• Journal of Korean Society for Atmospheric Environment
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• v.30 no.2
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• pp.139-149
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• 2014

A new technique, namely the combination of satellite and trajectory analysis (CSTA), for exploring the spatio-temporal distribution information of volcanic ash plume (VAP) from volcanic eruption. CSTA uses the satellite derived ash property data and a matching forward-trajectories, which can generate airmass history pattern for specific VAP. In detail, VAP properties such as ash mask, aerosol optical thickness at 11 ${\mu}m$ ($AOT_{11}$), ash layer height, and effective radius from the Moderate Resolution Imaging Spectro-radiometer (MODIS) satellite were retrieved, and used to estimate the possibility of the ash forecasting in local atmosphere near volcano. The use of CSTA for Iceland's Eyjafjallaj$\ddot{o}$kull volcano erupted in May 2010 reveals remarkable spatial coherence for some VAP source-transport pattern. The CSTA forecasted points of VAP are consistent with the area of MODIS retrieved VAP. The success rate of the 24 hour VAP forecast result was about 77.8% in this study. Finally, the use of CSTA could provide promising results for VAP monitoring and forecasting by satellite observation data and verification with long term measurement dataset.

• Korean Journal of Remote Sensing
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• v.29 no.1
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• pp.21-34
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• 2013

Permanent Scatterer InSAR (PSInSAR) technique extracts permanent scatterers exhibiting high phase stability over the entire observation period and calculates precise time-series deformation at Permanent Scatterer (PS) points by using single master interferograms. This technique is not a good method to apply on nature environment such as forest area where permanent scatterers cannot be identified. Another muti-temporal Interferometric Synthetic Aperture Radar (InSAR), Small BAseline Subset (SBAS) technique using multi master interferograms with short baselines, can be effective to detect deformation in forest area. However, because of the error induced from phase unwrapping, the technique sometimes fails to estimate correct deformation from a stack of interferograms. To overcome those problems, we introduced new multi-temporal InSAR technique, called Temporarily Coherence Point InSAR (TCPInSAR), in this paper. This technique utilizes multi master interferograms with short baseline and without phase unwrapping. To compare with traditional multi-temporal InSAR techniques, we retrieved spatially changing deformation because PSs have been found enough in forest area with TCPInSAR technique and time-series deformation without phase unwrapping error. For this study, we acquired ERS-1 and ERS-2 SAR dataset on Augustine volcano, Alaska and detected deformation in study area for the period 1992-2005 with SBAS and TCPInSAR techniques.

• Journal of the Korean earth science society
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• v.40 no.2
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• pp.177-187
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• 2019

Several volcanic activities have continued in Mt. Baekdu since the Millennium eruption, and these phenomena have increased the need for volcanic activity surveillance. Various geophysical approaches are needed to obtain the depth and size of magma chamber that lie several kilometers below the surface. We examined the applicability of direct-current resistivity survey in this study. In order to explore the deep magma chamber of Mt. Baekdu, which has a spatial limitation due to the borderline, a large-scale survey with a length of tens of kilometers should be conducted. This type of survey requires a distributed measurement system and optimized exploration designs. Therefore, we propose survey designs taking advantage of our developed distributed acquisition system and analyze the applicability using numerical simulation. We confirmed that our designs that use single survey line with offline transmitting points show comparable results to the conventional 3D survey. It is expected that our research result can contribute to the deep geophysical exploration in Mt. Baekdu.

• Korean Journal of Ecology and Environment
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• v.48 no.1
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• pp.68-76
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• 2015

There is no willow riparian vegetation in Jeju Island, Korea. Instead, a genetically-isolated population of Adina rubella is found in some parts of the riparian system. We describe its syntaxonomy and synecology. A total of 27 phytosociological relev$\acute{e}$s were collected, 11 relev$\acute{e}$s from 91 sites and 16 relev$\acute{e}$s from the previously published relevant materials. Data were analyzed by traditional Braun-Blanquet method and multivariate PCoA (Principal coordinates analysis). New syntaxa are distinguished, Adinion rubellae all. nov. and its type association Tripogono-Adinetum rubellae ass. nov. with two subassociations, typicum and rhododendretosum poukhanensae. Adino-Rhododendretum poukhanensae Itow et al. 1993 was discarded owing to mismatch of syntaxonomy and syngeography of Adina and Rhododendron phytocoena. The alliance Adinion is Jeju's regional and partly ombrotrophic vegetation occurring in pothole and rock crevice where are independent on ground-water table. We also suggest a revised alliance, Rhododendrion poukhanensae Lee 2004 ex. hoc loco in Korean peninsula, as a corresponding syntaxon to Adinion, which completely differs from Phragmito-Salicion. Finally we pointed out that Adina phytocoena requiring an absolutely monitoring has been threatened by river maintenance project of local government.

