• Journal of Positioning, Navigation, and Timing
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• v.3 no.4
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• pp.131-141
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• 2014

Over the last decade, the Global Navigation Satellite System (GNSS) has been increasingly utilized as a meteorological research tool. The Korea Astronomy and Space Science Institute (KASI) has also been developing a near real-time GNSS precipitable water vapor (PWV) information management system that can produce a precise PWV for the Korean Peninsula region using GNSS data processing and meteorological measurements. The goal of this paper is to evaluate whether the precise point positioning (PPP) strategy will be used as the new data processing strategy of the GNSS-PWV information management system. For this purpose, quality assessment has been performed by means of a comparative analysis of the troposphere zenith total delay (ZTD) estimates from KASI PPP solutions (KPS), KASI network solutions (KNS), and International GNSS Service (IGS) final troposphere products (IFTP) for ten permanent GNSS stations in the Korean Peninsula. The assessment consists largely of two steps: First, the troposphere ZTD of the KNS are compared to those of the IFTP for only DAEJ and SUWN, in which the IFTP are used as the reference. Second, the KPS are compared to the KNS for all ten GNSS stations. In this step, the KNS are used as a new reference rather than the IFTP, because it was proved in the previous step that the KNS can be a suitable reference. As a result, it was found that the ZTD values from both the KPS and the KNS followed the same overall pattern, with an RMS of 5.36 mm. When the average RMS was converted into an error of GNSS-PWV by considering the typical ratio of zenith wet delay and PWV, the GNSS-PWV error met the requirement for PWV accuracy in this application. Therefore, the PPP strategy can be used as a new data processing strategy in the near real-time GNSS-PWV information management system.

• Journal of Korea Water Resources Association
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• v.53 no.12
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• pp.1193-1201
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• 2020

This study aims to develop a regression model that estimates a low-flow index that can be applied to ungauged basins. A total of 30 midsized basins in South Korea use long-term runoff data provided by the National Integrated Water Management System (NIWMS) to calculate average low-flow, average minimum streamflow, and low-flow index duration and frequency. This information is used in the correlation analysis with 18 basin factors and 3 climate change factors to identify the basin area, average basin altitude, average basin slope, water system density, runoff curve number, annual evapotranspiration, and annual precipitation in the low-flow index regression model. This study evaluates the model's accuracy by using the root-mean-square error (RMSE) and the mean absolute error (MAE) for 10 ungauged, verified basins and compares them with the previous model's low-flow calculations to determine the effectiveness of the newly developed model. Comparative analysis indicates that the new regression model produces average low-flow, attributed to the consideration of varied basin and hydrologic factors during the new model's development.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1315-1328
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• 2022

Sinduri beach is a typical sedimentary landform that forms sand dunes due to the influence of the northwest wind in winter. Due to the its large scale and well-developed nature, it has been recognized for conservation value and is currently designated as Natural Monument No. 431, and continuous monitoring is required in terms of the preservation of topographical values. In this study, aerial images, drone images, and drone-based LiDAR data during 36 years were used for long-term topographical change observation of the Sinduri coastal sand dunes located in Taean-gun, Chungcheongnam-do. To implement this, the amount of change in elevation and volume for each period was calculated by applying the difference of Digital Elevation Model (DEM) based on raster calculation using the numerical elevation model generated from the raw data. Also, the amount of change in volume based on probability was calculated using the error propagation law for the intrinsic error of each data source. As a result, it can be seen that from 1986 to 2022, deposition of 35,119 m³ occurred in region of interest A (area: 17,960 m²) and 54,954 m³ of deposition occurred in region of interest B (area: 17,686 m²).

• Journal of Broadcast Engineering
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• v.28 no.1
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• pp.145-148
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• 2023

Open-loop Octonion space-time block code for 4 transmit antenna system is considered and random phases are applied to 4 transmit antennas for physical layer security. When an illegal hacker estimates the random phases of 1 through 4 transmit antennas with maximum likelihood (ML), this letter analyzes the bit error rate (BER) performances versus signal-to-noise ratio (SNR). And the Octonion code in the literature[1] does not have full orthogonality so, this letter employs the perfect orthogonal Octonion code. When the hacker knows that the random phases are 2-PSK constellations and he should estimate all the 4 random phases, the hacking is impossible until 100dB. When the hacker possibly know that some of the random phases, bit error rate goes down to 10^-3 so, the transmit message could be hacked.

