• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.2
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• pp.11-22
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• 2007

This paper is to discuss analytical techniques to estimate demand sizes and volumes that determine optimal locations for multiple facilities for a given services. While demand size estimation is a core part of location modeling to enhance solution quality and practical applicability, the estimation method has been used in limited and restrict parts such as a single population centroid in a given larger census boundary area or small theoretical application experiments(e.s. census track and enumeration district). Therefore, this paper strives to develop an analytical estimation method of demand size that converts area based demand data to point based population weighted centroids. This method is free to spatial boundary units and more robust to estimate accurate demand volumes regardless of geographic boundaries. To improve the estimation accuracy, this paper uses house weighted value to the population centroid calculation process. Then the population weighted centroids are converted to individual demand points on a grid formated surface area. In turn, the population weighted centroids, demand points and network distance measures are operated into location-allocation models to examine their roles to enhance solution quality and applicability of GIS location models. Finally, this paper demonstrates the robustness of the weighted estimation method with the application of location-allocation models.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.5
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• pp.299-308
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• 2022

This study was conducted to predict the tendency for heat exchange and boil-off gas (BOG) in a liquefied hydrogen tank under sloshing excitation. First, athe fluid domain excited by sloshing was modeled using a multiphase-thermal flow domain in which liquid hydrogen and hydrogen gas are in the saturated state. Both the the volume of fluid (VOF) and Eulerian-based multi-phase flow methods were applied to validate the accuracy of the pressure prediction. Second, it was indirectly shown that the fluid velocity prediction could be accurate by comparing the free surface and impact pressure from the computational fluid dynamics with those from the experimental results. Thereafter, the heat ingress from the external convective heat flux was reflected on the outer surfaces of the hydrogen tank. Eulerian-based multiphase-heat flow analysis was performed for a two-dimensional Type-C cylindrical hydrogen tank under rotational sloshing motion, and an inflation technique was applied to transform the fluid domain into a computational grid model. The heat exchange and heat flux in the hydrogen liquid-gas mixture were calculated throughout the analysis,, whereas the mass transfer and vaporization models were excluded to account for the pure heat exchange between the liquid and gas in the saturated state. In addition, forced convective heat transfer by sloshing on the inner wall of the tank was not reflected so that the heat exchange in the multiphase flow of liquid and gas could only be considered. Finally, the effect of sloshing on the amount of heat exchange between liquid and gas hydrogen was discussed. Considering the heat ingress into liquid hydrogen according to the presence/absence of a sloshing excitation, the amount of heat flux and BOG were discussed for each filling ratio.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.45-52
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• 2023

The power generation method using expensive diesel has operation problems such as high cost diesel generator and a lack of reserved power due to increase of power demand in some islands, requiring expansion of power generation facilities. To solve this problems, it is necessary to improve the efficiency of power generation facilities through an ORC(Organic Rankin Cycle) system application that uses waste heat as a heat source. Therefore, localized application technology of price competitive and highly reliable ORC power generation system is needed, and optimization technology of generators is having great effect, so this study performed two generator designs to get a high-efficiency generator with an optimized 30kW output. The comparison of simulation data for two designed models showed that a generator with SPM factor of 46.2% had an efficiency of 92.1% and a power ouput of about 23.2kW based on 12,000rpm, a generator with SPM factor of 44.46%, had a power output of 27.9kW and efficiency of 93.6% based on above rpm. For the verification of improved design model with SPM factor of 44.46%, the prototype test system with 110kW motor dynamometer was installed and got to the efficiency of 92.08% with conditions of the rated capacity 25kW at 12,000rpm, the test results of prototype generator showed the validity of generator design.

• Journal of Korea Water Resources Association
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• v.56 no.2
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• pp.75-89
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• 2023

