• Title/Summary/Keyword: earth science data

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Prediction of Landslides and Determination of Its Variable Importance Using AutoML (AutoML을 이용한 산사태 예측 및 변수 중요도 산정)

  • Nam, KoungHoon;Kim, Man-Il;Kwon, Oil;Wang, Fawu;Jeong, Gyo-Cheol
    • The Journal of Engineering Geology
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    • v.30 no.3
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    • pp.315-325
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    • 2020
  • This study was performed to develop a model to predict landslides and determine the variable importance of landslides susceptibility factors based on the probabilistic prediction of landslides occurring on slopes along the road. Field survey data of 30,615 slopes from 2007 to 2020 in Korea were analyzed to develop a landslide prediction model. Of the total 131 variable factors, 17 topographic factors and 114 geological factors (including 89 bedrocks) were used to predict landslides. Automated machine learning (AutoML) was used to classify landslides and non-landslides. The verification results revealed that the best model, an extremely randomized tree (XRT) with excellent predictive performance, yielded 83.977% of prediction rates on test data. As a result of the analysis to determine the variable importance of the landslide susceptibility factors, it was composed of 10 topographic factors and 9 geological factors, which was presented as a percentage for each factor. This model was evaluated probabilistically and quantitatively for the likelihood of landslide occurrence by deriving the ranking of variable importance using only on-site survey data. It is considered that this model can provide a reliable basis for slope safety assessment through field surveys to decision-makers in the future.

Status and Prospect of Unmanned, Global Ocean Observations Network (글로벌 무인해양관측 네트워크 현황과 전망)

  • Nam, Sunghyun;Kim, Yun-Bae;Park, Jong Jin;Chang, Kyung-Il
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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    • v.19 no.3
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    • pp.202-214
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    • 2014
  • We introduce status and prospect of increasingly utilizing, unmanned, global ocean observing systems, and the global network to integrate, coordinate, and manage the systems. Platforms of the ocean observing system are diversified in order to resolve/monitor the variability occurring at multiple scales in both three-dimensional space and time. Here purpose, development history, and current status of the systems in two kinds - mobile (surface drifter, subsurface float, underwater glider) and fixed platforms (surface and subsurface moorings, bottom mounts), are examined and the increased future uses to produce synergies are envisioned. Simultaneous use of various mobile and fixed platforms is suggested to more effectively design the observing system, with an example of the NSF-funded OOI (Ocean Observations Initiative) program. Efforts are suggested 1) to fill the data gap existing in the deep sea and the Southern Ocean, and toward 2) new global network for oceanic boundary currents, 3) new technologies for existing and new sensors including biogeochemical, acoustic, and optical sensors, 3) data standardization, and 4) sensor calibration and data quality control.

Change of Regional Atmospheric Circulation Related with Recent Warming in the Antarctic Peninsula (남극반도의 최근 온난화와 관련된 지역적 대기순환의 변화)

  • Lee, Jeong-Soon;Kwon, Tae-Yong;Lee, Bang-Yong;Yoon, Ho-Il;Kim, Jeong-Woo
    • Ocean and Polar Research
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    • v.25 no.4
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    • pp.503-518
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    • 2003
  • This study examines the relationship among temperature, wind, and sea level pressure to understand recent warming in the vicinity of the Antarctic Peninsula. To do this, the surface air temperature, NCEP/NCAR reanalysis wind data and sea level pressure data for the period of 40 years are analyzed. The 40-year surface air temperature data in the Antarctic Peninsula reveals relatively the larger warming trends for autumn and winter than other seasons. The variability of the surface air temperature in this region is compared with that of the regional atmospheric circulation. The surface air temperature is positively correlated with frequency of northwesterlies and negatively correlated with frequency of southeasterlies. This relation is more evident in the northern tip of the Antarctic Peninsula for autumn and winter. The trend analysis of wind frequency in the study area shows increasing and decreasing trends in the frequency of northwesterlies and southeasterlies, respectively, in the northwestern part of the Weddell Sea for autumn and winter. And also it is found that these winds are closely related with decreasing of sea level pressure in the southeastern region of the Antarctic Peninsula. Furthermore from the seasonal variation of sea level pressure in this area, it may be presumed that decreasing of sea level pressure in the southeastern region of the Antarctic Peninsula is related with warming in the vicinity of the Antarctic Peninsula for autumn and winter. Therefore it can be explained that recent warming in the vicinity of the Antarctic Peninsula is caused by positive feedback mechanism, that is, the process that warming in the vicinity of the Antarctic Peninsula can lead to the decrease of sea level pressure in the southeastern region of the Antarctic Peninsula and these pressure decrease in turn lead to the variation of wind direction in northwestern part of Weddell Sea, again the variation of wind direction enhances the warming in the Antarctic Peninsula.