• Korean Journal of Ecology and Environment
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• v.56 no.2
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• pp.161-171
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• 2023

The medium-large cladoceran species Simocephalus spp. predominantly occur in habitats with developed aquatic vegetation. Accordingly, due to Simocephalus' high contribution to zooplankton community biomass in the lake's littoral zone and wetland habitats, estimating their biomass is important to understand the matter cycling based on biological interactions within the aquatic food web. In this study, we reviewed the length-weight regression equations used previously to estimate Simocephalus biomass, directly measured S. serrulatus' body specification (length, width and area) and their biomass(dry weight) using instruments such as a microscopic digital camera and a microscale, and performed regression analysis between each other. When S. serrulatus biomass was estimated using the equation (Kawabata and Urabe, 1998) presented in 『Biomonitoring Survey and Assessment Manual』, Korea, errors between estimates and measures were relatively large compared to the S. serrulatus species-specific biomass estimate equation developed by Lemke and Benke (2003). In addition, both equations showed not only increasing trends in error (estimate-measure) with increasing S. serrulatus' body length, but also in error variance among similar-sized individuals. The results of regression analysis with dry weight by body specifications indicated that the most appropriate equation for estimating the biomass of S. serrulatus was derived from the width-dry weight exponential regression equation (R²=0.9555). The review and development study of such species-specific biomass estimation equations for zooplankton can be used as a tool to understand their role and function in aquatic ecosystem food webs.

• The Journal of Bigdata
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• v.8 no.2
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• pp.165-175
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• 2023

LNG is a representative imported cargo at Incheon Port and has a relatively high contribution to the increase/decrease in overall cargo volume at Incheon Port. In addition, in the view point of nationwide, LNG is the one of the most important key resource to supply the gas and generate electricity. Thus, it is very essential to identify the factors that have impact on the demand fluctuation and build the appropriate forecasting model, which present the basic information to make balance between supply and demand of LNG and establish the plan for power generation. In this study, different to previous research based on macroscopic annual data, the weekly demand of LNG is converted from the cargo volume unloaded by LNG carriers. We have identified the periodicity and correlations among internal and external factors of demand variability. We have identified the input factors for predicting the LNG demand such as seasonality of weekly cargo volume, the peak power demand, and the reserved capacity of power supply. In addition, in order to predict LNG demand, considering the characteristics of the data, time series prediction with weekly LNG cargo volume as a dependent variable and prediction through an artificial neural network model were made, the suitability of the predictions was verified, and the optimal model was established through error comparison between performance and estimates.

• The Korean Journal of Applied Statistics
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• v.37 no.4
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• pp.509-523
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• 2024

This study estimates connectedness index among the US, China, Europe, Japan, and South Korea using monthly economic policy uncertainty (EPU) data from January 2000 to December 2023. The connectedness index allows us to analyze the effect of global economic uncertainty on domestic economic uncertainty. The EPU is used as a proxy for economic uncertainty. Inter-country connectedness index is computed from variance decomposition. The findings from forecast error variance decomposition show that three-fourths of total uncertainty comes from economic uncertainty in the own country and one-fourth of total uncertainty comes from economic uncertainty in the others. The analysis on net pairwise connectedness reveals that, even though the extent of the effect of economic uncertainty in one country from economic uncertainty in another country varies over time, economic uncertainty in South Korea, a small-open economy, is mainly affected by economic uncertainty in the others. The reverse situation rarely happens except in the specific occurrence such as the collapse of the credit bubble in 2003 and the subsequent years, the inter-Korean summit and North Korea-the US summit in 2018, and the period from the first outbreak of COVID-19 on the implementation of the government's severe regulation against COVID-19.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.3
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• pp.129-141
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• 2023

