on PM_2.5 reduction using a computational fluid dynamics (CFD) model. For realistic numerical simulations, the meteorological components(e.g., wind velocity components and air temperatures) predicted by the local data assimilation and prediction system (LDAPS), an operational model of the Korea Meteorological Administration, were used as the initial and boundary conditions of the CFD model. The CFD model was validated against, the PM_2.5 concentrations measured by the sensor networks. To investigate the effects of trees on the PM_2.5 reduction, we conducted the numerical simulations for three configurations of the buildings and trees: i) no tree (NT), ii) trees with only drag effect (TD), and iii) trees with the drag and dry-deposition effects (DD). The results showed that the trees in the target area significantly reduced the PM_2.5 concentrations via the dry-deposition process. The PM_2.5 concentration averaged over the domain in DD was reduced by 5.7 ㎍ m^-3 compared to that in TD.

• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1107-1115
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• 2019

Satellite data play a major role in supporting knowledge about forest fire by delivering rapid information to map areas damaged. This study, we used 7 Sentinel-2A images to detect change area in forests of Sokcho on April 4, 2019. The process of classify forest fire severity used 7 levels from Sentinel-2A dNBR(differenced Normalized Burn Ratio). In the process of classifying forest fire damage areas, the study selected three areas with high regrowth of vegetation level and conducted a detailed spatial analysis of the areas concerned. The results of dNBR analysis, regrowth of coniferous forest was greater than broad-leaf forest, but NDVI showed the lowest level of vegetation. This is the error of dNBR classification of dNBR. The results of dNBR time series, an area of forest fire damage decreased to a large extent between April 20th and May 3rd. This is an example of the regrowth by developing rare-plants and recovering broad-leaf plants vegetation. The results showed that change area was detected through the change detection of danage area by forest category and the classification errors of the coniferous forest were reached through the comparison of NDVI and dNBR. Therefore, the need to improve the precision Korean forest fire damage rating table accompanied by field investigations was suggested during the image classification process through dNBR.