Fault Detection for Seismic Data Interpretation Based on Machine Learning: Research Trends and Technological Introduction (기계 학습 기반 탄성파 자료 단층 해석: 연구동향 및 기술소개)

  • Choi, Woochang;Lee, Ganghoon;Cho, Sangin;Choi, Byunghoon;Pyun, Sukjoon
    • Geophysics and Geophysical Exploration
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    • v.23 no.2
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    • pp.97-114
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    • 2020
  • Recently, many studies have been actively conducted on the application of machine learning in all branches of science and engineering. Studies applying machine learning are also rapidly increasing in all sectors of seismic exploration, including interpretation, processing, and acquisition. Among them, fault detection is a critical technology in seismic interpretation and also the most suitable area for applying machine learning. In this study, we introduced various machine learning techniques, described techniques suitable for fault detection, and discussed the reasons for their suitability. We collected papers published in renowned international journals and abstracts presented at international conferences, summarized the current status of the research by year and field, and intensively analyzed studies on fault detection using machine learning. Based on the type of input data and machine learning model, fault detection techniques were divided into seismic attribute-, image-, and raw data-based technologies; their pros and cons were also discussed.

A New Correction Method for Ship's Viscous Magnetization Effect on Shipboard Three-component Magnetic Data Using a Total Field Magnetometer (총자력계를 이용한 선상 삼성분 자기 데이터의 선박 점성 자화 효과에 대한 새로운 보정 방법 연구)

  • Hanjin Choe;Nobukazu Seama
    • Geophysics and Geophysical Exploration
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    • v.27 no.2
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    • pp.119-128
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    • 2024
  • Marine magnetic surveys provide a rapid and cost-effective method for pioneer geophysical survey for many purposes. Sea-surface magnetometers offer high accuracy but are limited to measuring the scalar total magnetic field and require dedicated cruise missions. Shipboard three-component magnetometers, on the other hand, can collect vector three components and applicable to any cruise missions. However, correcting for the ship's magnetic field, particularly viscous magnetization, still remains a challenge. This study proposes a new additional correction method for ship's viscous magnetization effect in vector data acquired by shipboard three-component magnetometer. This method utilizes magnetic data collected simultaneously with a sea-surface magnetometer providing total magnetic field measurements. Our method significantly reduces deviations between the two datasets, resulting in corrected vector anomalies with errors as low as 7-25 nT. These tiny errors are possibly caused by the vector magnetic anomaly and its related viscous magnetization. This method is expected to significantly improve the accuracy of shipborne magnetic surveys by providing corrected vector components. This will enhance magnetic interpretations and might be useful for understanding plate tectonics, geological structures, hydrothermal deposits, and more.

