• Journal of the Korean Mathematical Society
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• v.60 no.2
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• pp.273-302
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• 2023

In this paper, a fully discrete numerical scheme for the viscoelastic Oldroyd flow is considered with an introduced auxiliary variable. Our scheme is based on the finite element approximation for the spatial discretization and the backward Euler scheme for the time discretization. The integral term is discretized by the right trapezoidal rule. Firstly, we present the corresponding equivalent form of the considered model, and show the relationship between the origin problem and its equivalent system in finite element discretization. Secondly, unconditional stability and optimal error estimates of fully discrete numerical solutions in various norms are established. Finally, some numerical results are provided to confirm the established theoretical analysis and show the performances of the considered numerical scheme.

• The Journal of Bigdata
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• v.8 no.2
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• pp.97-107
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• 2023

Small business owners are relatively likely to be alienated from various benefits caused by the change to a big data/AI-based society. To support them, we would like to detect a hot place based on the floating population to support small business owners' decision-making in the start-up area. Through various studies, it is known that the population size of the region has an important effect on the sales of small business owners. In this study, inland regions were extracted from the Incheon floating population data from January 2019 to June 2022. the Data is consisted of a grid of 50m intervals, central coordinates and the population for each grid are presented, made image structure through imputation to maintain spatial information. Spatial outliers were removed and imputated using LOF and GAM, and temporal outliers were removed and imputated through LOESS. We used ConvLSTM which can take both temporal and spatial characteristics into account as a predictive model, and used AutoEncoder structure, which performs outliers detection based on reconstruction error to define an area with high MAPE as a hot place.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.4
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• pp.124-137
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• 2018

The main purpose of this study is to find the hotspots of crimes that occur frequently in the space and to derive the appropriate CCTV installation location. One of the characteristics of crime is clustered around past occurrence area, and these crimes are strongly correlated. It is also possible to find the cause of the clusters and the variables that affect the crime through the history of the crime. In addition to the traditional OLS model, spatial differential model including spatial autocorrelation and spatial error model were used to select the variables influencing the five major crime rate, the theft rate and the foreign resident rate. The variables affecting the Five major crimes were positive (+) sign for the welfare and the rate of the bar cluster rate, and negative (-) for the street density. The CCTV area occupies 46% of the hotspots based on the overlapping of the areas where the elderly people are crowded, the bar cluster, many multicultural families, and the areas with low density of street lamps. It turned out. Taking into account the current CCTV operation, the total number of new cases to cover the risk point was 89.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.577-587
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• 2023

The utilization of crowdsourced spatial data has been actively researched; however, issues stemming from the uncertainty of data quality have been raised. In particular, when low-quality data is mixed into drone imagery datasets, it can degrade the quality of spatial information output. In order to address these problems, the study presents a methodology for automatically validating the geometric quality of crowdsourced imagery. Key quality factors such as spatial resolution, resolution variation, matching point reprojection error, and bundle adjustment results are utilized. To classify imagery suitable for spatial information generation, training and validation datasets are constructed, and machine learning is conducted using a radial basis function (RBF)-based support vector machine (SVM) model. The trained SVM model achieved a classification accuracy of 99.1%. To evaluate the effectiveness of the quality validation model, imagery sets before and after applying the model to drone imagery not used in training and validation are compared by generating orthoimages. The results confirm that the application of the quality validation model reduces various distortions that can be included in orthoimages and enhances object identifiability. The proposed quality validation methodology is expected to increase the utility of crowdsourced data in spatial information generation by automatically selecting high-quality data from the multitude of crowdsourced data with varying qualities.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.3
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• pp.3-9
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• 2016

UAV(unmanned aerial vehicle) can quickly produce orthoimage with high-spatial resolution and DSM(digital surface model) at low cost. However, vertical and horizontal positioning accuracy of orthoimage and DSM, which are obtained by UAV, are influenced by image processing techniques, quality of aerial photo, the number and position of GCPs(ground control points) and overlap in flight plan. In this study, effects of overlap and the number of GCPs are analyzed in orthoimage and DSM. Positioning accuracy are estimated based on RMSE(root mean square error) by using dataset of nine pairs. In the experiments, Overlaps and the number of GCPs have influence on horizontal and vertical accuracy of orthoimage and DSM.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.525-533
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• 2019

There are two feature collection methods in digital mapping using the UAV (Unmanned Aerial Vehicle) Photogrammetry: vectorization and stereo plotting. In vectorization, planar information is extracted from orthomosaics and elevation value obtained from a DSM (Digital Surface Model) or a DEM (Digital Elevation Model). However, the exact determination of the positional accuracy of 3D features such as ground facilities and buildings is very ambiguous, because the accuracy of vectorizing results has been mainly analyzed using only check points placed on the ground. Thus, this study aims to review the possibility of 3D spatial information acquisition and digital map production of vectorization by analyzing the corner point coordinates of different layers as well as check points. To this end, images were taken by a Phantom 4 (DJI) with 3.6 cm of GSD (Ground Sample Distance) at altitude of 90 m. The outcomes indicate that the horizontal RMSE (Root Mean Square Error) of vectorization method is 0.045 cm, which was calculated from residuals at check point compared with those of the field survey results. It is therefore possible to produce a digital topographic (plane) map of 1:1,000 scale using ortho images. On the other hand, the three-dimensional accuracy of vectorization was 0.068~0.162 m in horizontal and 0.090~1.840 m in vertical RMSE. It is thus difficult to obtain 3D spatial information and 1:1,000 digital map production by using vectorization due to a large error in elevation.