• Journal of Satellite, Information and Communications
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• v.12 no.1
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• pp.6-12
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• 2017

Recently, the demand for SAR imaging is growing to monitor natural disasters or military sites to foresee topographic changes, where optical sensing is not easily available. High-resolution SAR images are useful in exploring topography and monitoring artificial land objects in all weather conditions. In this paper,high resolution SAR images acquired from KOMPSAT-5 are exploited for the applications of change detection and classification. In order to detect change areas, amplitude change detection (ACD) and coherence change detection (CCD) algorithms are employed and their performances are compared in practical applications. For enhanced performance, the potential of small scaled change detection is explored by combining multi-temporary SAR images. The k-means and SVM methods are applied for land classifications and their performances are compared by applying to the real spaceborne SAR images.

• Economic and Environmental Geology
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• v.39 no.4 s.179
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• pp.495-505
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• 2006

Atmospheric infrasound is defined as low frequency inaudible sound waves generated from natural phenomena and human activities. One property of long-distance travelling of infrasound makes it possible to detect the wave propagated from remote sound sources and to understand many geophysical phenomena generating it. Recently, advanced global infrasound sensor arrays are being deployed to monitor the clandestine nuclear test and to study geophysical phenomena in the world. In Korea, five seismo-acoustic arrays consisting of co-located seismometer and micro-barometer have been operated to discriminate the artificial explosions from the natural earthquakes in and around the Korean Peninsula. In addition to the discrimination purpose, these ways also record distinct infrasonic signals from natural phenomena on global scale such as large earthquake, bolide event, volcanic explosion, typhoon, and so on. As a new frontier in monitoring the earth, infrasound is being applied to understand various phenomena in and above the earth's surface.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.267-267
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• 2021

제주도는 화산섬의 지질특성상 강수의 지표침투성이 높아 지표수의 개발이용여건이 취약한 관계로 용수의 대부분을 지하수에 의존하고 있다. 따라서 지하수의 보전관리는 매우 중요한 사항이며 특히 지하수의 안정적인 이용을 위해서는 지하수 취수가 주변지역 지하수위에 미치는 영향 분석이 반드시 필요하다. 본 연구는 딥러닝 알고리즘인 Long Short-Term Memory(LSTM)를 활용하여 제주도 남동쪽 표선유역 중산간지역에 위치한 2개 지하수위 관측정을 대상으로 지하수 취수영향을 분석하였다. 입력자료로써 인근 2개 강우관측소의 일단위 강수량자료와 인근 6개 취수정의 지하수 취수량자료 및 연구대상 관측정의 지하수위 자료(2001. 2. 11. ~ 2019. 10. 31.)를 사용하였다. 지하수위 변동특성을 최대한 반영하기 위해 LSTM의 예측일수를 1일로 설정하였다. 보정 및 검증 기간을 사용하여 매개변수의 과적합을 방지하였으며, 테스트 기간을 사용하여 LSTM의 예측성능을 평가하였다. 평가지수로써 Nash-Sutcliffe Efficiency(NSE)와 평균제곱근오차(RMSE)를 사용하였다. 그리고 지하수 취수가 주변 지하수위 변동에 미치는 영향을 분석하기 위해 취수량을 최대취수량인 2,300 m³/일, 최대취수량의 2/3인 1,533 m³/일 및 0 m³/일로 설정하여 모의하였다. 모의결과, 2개 감시정의 보정, 검증 및 예측기간에 대한 NSE는 최대 0.999, 최소 0.976의 범위를 보였으며, RMSE는 최대 0.494 m, 최소 0.084 m를 보여 LSTM은 우수한 예측성능을 나타내었다. 이것은 LSTM이 지하수위 변동특성을 적절히 학습하였다는 것을 의미하며 따라서 추정된 매개변수를 활용하여 지하수 취수영향을 모의 및 분석하였다. 그 결과, 지하수위 하강량은 최대 0.38 m 였으며 이것은 대상지점에 대한 취수량은 지하수위 하강에 거의 영향을 주지 않는다는 것을 의미한다. 또한 취수량과 지하수위 하강량과의 관계는 한 개 관측정에 대해 선형적인 관계를 보인 반면 나머지 한 개 관측정에 대해서는 비선형적인 관계를 나타내는 것을 확인하였다. 따라서 LSTM 알고리즘을 활용하여 제주도 표선유역 중산간지역의 지하수위 변동특성을 분석할 수 있다.