• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.2
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• pp.27-46
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• 2016

In this study, the parameter-elevation regressions on independent slopes model-Kongju National University(PRISM-KNU) system was developed to interpolate monthly precipitation data. One of the features of PRISM-KNU is that it can adjust the allowable range of slope according to the elevation range in the equation representing a linear relationship between the precipitation and elevation. The parameter value of the model was determined by using the optimization technique, and the result was applied to produce monthly precipitation data with a spatial resolution of $1{\times}1km$ from 2000 to 2014 in South Korea. In the result, the Kling-Gupta Efficiency for model evaluation was over 0.7 in 86% of the total cases simulated. In addition, a dramatic change in the spatial pattern of precipitation data was observed in the output of the Modified Korean PRISM, but such a phenomenon did not occur in the output of the PRISM-KNU. This study confirmed the appropriateness of the PRISM-KNU, and the result showed that the spatial consistency of the data produced by the model improved compared with that produced by the Modified Korean PRISM. It is expected that the PRISM-KNU and its output will be utilized in various studies in the future.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.3
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• pp.11-18
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• 2012

Increasing concern about biodiversity has lead to a rise in demand on the spatial assessment of biological resources such as biodiversity assessment, protected area selection, habitat management and restoration in Korea. The purpose of this study is to create species richness map through data collection and modeling techniques for wildlife habitat assessment. The GAM (Generalized Additive Model) is easy to interpret and shows better relationship between environmental variables and a response variable than an existing overlap analysis and GLM (Generalized Linear Model). The study area delineated by a large watershed contains Jirisan national park, Mt. Baekun and Sumjin river with three kinds of protected areas (a national park, a landscape ecology protected area and an otter protected area). We collected the presence-absence data for wildlife (mammals and birds) using a stratified random sampling based on a land cover in the study area and implemented natural and socio-environmental data affecting wildlife habitats. After doing a habitat use analysis and specifying significant factors for each species, we built habitat suitability models using a presence-absence model and created habitat suitability maps for each species. Biodiversity maps were generated by taxa and all species using habitat suitability maps. Significant factors affecting each species habitat were different according to their habitat selection. Although some species like a water deer or a great tit were distributed at the low elevation, most potential habitats for mammals and birds were found at the edge of a national park boundary or near a forest around the medium elevation of a mountain range. This study will be used for a basis on biodiversity assessment and proected area selection carried out by Ministry of Environment.

• Journal of Ecology and Environment
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• v.40 no.1
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• pp.34-44
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• 2016

Background: Little is known about how chemical water quality is associated with ecological stream health in relation to landuse patterns in a watershed. We evaluated spatial characteristics of water quality characteristics and the ecological health of Dongjin-River basin, Korea in relation to regional landuse pattern. The ecological health was assessed by the multi-metric model of Index of Biological Integrity (IBI), and the water chemistry data were compared with values obtained from the health model. Results: Nutrient and organic matter pollution in Dongjin-River basin, Korea was influenced by land use pattern and the major point sources, so nutrients of TN and TP increased abruptly in Site 4 (Jeongeup Stream), which is directly influenced by wastewater treatment plants along with values of electric conductivity (EC), bacterial number, and sestonic chlorophyll-a. Similar results are shown in the downstream (S7) of Dongjin River. The degradation of chemical water quality in the downstream resulted in greater impairment of the ecological health, and these were also closely associated with the landuse pattern. Forest region had low nutrients (N, P), organic matter, and ionic content (as the EC), whereas urban and agricultural regions had opposite in the parameters. Linear regression analysis of the landuse (arable land; $A_L$) on chemicals indicated that values of $A_L$ had positive linear relations with TP ($R^2=0.643$, p < 0.01), TN ($R^2=0.502$, p < 0.05), BOD ($R^2=0.739$, p < 0.01), and suspended solids (SS; ($R^2=0.866$, p < 0.01), and a negative relation with TDN:TDP ratios ($R^2=0.719$, p < 0.01). Conclusions: Chemical factors were closely associated with land use pattern in the watershed, and these factors influenced the ecological health, based on the multimetric fish IBI model. Overall, the impairments of water chemistry and the ecological health in Dongjin-River basin were mainly attributes to point-sources and land-use patterns.

• The Korean Journal of Applied Statistics
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• v.30 no.3
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• pp.417-426
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• 2017

It is important to predict the flowering dates of Japanese cherry and autumnal dates in Korea. Flowering date is decided by heating requirement with daily maximum and minimum temperature used to calculate the pre-determined heating requirements for flowering. Recent, changes in climate have impacted the flowering season of Japanese cherry in Korea. When compared with the current normal, the flowering of Japanese cherry is expected to be about 10 days earlier than in near future normal years. In this paper, we first consider a linear model based on meteorological data that predicts the flowering date and then incorporate a spatial structure into the model. Real data analysis indicates that the proposed approach provides more reasonable predicted dates.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.11
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• pp.2172-2178
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• 2007

In indoor environment, the combination of the two variations, large scale(path loss) and small scale(fading), leads to non-linear variation of RSSI(received signal strength indicator) values as distance varied. This has been one of the difficulties for indoor location estimation. This paper presents new findings on indoor RSSI characterization for more accurate model building. Experiments have been done statistically to find overall trend of RSSI values at different places and times within the same room. From experiments, it has been shown that the variation of RSSI values can be determined by both spatial and temporal factors. These two factors are directly indicated by the two main parameters of path loss model. The results show that all sensor nodes which are located at different places share the same characterization value for the temporal parameter whereas different values for the spatial parameters. The temporal parameter also has a large scale variation effect that is slowly time varying due to environmental changes. Using this relationship, the characterization for location estimation can be more efficient and accurate.