Crop models have been used to predict yield under diverse environmental and cultivation conditions, which can be used to support decisions on the management of forage crop. Cultivar parameters are one of required inputs to crop models in order to represent genetic properties for a given forage cultivar. The objectives of this study were to compare calibration and ensemble approaches in order to minimize the uncertainty of crop yield estimates using the SIMPLE crop model. Cultivar parameters were calibrated using Log-likelihood (LL) and Generic Composite Similarity Measure (GCSM) as an objective function for Metropolis-Hastings (MH) algorithm. In total, 20 sets of cultivar parameters were generated for each method. Two types of ensemble approach. First type of ensemble approach was the average of model outputs (E_em), using individual parameters. The second ensemble approach was model output (E_pm) of cultivar parameter obtained by averaging given 20 sets of parameters. Comparison was done for each cultivar and for each error calculation methods. 'Jowoo' and 'Yeongwoo', which are forage rice cultivars used in Korea, were subject to the parameter calibration. Yield data were obtained from experiment fields at Suwon, Jeonju, Naju and I ksan. Data for 2013, 2014 and 2016 were used for parameter calibration. For validation, yield data reported from 2016 to 2018 at Suwon was used. Initial calibration indicated that genetic coefficients obtained by LL were distributed in a narrower range than coefficients obtained by GCSM. A two-sample t-test was performed to compare between different methods of ensemble approaches and no significant difference was found between them. Uncertainty of GCSM can be neutralized by adjusting the acceptance probability. The other ensemble method (E_pm) indicates that the uncertainty can be reduced with less computation using ensemble approach.

• Korean Journal of Remote Sensing
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• v.34 no.2_1
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• pp.301-306
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• 2018

Urbanization causes urban floods and urban heat island in the summer, so it is necessary to understanding the changes of the thermal environment through urban climate and energy balance. This can be explained by the energy balance, but in urban areas, unlike the typical energy balance, the storage heat flux saved in the building or artificial land cover should be considered. Since the environment of each city is different, there is a difficulty in applying the method of retrieving the storage heat flux of the previous research. Especially, most of the previous studies are focused on the overseas cities, so it is necessary to study the storage heat retrieval suitable for various land cover and building characteristics of the urban areas in Korea. Therefore, the object of this study, it is to derive the regression formula which can quantitatively retrieve the storage heat using the data of the area where various surface types exist. To this end, nonlinear regression analysis was performed using net radiation and surface temperature data as independent variables and flux tower based storage heat estimates as dependent variables. The retrieved regression coefficients were applied to each independent variable to derive the storage heat retrieval regression formula. As a result of time series analysis with flux tower based storage heat estimates, it was well simulated high peak at day time and the value at night. Moreover storage heat retrieved in this study was possible continuous retrieval than flux tower based storage heat estimates. As a result of scatter plot analysis, accuracy of retrieved storage heat was found to be significant at $50.14Wm^{-2}$ and bias $-0.94Wm^{-2}$.

• Korean Journal of Remote Sensing
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• v.30 no.4
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• pp.525-536
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• 2014

In this study, a method to assess and monitor hydrological drought using remote sensing was investigated for use in regions with limited observation data, and was applied to the Upper Namhangang basin in South Korea, which was seriously affected by the 2008-2009 drought. Drought information may be obtained more easily from meteorological data based on water balance than hydrological data that are hard to estimate. Air temperature data at 2 m above ground level (AGL) were estimated using remotely sensed data, evapotranspiration was estimated from the air temperature, and the correlations between precipitation minus evapotranspiration (P-PET) and streamflow percentiles were examined. Land Surface Temperature data with $1{\times}1km$ spatial resolution as well as Atmospheric Profile data with $5{\times}5km$ spatial resolution from MODIS sensor on board Aqua satellite were used to estimate monthly maximum and minimum air temperature in South Korea. Evapotranspiration was estimated from the maximum and minimum air temperature using the Hargreaves method and the estimates were compared to existing data of the University of Montana based on Penman-Monteith method showing smaller coefficient of determination values but smaller error values. Precipitation was obtained from TRMM monthly rainfall data, and the correlations of 1-, 3-, 6-, and 12-month P-PET percentiles with streamflow percentiles were analyzed for the Upper Namhan-gang basin in South Korea. The 1-month P-PET percentile during JJA (r = 0.89, tau = 0.71) and SON (r = 0.63, tau = 0.47) in the Upper Namhan-gang basin are highly correlated with the streamflow percentile with 95% confidence level. Since the effect of precipitation in the basin is especially high, the correlation between evapotranspiration percentile and streamflow percentile is positive. These results indicate that remote sensing-based P-PET estimates can be used for the assessment and monitoring of hydrological drought. The high spatial resolution estimates can be used in the decision-making process to minimize the adverse impacts of hydrological drought and to establish differentiated measures coping with drought.