On-orbit Thermal Analysis for Verification of Thermal Design of 6 U Nano-Satellite with Multiple Payloads (멀티 탑재체를 가진 6 U 초소형위성의 열설계 검증을 위한 궤도 열해석)

  • Kim, Ji-Seok;Kim, Hui-Kyung;Kim, Min-Ki;Kim, Hae-Dong
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.48 no.6
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    • pp.455-466
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    • 2020
  • In this study, we built a thermal model for SNIPE 6U nano-satellite which has scientific mission for measuring science data in near Earth space environment and described thermal design based on the thermal model. And the validity of the thermal design was verified through the on-orbit thermal analysis. The thermal design was carried out mainly on the passive thermal control techniques such as surface finishes, insulators, and thermal conductors in consideration of the characteristics of the nano-satellite. However, the components with narrow operating temperature range and directly exposed to the orbital thermal environments, such as a battery and thrusters, are accomodated with heaters to satisfy the temperature requirements. On-orbit thermal analysis conditions are based on the basic orbital conditions of the satellite, and thermal analysis was performed for Normal mode, Launch & Early Orbit Phase (LEOP), Safehold mode, and Maneuver mode which are classified by the power consumption and the attitude of the satellite according to the mission scenario. The analysis results for each mode confirmed that every component satisfies the temperature requirement. In addition, the heater capacity and duty cycle of the battery and thruster were calculated through the analysis results of the Safehold mode.

Indoor Air Quality Index for School Classrooms Based on Health Effects (학교 교실 공기질 관리를 위한 건강영향 기반 실내공기질지수 개발)

  • Kim, Do Yun;Kwon, Ji You;Lee, Tae Jung;Park, Young Koo;Jo, Young Min
    • Journal of Environmental Impact Assessment
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    • v.30 no.6
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    • pp.380-392
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    • 2021
  • An indoor air quality index for school classrooms based on the Hazard Quotient (HQ) was developed in this study. The current index (IAQI-S) covered PM10, PM2.5, and CO2, and breakpoints of IAQI-S were calculated using each HQ value. IAQI-S was applied to the real-time data obtained from 123 classrooms of 46 schools during November 2017 to December 2020. As a result of the comprehensive assessment, 93.1% of PM10 and 94% of PM2.5 belonged to 'good' and 'moderate', respectively. The IAQI-S based on an 8-hour predicted moving average was compared with Comprehensive Air-quality Index (CAI) and with the IAQI of a foreign reference. The IAQI-S includes CO2 and consists of more stringent levels comparing to outdoor index (CAI).

Fog Detection over the Korean Peninsula Derived from Satellite Observations of Polar-orbit (MODIS) and Geostationary (GOES-9) (극궤도(MODIS) 및 정지궤도(GOES-9) 위성 관측을 이용한 한반도에서의 안개 탐지)

  • Yoo, Jung-Moon;Yun, Mi-Young;Jeong, Myeong-Jae;Ahn, Myoung-Hwan
    • Journal of the Korean earth science society
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    • v.27 no.4
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    • pp.450-463
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    • 2006
  • Seasonal threshold values for fog detection over the ten airport areas within the Korean Peninsula have been derived from the data of polar-orbit Aqua/Terra MODIS and geostationary GOES-9 during a two years. The values are obtained from reflectance at $0.65{\mu}m\;(R_{0.65})$ and the difference in brightness temperature between $3.7{\mu}m\;and\;11{\mu}m\;(T_{3.7-11})$. In order to examine the discrepancy between the threshold values of two kinds of satellites, the following four parameters have been analyzed under the condition of daytime/nighttime and fog/clear-sky, utilizing their simultaneous observations over the Seoul metropolitan area: brightness temperature at $3.7{\mu}m$, the temperature at $11{\mu}m,\;the\;T_{3.7-11}$ for day and night, and the $R_{0.65}$ for daytime. The parameters show significant correlations (r<0.5) in spatial distribution between the two kinds of satellites. The discrepancy between their infrared thresholds is mainly due to the disagreement in their spatial resolutions and spectral bands, particularly at $3.7{\mu}m$. Fog detection from GOES-9 over the nine airport areas except the Cheongju airport has revealed accuracy of 60% in the daytime and 70% in the nighttime, based on statistical verification. The accuracy decreases in foggy cases with twilight, precipitation, short persistence, or the higher cloud above fog. The sensitivity of radiance and reflectance with wavelength has been analyzed in numerical experiments with respect to various meteorological conditions to investigate optical characteristics of the three channels.