• East Asian mathematical journal
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• v.34 no.5
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• pp.661-681
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• 2018

In this paper, we discuss a reduced-order modeling for the Benjamin-Bona-Mahony-Burgers (BBMB) equation and its application to a distributed feedback control problem through the centroidal Voronoi tessellation (CVT). Spatial distcritization to the BBMB equation is based on the finite element method (FEM) using B-spline functions. To determine the basis elements for the approximating subspaces, we elucidate the CVT approaches to reduced-order bases with snapshots. For the purpose of comparison, a brief review of the proper orthogonal decomposition (POD) is provided and some numerical experiments implemented including full-order approximation, CVT based model, and POD based model. In the end, we apply CVT reduced-order modeling technique to a feedback control problem for the BBMB equation.

• Journal of the Optical Society of Korea
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• v.5 no.1
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• pp.9-15
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• 2001

The ocean Scanning Multi-spectral Imager (OSMI) is a payload on the KOrea Multi-Purpose SATellite (KOMPSAT) to perform worldwide ocean color monitoring f the study of biological oceanography. OSMI performs solar and dark calibrations for on-orbit instrument calibration. The purpose of the solar calibration is to monitor the degradation of imaging performance for each pixel of 6 spectral bands and to correct the degradation effect on OSMI image during the ground station date processing. The design, the operation concept, and the radiometric characteristics of the solar calibration are investigated. A linear model of image response and a solar calibration radiance model are proposed to study the instrument characteristics using the solar calibration data. The performance of spectral responsivity and spatial response uniformity. The first solar calibration data and the analysis results are important references for further study on the on-orbit stability of OSMI response during its lifetime.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.164-173
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• 2017

Alternative cropping systems would be one of climate change adaptation options. Suitable areas for a crop could be identified using a climate suitability model. The EcoCrop model has been used to assess climate suitability of crops using monthly climate surfaces, e.g., the digital climate map at high spatial resolution. Still, a high-performance computing approach would be needed for assessment of climate suitability to take into account a complex terrain in Korea, which requires considerably large climate data sets. The objectives of this study were to implement a script for R, which is an open source statistics analysis platform, in order to use the EcoCrop model under a parallel computing environment and to assess climate suitability of maize using digital climate maps at high spatial resolution, e.g., 1 km. The total running time reduced as the number of CPU (Central Processing Unit) core increased although the speedup with increasing number of CPU cores was not linear. For example, the wall clock time for assessing climate suitability index at 1 km spatial resolution reduced by 90% with 16 CPU cores. However, it took about 1.5 time to compute climate suitability index compared with a theoretical time for the given number of CPU. Implementation of climate suitability assessment system based on the MPI (Message Passing Interface) would allow support for the digital climate map at ultra-high spatial resolution, e.g., 30m, which would help site-specific design of cropping system for climate change adaptation.

• Korean Journal of Remote Sensing
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• v.32 no.6
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• pp.741-746
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• 2016

Albedo is one of the climate variables that modulate absorption of solar energy, and its retrieval is important process for climate change study. High spatial resolution and long-term consistent periods are important considerations in order to efficiently use the retrieved albedo data. This study retrieved surface broadband albedo based on Landsat 8 as high resolution which is consistent with Landsat 7. First of all, we analyzed consistency of Landsat 7 channel and Landsat 8 channel. As a result, correlation coefficient(R) on all channels is average 0.96. Based on this analysis, we used multiple linear regression model using Landsat 7 albedo, which is being used in many studies, and Landsat 8 reflectance channel data. The regression coefficients of each channel calculated by regression analysis were used to derive a formula for converting the Landsat 8 reflectance channel data to broadband albedo. After Landsat 8 albedo calculated using the derived formula is compared with Landsat 7 albedo data, we confirmed consistency of two satellite using Root Mean Square Error (RMSE), R-square ($R^2$) and bias. As a result, $R^2$ is 0.89 and RMSE is 0.003 between Landsat 7 albedo and Landsat 8 albedo.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.5
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• pp.1-11
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• 2020

Image-based virtual try-on (VTON) is becoming popular for online apparel shopping, mainly because of not requiring 3D information for try-on clothes and target humans. However, existing 2D algorithms, even when utilizing advanced non-rigid deformation algorithms, cannot handle large spatial transformations for complex target human poses. In this study, we propose a 3D clothing reconstruction method using a 3D human body model. The resulting 3D models of try-on clothes can be more easily deformed when applied to rest posed standard human models. Then, the poses and shapes of 3D clothing models can be transferred to the target human models estimated from 2D images. Finally, the deformed clothing models can be rendered and blended with target human representations. Experimental results with the VITON dataset used in the previous works show that the shapes of reconstructed clothing are significantly more natural, compared to the 2D image-based deformation results when human poses and shapes are estimated accurately.