• Journal of Wetlands Research
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• v.22 no.1
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• pp.15-23
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• 2020

The purpose of this study is to investigate how the degree of distribution influences the calibration of snow and runoff in distributed hydrological models using a multi-criteria calibration method. The Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) developed by NOAA-National Weather Service (NWS) is employed to estimate optimized parameter sets. We have 3 scenarios depended on the model complexity for estimating best parameter sets: Lumped, Semi-Distributed, and Fully-Distributed. For the case study, the Durango River Basin, Colorado is selected as a study basin to consider both snow and water balance components. This study basin is in the mountainous western U.S. area and consists of 108 Hydrologic Rainfall Analysis Project (HRAP) grid cells. 5 and 13 parameters of snow and water balance models are calibrated with the Multi-Objective Shuffled Complex Evolution Metropolis (MOSCEM) algorithm. Model calibration and validation are conducted on 4km HRAP grids with 5 years (2001-2005) meteorological data and observations. Through case study, we show that snow and streamflow simulations are improved with multiple criteria calibrations without considering model complexity. In particular, we confirm that semi- and fully distributed models are better performances than those of lumped model. In case of lumped model, the Root Mean Square Error (RMSE) values improve by 35% on snow average and 42% on runoff from a priori parameter set through multi-criteria calibrations. On the other hand, the RMSE values are improved by 40% and 43% for snow and runoff on semi- and fully-distributed models.

• Journal of the Korean earth science society
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• v.39 no.2
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• pp.131-138
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• 2018

The purpose of this study is to improve the quantitative precipitation estimation method based on satellite brightness temperature. The non-linear equation for rainfall estimation is improved by analysing precipitation cases around the Korean peninsula in summer. Radar reflectivity is adopted the CAPPI 1.5 and CMAX composite fields that provided by the Korea Meteorological Agency (KMA). In addition, the satellite data are used infrared, water vapor and visible channel measured from meteorological imager sensor mounted on the Chollian satellite. The improved algorithm is compared with the results of the A-E method and CRR analytic function. POD, FAR and CSI are 0.67, 0.76 and 0.21, respectively. The MAE and RMSE are 2.49 and 6.18 mm/h. As the quantitative error was reduced in comparison to A-E and qualitative accuracy increased in compare with CRR, the disadvantage of both algorithms are complemented. The method of estimating precipitation through a relational expression can be used for short-term forecasting because of allowing precipitation estimation in a short time without going through complicated algorithms.

• Journal of Korea Water Resources Association
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• v.43 no.12
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• pp.1011-1027
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• 2010

In hydrologic modeling, prediction uncertainty generally stems from various uncertainty sources associated with model structure, data, and parameters, etc. This study aims to assess the parameter uncertainty effect on hydrologic prediction results. For this objective, a distributed rainfall-sediment yield-runoff model, which consists of rainfall-runoff module for simulation of surface and subsurface flows and sediment yield module based on unit stream power theory, was applied to the mesoscale mountainous area (Cheoncheon catchment; 289.9 $km^2$). For parameter uncertainty evaluation, the model was calibrated by a multi-objective optimization algorithm (MOSCEM) with two different objective functions (RMSE and HMLE) and Pareto optimal solutions of each case were then estimated. In Case I, the rainfall-runoff module was calibrated to investigate the effect of parameter uncertainty on hydrograph reproduction whereas in Case II, sediment yield module was calibrated to show the propagation of parameter uncertainty into sedigraph estimation. Additionally, in Case III, all parameters of both modules were simultaneously calibrated in order to take account of prediction uncertainty in rainfall-sediment yield-runoff modeling. The results showed that hydrograph prediction uncertainty of Case I was observed over the low-flow periods while the sedigraph of high-flow periods was sensitive to uncertainty of the sediment yield module parameters in Case II. In Case III, prediction uncertainty ranges of both hydrograph and sedigraph were larger than the other cases. Furthermore, prediction uncertainty in terms of spatial distribution of erosion and deposition drastically varied with the applied model parameters for all cases.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2002.09a
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• pp.253-256
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• 2002