As the Mekong River basin is a nationally shared river, it is difficult to collect precipitation data, and the quantitative and qualitative quality of the data sets differs from country to country, which may increase the uncertainty of hydrological analysis results. Recently, with the development of remote sensing technology, it has become easier to obtain grid-based precipitation products(GPPs), and various hydrological analysis studies have been conducted in unmeasured or large watersheds using GPPs. In this study, rainfall-runoff simulation in the Mekong River basin was conducted using the SWAT model, which is a quasi-distribution model with three satellite GPPs (TRMM, GSMaP, PERSIANN-CDR) and two GPPs (APHRODITE, GPCC). Four water level stations, Luang Prabang, Pakse, Stung Treng, and Kratie, which are major outlets of the main Mekong River, were selected, and the parameters of the SWAT model were calibrated using APHRODITE as an observation value for the period from 2001 to 2011 and runoff simulations were verified for the period form 2012 to 2013. In addition, using the ConvAE, a convolutional neural network model, spatio-temporal correction of original satellite precipitation products was performed, and rainfall-runoff performances were compared before and after correction of satellite precipitation products. The original satellite precipitation products and GPCC showed a quantitatively under- or over-estimated or spatially very different pattern compared to APHPRODITE, whereas, in the case of satellite precipitation prodcuts corrected using ConvAE, spatial correlation was dramatically improved. In the case of runoff simulation, the runoff simulation results using the satellite precipitation products corrected by ConvAE for all the outlets have significantly improved accuracy than the runoff results using original satellite precipitation products. Therefore, the bias correction technique using the ConvAE technique presented in this study can be applied in various hydrological analysis for large watersheds where rain guage network is not dense.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.24 no.2
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• pp.208-225
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• 2019

To understand the mean surface circulation and surface currents in the East Sea, trajectories of surface drifters passed through the East Sea from 1991 to 2017 were analyzed. By analyzing the surface drifter trajectory data, the main paths of surface ocean currents were grouped and the variation in each main current path was investigated. The East Korea Warm Current (EKWC) heading northward separates from the coast at $36{\sim}38^{\circ}N$ and flows to the northeast until $131^{\circ}E$. In the middle (from $131^{\circ}E$ to $137^{\circ}E$) of the East Sea, the average latitude of the currents flowing eastward ranges from 36 to $40^{\circ}N$ and the currents meander with large amplitude. When the average latitude of the surface drifter paths was in the north (south) of $37.5^{\circ}N$, the meandering amplitude was about 50 (100) km. The most frequent route of surface drifters in the middle of the East Sea was the path along $37.5-38.5^{\circ}N$. The surface drifters, which were deployed off the coast of Vladivostok in the north of the East Sea, moved to the southwest along the coast and were separated from the coast to flow southeastward along the cyclonic circulation around the Japan Basin. And, then, the drifters moved to the east along $39-40^{\circ}N$. The mean surface current vector and mean speed were calculated in each lattice with $0.25^{\circ}$ grid spacing using the velocity data of surface drifters which passed through each lattice. The current variance ellipses were calculated with $0.5^{\circ}$ grid spacing. Because the path of the EKWC changes every year in the western part of the Ulleung Basin and the current paths in the Yamato Basin keep changing with many eddies, the current variance ellipses are relatively large in these region. We present a schematic map of the East Sea surface current based on the surface drifter data. The significance of this study is that the surface ocean circulation of the East Sea, which has been mainly studied by numerical model simulations and the sea surface height data obtained from satellite altimeters, was analyzed based on in-situ Lagrangian observational current data.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1505-1514
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• 2022

Image matching is a crucial preprocessing step for effective utilization of multi-temporal and multi-sensor very high resolution (VHR) satellite images. Deep learning (DL) method which is attracting widespread interest has proven to be an efficient approach to measure the similarity between image pairs in quick and accurate manner by extracting complex and detailed features from satellite images. However, Image matching of VHR satellite images remains challenging due to limitations of DL models in which the results are depending on the quantity and quality of training dataset, as well as the difficulty of creating training dataset with VHR satellite images. Therefore, this study examines the feasibility of DL-based method in matching pair extraction which is the most time-consuming process during image registration. This paper also aims to analyze factors that affect the accuracy based on the configuration of training dataset, when developing training dataset from existing multi-sensor VHR image database with bias for DL-based image matching. For this purpose, the generated training dataset were composed of correct matching pairs and incorrect matching pairs by assigning true and false labels to image pairs extracted using a grid-based Scale Invariant Feature Transform (SIFT) algorithm for a total of 12 multi-temporal and multi-sensor VHR images. The Siamese convolutional neural network (SCNN), proposed for matching pair extraction on constructed training dataset, proceeds with model learning and measures similarities by passing two images in parallel to the two identical convolutional neural network structures. The results from this study confirm that data acquired from VHR satellite image database can be used as DL training dataset and indicate the potential to improve efficiency of the matching process by appropriate configuration of multi-sensor images. DL-based image matching techniques using multi-sensor VHR satellite images are expected to replace existing manual-based feature extraction methods based on its stable performance, thus further develop into an integrated DL-based image registration framework.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1009-1029
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• 2023

Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R² of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R² of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.

