• Title/Summary/Keyword: Observation-error model

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A High-Resolution Image Reconstruction Method Utilizing Automatic Input Image Selection from Low-Resolution Video (저해상도 동영상에서의 자동화된 입력영상 선별을 이용한 고해상도 영상 복원 방법)

  • Kim Sung-Deuk
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.43 no.2 s.308
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    • pp.12-18
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    • 2006
  • This paper presents a method to extract a good high-resolution image from a low-resolution video in an automatic manner. Since a high-resolution image reconstruction method utilizing several low-resolution input images works better than a conventional interpolation method utilizing single low-resolution input image only if the input images are well registered onto a common high-resolution grid, low-resolution input images should be carefully chosen so that the registration errors can be carefully considered. In this paper, the statistics obtained from the motion-compensated low-resolution images are utilized to evaluate the feasibility of the input image candidates. Maximum motion-compensation error is estimated from the high-resolution image observation model. U the motion-compensation error of the input image candidate is greater than the estimated maximum motion-compensation error, the input image candidate is discarded. The number of good input image candidates and the statistics of the motion-compensation errors are used to choose final input images. The final input images chosen from the input image selection block are given to the following high-resolution image reconstruction block. It is expected that the proposed method is utilized to extract a good high-resolution image efficiently from a low-resolution video without any user intervention.

Numerical Study on the Observational Error of Sea-Surface Winds at leodo Ocean Research Station (수치해석을 이용한 이어도 종합해양과학기지의 해상풍 관측 오차 연구)

  • Yim Jin-Woo;Lee Kyung-Rok;Shim Jae-Seol;Kim Chong-Am
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.18 no.3
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    • pp.189-197
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    • 2006
  • The influence of leodo Ocean Research Station structure to surrounding atmospheric flow is carefully investigated using CFD techniques. Moreover, the validation works of computational results are performed by the comparison with the observed data of leodo Ocean Research station. In this paper, we performed 3-dimensional CAD modelling of the station, generated the grid system for numerical analysis and carried out flow analyses using Navier-Stokes equations coupled with two-equation turbulence model. For suitable free stream conditions of wind speed and direction, the interference of the research station structure on the flow field is predicted. Beside, the computational results are benchmarked by observed data to confirm the accuracy of measured date and reliable data range of each measuring position according to the wind direction. Through the results of this research, now the quantitative evaluation of the error range of interfered gauge data is possible, which is expected to be applied to provide base data of accurate sea surface wind around research stations.

Analysis of Land Surface Temperature from MODIS and Landsat Satellites using by AWS Temperature in Capital Area (수도권 AWS 기온을 이용한 MODIS, Landsat 위성의 지표면 온도 분석)

  • Jee, Joon-Bum;Lee, Kyu-Tae;Choi, Young-Jean
    • Korean Journal of Remote Sensing
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    • v.30 no.2
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    • pp.315-329
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    • 2014
  • In order to analyze the Land Surface Temperature (LST) in metropolitan area including Seoul, Landsat and MODIS land surface temperature, Automatic Weather Station (AWS) temperature, digital elevation model and landuse are used. Analysis method among the Landsat and MODIS LST and AWS temperature is basic statistics using by correlation coefficient, root-mean-square error and linear regression etc. Statistics of Landsat and MODIS LST are a correlation coefficient of 0.32 and Root Mean Squared Error (RMSE) of 4.61 K, respectively. And statistics of Landsat and MODIS LST and AWS temperature have the correlations of 0.83 and 0.96 and the RMSE of 3.28 K and 2.25 K, respectively. Landsat and MODIS LST have relatively high correlation with AWS temperature, and the slope of the linear regression function have 0.45 (Landsat) and 1.02 (MODIS), respectively. Especially, Landsat 5 has lower correlation about 0.5 or less in entire station, but Landsat 8 have a higher correlation of 0.5 or more despite of lower match point than other satellites. Landsat 7 have highly correlation of more than 0.8 in the center of Seoul. Correlation between satellite LSTs and AWS temperature with landuse (urban and rural) have 0.8 or higher. Landsat LST have correlation of 0.84 and RMSE of more than 3.1 K, while MODIS LST have correlation of more than 0.96 and RMSE of 2.6 K. Consequently, the difference between the LSTs by two satellites have due to the difference in the optical observation and detection the radiation generated by the difference in the area resolution.