거제도는 남쪽에서 두 번째로 큰 섬으로써 총면적은 399.96$\textrm{km}^2$이며 총면적의 71.85%가 임야로 이루어져 있고 하천이 짧으며 유역면적이 좁은 관계로 지하수의 함양이 어려우며 해안으로 유출되는 지하수가 상당량이 될 것으로 사료되었다. 따라서 유출지하수의 특성을 연구하여 지하수의 유출가능성이 높은 지역을 찾을 수 있도록 여러 가지 분석을 통하여 알아보았다. 이를 위하여 기본적으로 기온, 강수량 등의 기상자료와 지하수온도, 지하수위등의 수문자료 및 해수표면온도 등의 해양관측자료를 이용하였으며, 해수와 지하수의 온도차가 많은 달의 Lanset 7 ETM+ 인공위성 영상자료와 NOAA 인공영상자료를 이용하여 온도자료를 비교하고, 각개 영사의 열분포도를 분석함으로써 유출지하수의 가능성이 높은 지역을 추출하였다. 추출한 지역에서 인구밀집지역, 공단지역, 기 공급지역을 제외하였으며, 수문지질학 적으로 유리한 지역을 선정하고, 평균해수분포차가 큰 지역을 추출함으로써 이후에 이루어질 현장조사시에 접근이 용이하도록 하였다. 연구결과 거제도 일대의 해안유출지하수 가능지점은 10개소 이상이며 자연적, 사회학석인 여건을 고려한다면 지하수개발가능 지역은 6개 정도로 예상된다. 또한 해수면의 온도와 지하수의 온도가 차이가 클 때는11~13$^{\circ}C$의 분포를 보이고 있어, 이후 이와 같은 연구에 충분히 활용할 수 있을 것이며, 해상도가 높은 자료와 연계하면 보다 정확한 자료의 추출이 가능해 앞으로의 국내에 활용되지 못한 수자원 개발에도 많은 도움이 될 것으로 판단된다.하게도 유기물과의 친화력이 높은 것으로 알려진 Cu 역시 F1과 F2에 대하여 높은 함량을 나타내어 오염원으로부터의 Cu의 확산을 지시하였다. 외국에 비하여, 그동안 국내에서는 사격장 주변의 자연환경변화에 관하여 연구된 결과가 거의 전무하였다. 본 연구 결과는, 이와 유사한 사격장 주변 환경에서의 중금속 분포와 거동 특성에 대하여 종합적인 모니터링(즉, 체계적인 환경지구화학적 조사ㆍ연구)이 시급함을 시사해 주고 있다.할 수 있었다.연구지역을 대상으로 추정한 함양율은 지하수이용에 따른 지하수위하강에 대한 보정을 할 필요가 있으며 지하수이용실태조사를 추가로 하여 그 이용량만큼을 지하수함양량에 더하여야 할것이다.의 특성 등을 고려하여 거기에 맞는 기술들을 복합적으로 또는 단독으로 사용하되 처리방법 채택 시 신중을 기할 것이 요망된다.정시에는 SeaWiFS 위성과 관련된 global algorithms 중에서 490nm와 555nm의 복합밴드를 포함하는 OC2 알고리즘(ocean color chlorophyll 2 algorithm)을 사용하는 것이 OC2 series 및 OC4 알고리즘보다 좋은 추정 값을 도출할 수 있을 것으로 기대된다.환경에서는 5일에서 7월에 주로 이 충체의 유충이 발육되고 전파되는 것으로 추측되었다.러 가지 방법들을 적극 적용하여 금후 검토해볼 필요가 있을 것이다.잡은 전혀 삭과가 형성되지 않았다. 이 결과는 종간 교잡종을 자방친으로 하고 그 자방친의 화분친을 사용할 때만 교잡이 이루어지고 있음을 나타내고 있다. 따라서 여교잡을 통한 종간잡종 품종육성 활용방안을 금후 적극 확대 검토해야 할 것이다하였다.함을 보