• Journal of Korean Society of Transportation
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• v.29 no.5
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• pp.121-138
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• 2011

More affordable and available cutting-edge technologies (e.g., wireless vehicle communication) are regarded as a possible alternative to the fixed infrastructure-based traffic information system requiring the expensive infrastructure investments and mostly implemented in the uninterrupted freeway network with limited spatial system expansion. This paper develops an advanced decentralized traveler information System (ATIS) using vehicle-to-vehicle (V2V) communication system whose performance (drivers' travel time savings) are enhanced by three complementary functions (autonomous automatic incident detection algorithm, reliable sample size function, and driver behavior model) and evaluates it in the typical $6{\times}6$ urban grid network with non-recurrent traffic state (traffic incident) with the varying key parameters (traffic flow, communication radio range, and penetration ratio), employing the off-the-shelf microscopic simulation model (VISSIM) under the ideal vehicle communication environment. Simulation outputs indicate that as the three key parameters are increased more participating vehicles are involved for traffic data propagation in the less communication groups at the faster data dissemination speed. Also, participating vehicles saved their travel time by dynamically updating the up-to-date traffic states and searching for the new route. Focusing on the travel time difference of (instant) re-routing vehicles, lower traffic flow cases saved more time than higher traffic flow ones. This is because a relatively small number of vehicles in 300vph case re-route during the most system-efficient time period (the early time of the traffic incident) but more vehicles in 514vph case re-route during less system-efficient time period, even after the incident is resolved. Also, normally re-routings on the network-entering links saved more travel time than any other places inside the network except the case where the direct effect of traffic incident triggers vehicle re-routings during the effective incident time period and the location and direction of the incident link determines the spatial distribution of re-routing vehicles.

• Korean Journal of Environment and Ecology
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• v.30 no.2
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• pp.173-184
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• 2016

Knowledge of the relationships among interspecific competition, spatial distributions and ecological niches plays an important role in understanding biogeographical distribution patterns of species. In this study, the distributional characteristics and ecological niches of the three Viperidae species (Gloydius ussuriensis, G. brevicaudus, and G. saxatilis) in South Korea were determined based on observation data and species distribution model. The effects of interspecific competition on geographical distribution and the division of the ecological niches of the vipers were also examined based on the models of predicted species distribution. The results showed that altitude was the most important environmental variable for their distribution, and the altitudes at which these snakes were distributed correlated with the climate of that region. Although interspecific ecological niches are quite overlapped, their predicted distribution patternsvary by the Taebaek Mountains. When overlaying the distribution models, most of the overlapping habitats were forest areas, which were relatively less overlapped than were the entire research areas. Thus, a parapatric distribution pattern was expected. The abundance of species occurring sympatrically was positively correlated with each other, indicating the lack of serious interspecies competition in this region. In conclusion, although the three Viperidae species in South Korea occupy similar ecological niches, these snakes exhibit parapatric distribution patterns without direct competition. Further research on various geographic variables (e.g., altitude, microhabitat characteristics) using relatively fine grid sizes, as well as further detailed ecological and behavioral research, is needed to determine the causative factors for the parapatric distribution pattern.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.4
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• pp.126-138
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• 2017

Recently, the national interest in environment is increasing and for dealing with water environment-related issues swiftly and accurately, the demand to facilitate the analysis of water environment data using a GIS is growing. To meet such growing demands, a spatial network data-based stream network analysis map(Korean Reach File; KRF) supporting spatial analysis of water environment data was developed and is being provided. However, there is a difficulty in delineating catchment areas, which are the basis of supplying spatial data including relevant information frequently required by the users such as establishing remediation measures against water pollution accidents. Therefore, in this study, the development of a computer program was made. The development process included steps such as designing a delineation method, and developing an algorithm and modules. DEM(Digital Elevation Model) and FDR(Flow Direction) were used as the major data to automatically delineate catchment areas. The algorithm for the delineation of catchment areas was developed through three stages; catchment area grid extraction, boundary point extraction, and boundary line division. Also, an add-in catchment area delineation module, based on ArcGIS from ESRI, was developed in the consideration of productivity and utility of the program. Using the developed program, the catchment areas were delineated and they were compared to the catchment areas currently used by the government. The results showed that the catchment areas were delineated efficiently using the digital elevation data. Especially, in the regions with clear topographical slopes, they were delineated accurately and swiftly. Although in some regions with flat fields of paddles and downtowns or well-organized drainage facilities, the catchment areas were not segmented accurately, the program definitely reduce the processing time to delineate existing catchment areas. In the future, more efforts should be made to enhance current algorithm to facilitate the use of the higher precision of digital elevation data, and furthermore reducing the calculation time for processing large data volume.