Method of Earthquake Acceleration Estimation for Predicting Damage to Arbitrary Location Structures based on Artificial Intelligence (임의 위치 구조물의 손상예측을 위한 인공지능 기반 지진가속도 추정방법 )

  • Kyeong-Seok Lee;Young-Deuk Seo;Eun-Rim Baek
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.27 no.3
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    • pp.71-79
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    • 2023
  • It is not efficient to install a maintenance system that measures seismic acceleration and displacement on all bridges and buildings to evaluate the safety of structures after an earthquake occurs. In order to maintain this, an on-site investigation is conducted. Therefore, it takes a lot of time when the scope of the investigation is wide. As a result, secondary damage may occur, so it is necessary to predict the safety of individual structures quickly. The method of estimating earthquake damage of a structure includes a finite element analysis method using approved seismic information and a structural analysis model. Therefore, it is necessary to predict the seismic information generated at arbitrary location in order to quickly determine structure damage. In this study, methods to predict the ground response spectrum and acceleration time history at arbitrary location using linear estimation methods, and artificial neural network learning methods based on seismic observation data were proposed and their applicability was evaluated. In the case of the linear estimation method, the error was small when the locations of nearby observatories were gathered, but the error increased significantly when it was spread. In the case of the artificial neural network learning method, it could be estimated with a lower level of error under the same conditions.

Characteristics of Tidal Flow Simulation of Real Tide in West-South Coastal Waters of Korea (실조석에 의한 한국 서남해 연안역에서 해수유동의 재현특성)

  • Jeong, Seung-Myong;Park, Il-Heum
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.26 no.5
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    • pp.531-541
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    • 2020
  • In this study, a computed tide of a real tide was introduced to improve the numerical solutions for tides and tidal flow simulations. The real tide was defined considering the nodal modulation amplitude, phase correction factor, astronomical argument, and tidal harmonic constants of all the constituents. The numerical simulation was performed using the real tide parameters for the west-south coastal waters of Korea, where the observation data for tides, tidal currents, waves, and winds over two seasons exist. The tidal flow simulation of the real tide was simulated successfully. The correlation coefficient between the observed and calculated values was 1.0, which indicated both accurate amplitude and phase. The U- and V-components of the tidal current obtained for the real tide had average valid correlations of 0.83 and 0.936, respectively. The speed error for the residual current was 0.006 m/s on the average, which indicated an insignificant difference, and the directional behavior of the residual current was very similar. In addition, the velocity error was attributed to various weather effects, such as high waves and wind storms. Therefore, this model is expected to improve current solutions provided that weathering forces, such as waves and winds, are considered.

The Effect of Uncertainty in Roughness and Discharge on Flood Inundation Mapping (조도계수와 유량의 불확실성이 홍수범람도 구축에 미치는 영향)

  • Jung, Younghun;Yeo, Kyu Dong;Kim, Soo Young;Lee, Seung Oh
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.33 no.3
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    • pp.937-945
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    • 2013
  • The accuracy of flood inundation maps is determined by the uncertainty propagated from all variables involved in the overall process including input data, model parameters and modeling approaches. This study investigated the uncertainty arising from key variables (flow condition and Manning's n) among model variables in flood inundation mapping for the Missouri River near Boonville, Missouri, USA. Methodology of this study involves the generalized likelihood uncertainty estimation (GLUE) to quantify the uncertainty bounds of flood inundation area. Uncertainty bounds in the GLUE procedure are evaluated by selecting two likelihood functions, which is two statistic (inverse of sum of squared error (1/SAE) and inverse of sum of absolute error (1/SSE)) based on an observed water surface elevation and simulated water surface elevations. The results from GLUE show that likelihood measure based on 1/SSE is more sensitive on observation than likelihood measure based on 1/SAE, and that the uncertainty propagated from two variables produces an uncertainty bound of about 2% in the inundation area compared to observed inundation. Based on the results obtained form this study, it is expected that this study will be useful to identify the characteristic of flood.

Development and Verification of a Rapid Refresh Wave Forecasting System (초단기 파랑예측시스템 구축 및 예측성능 검증)

  • Roh, Min;La, NaRy;Oh, SangMyeong;Kang, KiRyong;Chang, PilHun
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.32 no.5
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    • pp.340-350
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    • 2020
  • A rapid refresh wave forecasting system has been developed using the sea wind on the Korea Local Analysis and Prediction System. We carried out a numerical experiment for wind-wave interaction as an important parameter in determining the forecasting performance. The simulation results based on the seasons of with typhoon and without typhoon has been compared with the observation of the ocean data buoy to verify the forecasting performance. In case of without typhoon, there was an underestimate of overall forecasting tendency, and it confirmed that an increase in the wind-wave interaction parameter leads to a decrease in the underestimate tendency and root mean square error (RMSE). As a result of typhoon season by applying the experiment condition with minimum RMSE on without typhoon, the forecasting error has increased in comparison with the result without typhoon season. It means that the wave model has considered the influence of the wind forcing on a relatively weak period on without typhoon, therefore, it might be that the wave model has not sufficiently reflected the nonlinear effect and the wave energy dissipation due to the strong wind forcing.