• Journal of Elementary Mathematics Education in Korea
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• v.13 no.1
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• pp.1-15
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• 2009

This research is to provide a useful reference for the future revision of textbook by comparative analysis with the textbook in the 4th grade of elementary school in Japan. The results from this research is same as follows: First, Korean curriculum is emphasizing the reasonable problem-solving ability developed on the base of the mathematical knowledge and skill. Meantime, Japanese puts much value on the is focusing on discretion and the capability in life so that they emphasize each person's learning and raising the power of self-learning and thinking. The ratio on mathematics in both company are high, but Japanese ensures much more hours than Korean. Second, the chapter of Korean textbook is composed of 8 units and the title of the chapter is shown as key word, then the next objects are describes as 'Shall we do$\sim$' type. Hence, the chapter composition of Japanese textbook is different among the chapter and the title of the chapter is described as 'Let's do$\sim$'. Moreover, Korean textbook is arranged focusing on present study, however Japanese is composed with each independent segments in the present study subject to the study contents. Third, Japanese makes students understand the decimal as the extension of the decimal system with measuring unit($\ell$, km, kg) then, learn the operation by algorithm. In Korea, students learn fraction earlier than decimal, but, in Japan students learn decimal earlier than fraction. For the diagram, in Korea, making angle with vertex and side comes after the concept of angle, vertex and side is explained. Hence, in Japan, they show side and vertex to present angle.

• Journal of Korea Spatial Information System Society
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• v.12 no.1
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• pp.57-65
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• 2010

In this study, disaster damage investigation system was developed using high resolution satellite images and GIS technique to afford effective damage investigation system for widely disaster damaged area. Study area was selected in Bonghwa, Gyungsangbukdo where high magnitude of damages from torrential rain has occurred at July in 2008. GIS DB was built using 1:5,000 topographic map, cadastral map, satellite image and aerial photo to apply for investigation algorithm. Disaster damage investigation system was developed using VB NET languages, ArcObject component and MS-SQL DBMS for effective management of damage informations. The system can finding damaged area comparing pre- and post-disaster images and drawing damaged area according to the damage item unit. Extracted object was saved in Shape file format and overlayed with background GIS DB for obtaining detail information of damaged area. Disaster damage investigation system using high resolution spatial images can extract damage information rapidly and highly reliably for widely disaster areas. This system can be expected to highly contributing to enhance the disaster prevention capabilities in national level field investigation supporting and establishing recovery plan etc. This system can be utilized at the plan of disaster prevention through digital damage information and linked in national disaster information management system. Further studies are needed to better improvement in system and cover for the linkage of damage information with digital disaster registry.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.6
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• pp.1-10
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• 2019

This paper proposes a method to improve the detectable distance by reducing noise to perform a signal processing technique on the received signals. To increase the radar detection range, the noise component of the received signal has to be reduced. The proposed method reduces the noise component by employing two methods. First, the radar signals received with multiple pulses are accumulated. As the number of additions increases, the noise component gradually decreases due to noise randomness. On the other hand, the signal term gradually increases and thus signal to noise ratio increases. Secondly, after converting the accumulated signal into the frequency spectrum, a Least Mean Square (LMS) filter is applied. In the case of the radar received signal, desired signal exists in a specific part and most of the rest is a noise. Therefore, if the LMS filter is applied in the time domain, the noise increases. To prevent this, the LMS filter is applied after converting the received signal into the entire frequency spectrum. The LMS filter output is then transformed into the time domain and then range estimation algorithm is performed. Simulation results show that the proposed scheme reduces the noise component by about 25 dB. The experiment was conducted by comparing the proposed results with the conventional results of the radars held by the Korea Aerospace Research Institute for the international space station.