• Journal of The Korean Society of Agricultural Engineers
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• v.47 no.5
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• pp.3-13
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• 2005

The present study examined the 3 dimensional space distribution characteristics of sea water intrusion using data available from previous observations. For this study, we used 3D FEMWATER, which is a 3 dimensional finite element model. The target area was around Daechang-ri, Gimje-si, Jeollabuk-do. The area is relatively easy to formulate a conceptual model and has observation wells in operation for surveying sea water intrusion. Considering the uncertainty of numerical simulation, we analyzed sensitivity to hydraulic conductivity, which has a relatively higher effect. According to the result of the analysis, the variation of TDS concentration had an error range of $-1,336{\~}+107 mg/{\iota}$. Taking note that the survey data from observation wells were collected when the boundary between fresh water and sea water in the aquifer was in equilibrium, we set the range of time for numerical simulation and estimated the spatial distribution of TDS concentration as the range of sea water intrusion. According to the result of estimation, the spatial distribution of TDS concentration calculated when 1,440 days were simulated was taken as the range of sea water intrusion. Using the result of calculation, we can draw not only vertical views for a certain section but also horizontal views of different depth. These views will be greatly helpful in understanding the spatial distribution of the range of sea water intrusion. In addition, the result of this study can be used rationally in proposing an optimal quantity of water pumping through investigating the moving route of sea water intrusion over time in order to prevent excessive water pumping and to maintain an optimal number of water pumping wells per interval.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.2
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• pp.71-79
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• 2009

In this study, a distributed rainfall-runoff model, K-DRUM, based on physical kinematic wave was developed to simulate temporal and spatial distribution of flood discharge considering grid rainfall and grid based GIS hydrological parameters. The developed model can simulate temporal and spatial distribution of surface flow and sub-surface flow during flood period, and input parameters of ASCII format as pre-process can be extracted using ArcView. Output results of ASCII format as post-process can be created to express distribution of discharge in the watershed using GIS and express discharge as animation using TecPlot. an auto calibration method for initial soil moisture conditions that have an effect on discharge in the physics based K-DRUM was additionally developed. The baseflow for Namgang Dam Watershed was analysed to review the applicability of the developed auto calibration method. The accuracy of discharge analysis for application of the method was evaluated using RMSE and NRMSE. Problems in running time and inaccuracy setting using the existing trial and error method were solved by applying an auto calibration method in setting initial soil moisture conditions of K-DRUM.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.6
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• pp.101-112
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• 2013

Shuttle Radar Topography Mission Digital Elevation Model (SRTM DEM) offers opportunities to make advances in many research areas including hydrology by providing near-global scale elevation measurements at a uniform resolution. Its wide coverage and complimentary online access especially benefits researchers requiring topographic information of hard-to-access areas. However, SRTM DEM also contains inherent errors, which are subject to propagation with its manipulation into analysis outputs. Sensitivity of hydrologic analysis to the errors has not been fully understood yet. This study investigated their impact on estimation of hydrologic derivatives such as slope, stream network, and watershed boundary using Monte Carlo simulation and spatial moving average techniques. Different amount of the errors and their spatial auto-correlation structure were considered in the study. Two sub-watersheds of Geum and Deadong River areas located in South and North Korea, respectively, were selected as the study areas. The results demonstrated that the spatial presentations of stream networks and watershed boundaries and their length and area estimations could be greatly affected by the SRTM DEM errors, in particular relatively flat areas. In the Deadong River area, artifacts of the SRTM DEM created sinks even after the filling process and then closed drainage basin and short stream lines, which are not the case in the reality. These findings provided an evidence that SRTM DEM alone may not enough to accurately figure out the hydrologic feature of a watershed, suggesting need of local knowledge and complementary data.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.727-731
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• 2003

ASTER image has some advantages for classification such as 15 spectral bands and 15m ${\sim}$ 90m spatial resolution. However, in the classification using general remote sensing image, shadow areas are often classified into water area. It is very difficult to divide shadow and water. Because reflectance characteristics of water is similar to characteristics of shadow. Many land cover items are consisted in one pixel which is 15m spatial resolution. Nowadays, very high resolution satellite image (IKONOS, Quick Bird) and Digital Surface Model (DSM) by air borne laser scanner can also be used. In this study, mixed pixel analysis of ASTER image has carried out using IKONOS image and DSM. For mixed pixel analysis, high accurated geometric correction was required. Image matching method was applied for generating GCP datasets. IKONOS image was rectified by affine transform. After that, one pixel in ASTER image should be compared with corresponded 15×15 pixel in IKONOS image. Then, training dataset were generated for mixed pixel analysis using visual interpretation of IKONOS image. Finally, classification will be carried out based on Linear Mixture Model. Shadow extraction might be succeeded by the classification. The extracted shadow area was validated using shadow image which generated from 1m${\sim}$2m spatial resolution DSM. The result showed 17.2% error was occurred in mixed pixel. It might be limitation of ASTER image for shadow extraction because of 8bit quantization data.