Distribution of Hydrometeors and Surface Emissivity Derived from Microwave Satellite Observations and Model Reanalyses (위성관측(MSU)과 모델 재분석 자료에서 조사된 대기물현상과 표면 방출율의 분포)

  • Kim, Tae-Yean;Yoo, Jung-Moon
    • Journal of the Korean earth science society
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    • v.23 no.7
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    • pp.552-564
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    • 2002
  • The data of satellite-observed Microwave Sounding Unit (MSU) channel 1 (Ch1) brightness temperature and General Circulation Model (GCM) reanalyses over the globe have been used to investigate low tropospheric hydrometeors and microwave surface emissivity during the period from January 1981 to December 1993. The average of GCM Ch1 temperature has been reconstructed from three kinds of reanalyses, based on the MSU weighting function. Since the GCM temperature mainly corresponds to the thermal state of the lower troposphere without the difference in the emissivity between ocean and land, it is higher in summer than in other seasons over the regions. The MSU temperature over the ocean shows its maximum at the ITCZ and the SPCZ due to hydrometeors. Over high latitude ocean, the temperature is enhanced because of sea ice emissivity, while it is reduced over the land. The seasonal displacement of the ITCZ and the SPCZ systematically appeared in the difference of Ch1 temperature between the GCM and the MSU. The difference values decrease in the regions of the ITCZ, the SPCZ, and the sea ice because of the increase of the MSU temperature. According to the local minima of the values, the ITCZ moves norhward to 9 N in fall, and the SPCZ moves southward to 12 S in boreal fall and winter. The sea ice in the northern hemisphere is extended southward to 53 N in winter, while the ice in the southern hemisphere, northward to 58 S in boreal summer. We also have discussed the separated contribution from hydrometeors and surface emissivity to the MSU Ch1 temperature, utilizing radiative transfer theory. The increase of 4-6K in the temperature over the ITCZ is inferred to result from hydrometeors of 1-1.5mm/day, and furthermore the increase of 10-30K over the high latitude ocean, ice emissivity of 0.6-0.9.

Tropospheric Ozone over the Seoul Metropolitan Area Derived from Satellite Observations (MODIS) and Numerical Simulation (위성관측(MODIS)에서 유도된 수도권 지역의 대류권 오존 및 수치실험)

  • Yoo Jung-Moon;Park Yoo-Min;Lee Suk-Jo
    • Journal of the Korean earth science society
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    • v.26 no.3
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    • pp.283-296
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    • 2005
  • The effect of ozone and surface temperature on the ozone band at $9.7{\mu}m$ has been investigated from radiative transfer theory together with observations in order to derive empirical methods for remotely sensing ground-ozone concentration. Simultaneous observations of satellite (MODIS Aqua; ECT 13:30) and ground-ozone at 79 stations have been used over the Seoul Metropolitan Area (SMA; 125.7-127.2 E, 37.2-37.7 N) during four ozone-warning days in the year 2003. Cloud effect on the band in the methods was filtered out based on synoptic observations. Upwelling radiance values at $9.6{\mu}m$ which have been estimated at the given ozone concentration of 327-391 DU depend on surface temperature (Ts) showing $5.52\~5.78Wm^{-2}sr^{-1}\;at\;Ts = 290 K,\;and\;9.00\~9.57Wm^{-2}sr^{-1}$ Ts = 325K. Thus, the partitioned contributions of ozone and temperature to intensity of ozone absorption band are $0.26Wm^{-1}sr^{-1}/64\;DU\;and\;0.31 Wm^{-2}sr^{-1}/35K$, respectively. Here the intensity which has been used to remotely detect ground-ozone concentration from infrared satellite measurement is defined as the difference in brightness temperature between $11{\mu} m\;and\;9.7{\mu}m (i.e.,\; T_{11-9.7})$. The methods in this study have been applied to estimate ground-ozone from MODIS data in cases that there are significant correlations between the band intensity and ground-ozone. The values of estimated ozone significantly correlate (0.49-0.63) with ground observations at a significance level of $1\%$. For the improved methods, further study may be required to use tropospheric ozone rather than ground-ozone, considering the variation stratospheric ozone.