• Journal of Korean Society for Geospatial Information Science
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• v.11 no.4 s.27
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• pp.21-27
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• 2003

The rational polynomial coefficients(RPC) model is a generalized sensor model that is used as an alternative for the physical sensor model for IKONOS-2 and QuickBird. As the number of sensors increases along with greater complexity, and as the need for standard sensor model has become important, the applicability of the RPC model is also increasing. The RPC model can be substituted for all sensor models, such as the projective camera the linear pushbroom sensor and the SAR This paper is aimed at generating a RPC model from the physical sensor model of the KOMPSAT-1(Korean Multi-Purpose Satellite) and aerial photography. The KOMPSAT-1 collects $510{\sim}730nm$ panchromatic images with a ground sample distance (GSD) of 6.6m and a swath width of 17 km by pushbroom scanning. We generated the RPC from a physical sensor model of KOMPSAT-1 and aerial photography. The iterative least square solution based on Levenberg-Marquardt algorithm is used to estimate the RPC. In addition, data normalization and regularization are applied to improve the accuracy and minimize noise. And the accuracy of the test was evaluated based on the 2-D image coordinates. From this test, we were able to find that the RPC model is suitable for both KOMPSAT-1 and aerial photography.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.4
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• pp.111-124
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• 2010

To monitor the environment of land surface change is considered as an important research field since those parameters are related with land use, climate change, meteorological study, agriculture modulation, surface energy balance, and surface environment system. For the change detection, many different methods have been presented for distributing more detailed information with various tools from ground based measurement to satellite multi-spectral sensor. Recently, using high resolution satellite data is considered the most efficient way to monitor extensive land environmental system especially for higher spatial and temporal resolution. In this study, we use two different spatial resolution satellites; the one is SPOT/VEGETATION with 1 km spatial resolution to detect coarse resolution of the area change and determine objective threshold. The other is Landsat satellite having high resolution to figure out detailed land environmental change. According to their spatial resolution, they show different observation characteristics such as repeat cycle, and the global coverage. By correlating two kinds of satellites, we can detect land surface change from mid resolution to high resolution. The K-mean clustering algorithm is applied to detect changed area with two different temporal images. When using solar spectral band, there are complicate surface reflectance scattering characteristics which make surface change detection difficult. That effect would be leading serious problems when interpreting surface characteristics. For example, in spite of constant their own surface reflectance value, it could be changed according to solar, and sensor relative observation location. To reduce those affects, in this study, long-term Normalized Difference Vegetation Index (NDVI) with solar spectral channels performed for atmospheric and bi-directional correction from SPOT/VEGETATION data are utilized to offer objective threshold value for detecting land surface change, since that NDVI has less sensitivity for solar geometry than solar channel. The surface change detection based on long-term NDVI shows improved results than when only using Landsat.

• Korean Journal of Poultry Science
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• v.50 no.1
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• pp.41-50
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• 2023

Over the last decade, avian influenza (AI) has been considered an emerging disease that would become the next pandemic, particularly in countries like South Korea, with continuous animal outbreaks. In this situation, risk assessment is highly needed to prevent and prepare for human infection with AI. Thus, we developed the risk assessment matrix for a high-risk area of human infection with AI in South Korea based on the notion that risk is the multiplication of hazards with vulnerability. This matrix consisted of highly pathogenic avian influenza (HPAI) in poultry farms and the number of poultry-associated production facilities assumed as hazards of avian influenza and vulnerability, respectively. The average number of HPAI in poultry farms at the 229-municipal level as the hazard axis of the matrix was predicted using a negative binomial regression with nationwide outbreaks data from 2003 to 2018. The two components of the matrix were classified into five groups using the K-means clustering algorithm and multiplied, consequently producing the area-specific risk level of human infection. As a result, Naju-si, Jeongeup-si, and Namwon-si were categorized as high-risk areas for human infection with AI. These findings would contribute to designing the policies for human infection to minimize socio-economic damages.