• The Journal of Engineering Geology
• /
• v.24 no.2
• /
• pp.191-199
• /
• 2014

We describe a method for detecting slope instability in flume tests using pore pressure and water content data in conjunction with a statistical control chart analysis. Specifically, we conducted univariate statistical analysis on x-MR control chart data (pore pressure and water content) collected at several points along the flume slope, which we separated into three parts: upper, middle, and lower. To assess our results in the context of landslide forecasting and warning systems, we applied control limit lines at $1{\sigma}$, $2{\sigma}$, and $3{\sigma}$ levels of uncertainty. In doing so, we observed that dispersion time varies depending on the control limit line used. Moreover, the detection of instabilities is highly dependent on the position and type of sensor. Our findings indicate that different characteristics of the data on various factors predict slope failure differently and these characteristics can be identified by univariate statistical analysis. Therefore, we suggest that a univariate statistical approach is an effective method for the early detection of slope instability.

• 한국태양에너지학회:학술대회논문집
• /
• 2009.04a
• /
• pp.145-149
• /
• 2009

High-resolution atmospheric numerical system was set up to simulate the motion of the atmosphere and to produce the wind map on land. The results of several simulations were improved compare to the past system, because of using the fine geographical data, such as terrain height and land-use data, and the meteorological data assimilation. To estimate surface maximum wind speed when a typhoon is expected to strike the Korea peninsula, wind information at the upper level atmosphere was applied. Using 700hPa data, wind speed at the height of 300m was estimated, and surface wind speed was estimated finally considering surface roughness length. This study used formula from other countries and estimated RMW but RMW estimation formula apt to Korea should be developed for future.

• Journal of Korean Society for Atmospheric Environment
• /
• v.27 no.1
• /
• pp.30-40
• /
• 2011

Numerical simulations were carried out to investigate the impact of SST spatial distribution on the result of air quality modeling. Eulerian photochemical dispersion model CAMx (Comprehensive Air quality Model with eXtensions, version 4.50) was applied in this study and meteorological fields were prepared by RAMS (Regional Atmospheric Modeling System). Three different meteorological fields, due to different SST spatial distributions were used for air quality modeling to assess the sensitivity of CAMx modeling to the different meteorological input data. The horizontal distributions of surface ozone concentrations were analyzed and compared. In each case, the simulated ozone concentrations were different due to the discrepancies of horizontal SST distributions. The discrepancies of land-sea breeze velocity caused the difference of daytime and nighttime ozone concentrations. The result of statistic analysis also showed differences for each case. Case NG, which used meteorological fields with high resolution SST data was most successfully estimated correlation coefficient, root mean squared error and index of agreement value for ground level ozone concentration. The prediction accuracy was also improved clearly for case NG. In conclusion, the results suggest that SST spatial distribution plays an important role in the results of air quality modeling on high ozone episode at coastal region.

• Journal of the Korean Society of Groundwater Environment
• /
• v.7 no.1
• /
• pp.20-23
• /
• 2000

A general solution for determining the storage coefficient from multi-step pumping test recovery data is suggested. This solution is essentially based on the method of Banton and Bangoy (1996), which used single-step pumping test recovery data. The suggested solution can be applied to any-step pumping test recovery data. We have demonstrated the applicability of the general solution to single-, double-, and triple-step pumping and/or step-drawdown test data partially described in Lee and Lee (1999). The estimates of storage coefficient as well as transmissivity are well consistent with the values from other methods for pumping phase data.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
• /
• 2002.04a
• /
• pp.110-113
• /
• 2002

Statistical- based, principal component analysis (PCA) was applied to chemical data from two underground storage systems containing LPG to assess the usefulness of such technique at the initial stage (Pyeongtaek) or middle stage (Ulsan) of hydrochemical studies. For the first case, both natural and anthropogenic contamination characterize regional groundwater. Saline water buffered by Namyang lake affects as a natural factor, whereas cement grouting influence as an artificial factor. For the second study area, contaminations due to operation of LPG caverns, such as disinfection activity and cement grouting effect, deteriorate groundwater quality. This study indicates that principal component analysis would be particularly useful for summarizing large data set for the purpose of subsurface characterization, assessing their vulnerability to contamination and protecting recharge zones.