Applicability of Daily Solar Radiation Estimated by Mountain Microclimate Simulation Model (MT-CLIM) in Korea (MT-CLIM 프로그램을 이용한 일별 일사량 추정의 국내 적용성 검토)

  • Shim, Kyo Moon;Kim, Yong Seok;Lee, Deog Bae;Kang, Ki Keong;So, Kyo-Ho
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.14 no.4
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    • pp.260-264
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    • 2012
  • Accuracy of daily solar radiation estimated from a Mountain Microclimate Simulation Model (MT-CLIM) was assessed for seven observation sites with complex topography in Uiseong County. The coefficient of determination ($R^2$) between the observed and the estimated daily solar radiation was 0.52 for 7 sites for the study period from 1 August to 30 September 2009. Overall, the MT-CLIM overestimated the solar radiation with root mean square error (RMSE) of $3.83MJ\;m^{-2}$ which is about 25% of the mean daily solar radiation ($15.27MJ\;m^{-2}$) for the study period. Considering that the pyranometer's tolerance is ${\pm}5%$ of standard sensor, the RMSE of MT-CLIM was too large to accept for a direct application for agricultural sector. The reliability of solar radiation estimated by MT-CLIM must be improved by considering additional ways such as using a topography correction coefficient.

Application Analysis of GIS Based Distributed Model Using Radar Rainfall (레이더강우를 이용한 GIS기반의 분포형모형 적용성 분석)

  • Park, Jin-Hyeog;Kang, Boo-Sik;Lee, Geun-Sang
    • Journal of Korean Society for Geospatial Information Science
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    • v.16 no.1
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    • pp.23-32
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    • 2008
  • According to recent frequent local flash flood due to climate change, the very short-term rainfall forecast using remotely sensed rainfall like radar is necessary to establish. This research is to evaluate the feasibility of GIS-based distributed model coupled with radar rainfall, which can express temporal and spatial distribution, for multipurpose dam operation during flood season. $Vflo^{TM}$ model was used as physically based distributed hydrologic model. The study area was Yongdam dam basin ($930\;km^2$) and the 3 storm events of local convective rainfall in August 2005, and the typhoon.Ewiniar.and.Bilis.collected from Jindo radar was adopted for runoff simulation. Distributed rainfall consistent with hydrologic model grid resolution was generated by using K-RainVieux, pre-processor program for radar rainfall. The local bias correction for original radar rainfall shows reasonable results of which the percent error from the gauge observation is less than 2% and the bias value is $0.886{\sim}0.908$. The parameters for the $Vflo^{TM}$ were estimated from basic GIS data such as DEM, land cover and soil map. As a result of the 3 events of multiple peak hydrographs, the bias of total accumulated runoff and peak flow is less than 20%, which can provide a reasonable base for building operational real-time short-term rainfall-runoff forecast system.

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An Analysis of Global Solar Radiation using the GWNU Solar Radiation Model and Automated Total Cloud Cover Instrument in Gangneung Region (강릉 지역에서 자동 전운량 장비와 GWNU 태양 복사 모델을 이용한 지표면 일사량 분석)

  • Park, Hye-In;Zo, Il-Sung;Kim, Bu-Yo;Jee, Joon-Bum;Lee, Kyu-Tae
    • Journal of the Korean earth science society
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    • v.38 no.2
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    • pp.129-140
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    • 2017
  • Global solar radiation was calculated in this research using ground-base measurement data, meteorological satellite data, and GWNU (Gangneung-Wonju National University) solar radiation model. We also analyzed the accuracy of the GWNU model by comparing the observed solar radiation according to the total cloud cover. Our research was based on the global solar radiation of the GWNU radiation site in 2012, observation data such as temperature and pressure, humidity, aerosol, total ozone amount data from the Ozone Monitoring Instrument (OMI) sensor, and Skyview data used for evaluation of cloud mask and total cloud cover. On a clear day when the total cloud cover was 0 tenth, the calculated global solar radiations using the GWNU model had a high correlation coefficient of 0.98 compared with the observed solar radiation, but root mean square error (RMSE) was relatively high, i.e., $36.62Wm^{-2}$. The Skyview equipment was unable to determine the meteorological condition such as thin clouds, mist, and haze. On a cloudy day, regression equations were used for the radiation model to correct the effect of clouds. The correlation coefficient was 0.92, but the RMSE was high, i.e., $99.50Wm^{-2}$. For more accurate analysis, additional analysis of various elements including shielding of the direct radiation component and cloud optical thickness is required. The results of this study can be useful in the area where the global solar radiation is not observed by calculating the global solar radiation per minute or time.