• Journal of Environmental Science International
• /
• v.19 no.8
• /
• pp.983-999
• /
• 2010

Wind power energy is one of the favorable and fast growing renewable energies. It is most important for exact analysis of wind to evaluate and forecast the wind power energy. The purpose of this study is to improve the performance of numerical atmospheric model by data assimilation over a complex coastal area. The benefit of the profiler is its high temporal resolution and dense observation data at the lower troposphere. Three wind profiler sites used in this study are inhomogeneously situated near south-western coastal area of Korean Peninsula. The method of the data assimilation for using the profiler to the model simulation is the three-dimensional variational data assimilation (3DVAR). The experiment of two cases, with/without assimilation, were conducted for how to effect on model results with wind profiler data. It was found that the assimilated case shows the more reasonable results than the other case compared with vertical observation and surface Automatic Weather Station(AWS) data. Although the effect of sonde data was better than profiler at a higher altitude, the profiler data improves the model performance at lower atmosphere. Comparison with the results of 4 June and 5 June suggests that the efficiency with hourly assimilated profiler data is strongly influenced by synoptic conditions. The reduction rate of Normalized Mean Error(NME), mean bias normalized by averaged wind speed of observation, on 4 June was 28% which was larger than 13% of 5 June. In order to examine the difference in wind power energy, the wind power density(WPD) was calculated and compared.

• Journal of the Korean Solar Energy Society
• /
• v.26 no.4
• /
• pp.83-91
• /
• 2006

As a demand for sustainable development rises, the preference for earth house (earth construction) increases gradually. However, there are few data for predicting and evaluating the thermal environment and indoor air quality of earth house. Thus, this study aims to measure thermal properties(thermal conductivity, density and specific heat) and pollutants emission intensities(formaldehyde and volatile organic compounds) of current main earth construction materials and make a comparison between earth and cement construction materials. As results, quantitative thermal properties and pollutants emission intensities of current main earth construction materials are shown.

• Korean Journal of Remote Sensing
• /
• v.37 no.4
• /
• pp.777-788
• /
• 2021

Since aerosol has a relatively short duration and significant spatial variation, satellite observations become more important for the spatially and temporally continuous quantification of aerosol. However, optical remote sensing has the disadvantage that it cannot detect AOD (Aerosol Optical Depth) for the regions covered by clouds or the regions with extremely high concentrations. Such missing values can increase the data uncertainty in the analyses of the Earth's environment. This paper presents a spatial gap-filling framework using a univariate statistical method such as DCT-PLS (Discrete Cosine Transform-based Penalized Least Square Regression) and FMM (Fast Matching Method) inpainting. We conducted a feasibility test for the hourly AOD product from AHI (Advanced Himawari Imager) between January 1 and December 31, 2019, and compared the accuracy statistics of the two spatial gap-filling methods. When the null-pixel area is not very large (null-pixel ratio < 0.6), the validation statistics of DCT-PLS and FMM techniques showed high accuracy of CC=0.988 (MAE=0.020) and CC=0.980 (MAE=0.028), respectively. Together with the AI-based gap-filling method using extra explanatory variables, the DCT-PLS and FMM techniques can be tested for the low-resolution images from the AMI (Advanced Meteorological Imager) of GK2A (Geostationary Korea Multi-purpose Satellite 2A), GEMS (Geostationary Environment Monitoring Spectrometer) and GOCI2 (Geostationary Ocean Color Imager) of GK2B (Geostationary Korea Multi-purpose Satellite 2B) and the high-resolution images from the CAS500 (Compact Advanced Satellite) series soon.

• Journal of the Korean earth science society
• /
• v.39 no.4
• /
• pp.378-387
• /
• 2018

In this research, the change of Korean middle-school science education environments is investigated through analyzing eighth graders' survey data collected over the past 20 years of TIMSS. We extracted educational context variables that provide meaningful information on changes of Korean science education, and have been surveyed more than 3 study cycles up to TIMSS 2015. The selected educational context variables include school resources and school climate from the school principal's questionnaires, and teacher characteristics and instructional activities from the teacher's questionnaires. For each context variable, we analyzed its trend over TIMSS cycles, and discussed its implications in light of Korean educational policy and curriculum changes. Based on the results, we recommended several ways that help to improve science teaching and learning in light of lab assistants, computer availability, teacher learning community, and middle school Earth science curriculum.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
• /
• 2003.09a
• /
• pp.404-408
• /
• 2003

In this study, we examined the influences of pH and total concentration on the speciation of heavy metals (Cd, Cu, Zn) in acid mine drainage. Their labile concentrations were analyzed by Anodic Stripping Voltammetry (ASV) at both natural pH and adjusted pHs (from 2 to 8). We obtained regression equations for predicting labile concentrations as a function of the water pH and contamination level (total dissolved metal concentration). Our data show that labile Cu depends on both the total concentration and pH, while labile Cd and Zn concentrations are controlled mainly by their total concentration rather than pH. Therefore, the pH variation of AMD may significantly change the toxicity and bioavailability especially of Cu, owing to its speciation change.