• Journal of Korean Society for Atmospheric Environment
• /
• v.13 no.6
• /
• pp.463-474
• /
• 1997

Metallic elements in dustfall have been known as notable air pollutants directly or indirectly influencing human health and wealth. The first aim of this study was to obtain precise spatial distribution patterns of 5 elements (Pb, Zn, K, Cr, and Al) in dustfall around Suwon area. To predict isometric lines of metal fluxes deposited on unsupervised random sites, the study has applied both spatial statistics as a receptor model and a GIS (geographic information system). Total of 31 sampling sites were selected in the study area (roughly 3 by 3 km grid basis) and dustfall samples were then collected monthly basis by the British deposit gauges from Dec., 1995 to Nov., 1996. The metallic elements in the dustfall were then analyzed by an atomic absorption spectrometer (AAS). On the other hand, a base map overlapped by 7 layers was constructed by using the AutoCAD R13 and ARC/INFO 3.4D. Four different spatial interpolation and expolation techniques such as IDW (inverse distance weighted averaging), TIN (triangulated irregular network), polynomial regression, and kriging technique were examined to compare spatial distribution patterns. Each pattern obtained by each technique was substantally different as varing pollutant types, land of use types, and topological conditions, etc. Thus, our study focused intensively on uncertainty analysis based on a concept of the jackknife and the sum of error distance. It was found that a kriging technique was the best applicalbe in this study area.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2023.05a
• /
• pp.27-27
• /
• 2023

To analyze the evolution of water resources in Qiandao Lake Basin under the condition of climate change, a WEP-L distributed hydrological model was established to simulate the water cycle process in the basin during 1960-2020. The Mann-Kendall non-parametric test method and Hurst index method were used to analyze the inter-annual variation and annual distribution characteristics of the total water resources in the basin. The multi-scale temporal and spatial distribution and evolution trend of water resources in Qiandao Lake Basin were evaluated. The results show that: (1) The WEP-L model has good simulation results in the Qiandao Lake basin, and the Nash coefficient rate is above 0.83 in the periodic period and above 0.85 in the verification period. (2) The water yield coefficient of the whole basin ranges from 0.436 to 0.630. The annual average total water resource is 12.25 billion m³, equivalent to 1176.4mm of water depth. The annual distribution process shows a unimodal structure, and the water depth of each sub-basin ranges from 742 mm to 1266 mm, and the spatial distribution is higher in the west and lower in the east. (3) The annual water resources series in the basin showed an insignificant upward trend, and the Hurst index was 0.86, indicating a continuous upward trend. From the perspective of monthly water resources, January and February increased significantly, the other months were not significant changes.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.38 no.2
• /
• pp.141-151
• /
• 2020

Since it was first studied in 1980, solar energy analysis model for geographic information systems has been used to determine the approximate spatial distribution of terrain. However, the spatial pattern was not able to be grasped in 3D (three-dimensional) space with low accuracy due to the limitation of input data. Because of computational efficiency, using a constant value for the brightness of the sky caused the simulation results to be less reliable especially when the slope is high or buildings are crowded around. For the above reasons, this study proposed a model that predicts solar energy of vertical surfaces of buildings with four stages below. Firstly, CIE (Commission Internationale de l'Eclairage) luminance distribution model was used to calculate the brightness distribution of the sky using NREL (National Renewable Energy Laboratory) solar tracking algorithm. Secondly, we suggested a method of calculating the shadow effect using ray tracing. Thirdly, LOD (Level of Detail) 3 of 3D spatial data was used as input data for analysis. Lastly, the accuracy was evaluated based on the atmospheric radiation data collected through the ground observation equipment in Daejeon, South Korea. As a result of evaluating the accuracy, NMBE was 5.14%, RMSE 11.12, and CVRMSE 7.09%.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.24 no.2
• /
• pp.64-77
• /
• 2021

The purpose of this study is to examine the spatial distribution of highly educated human capital and to identify key factors affecting their spatial distribution. We analyzed the spatial concentration and inequality using Gini's coefficient and exploratory spatial data analysis and identified the economic and amenity factors to affect the spatial concentration of highly educated human capital using spatial regression model. The findings show that the spatial pattern of highly educated human capital is concentrated, imbalanced, and clustered in Capital region and part of Chungcheong and Gangwon region. The spatial concentration were more affected by economic factor than by amenity factors. This study provides some implication on the regional economic strategies to attract the human capital.

• Journal of Ecology and Environment
• /
• v.43 no.2
• /
• pp.191-201
• /
• 2019

Macroecologists and biogeographers continue to predict the distribution of species across space based on the relationship between biotic processes and environmental variables. This approach uses data related to, for example, species abundance or presence/absence, climate, geomorphology, and soils. Researchers have acknowledged in their statistical analyses the importance of accounting for the effects of spatial autocorrelation (SAC), which indicates a degree of dependence between pairs of nearby observations. It has been agreed that residual spatial autocorrelation (rSAC) can have a substantial impact on modeling processes and inferences. However, more attention should be paid to the sources of rSAC and the degree to which rSAC becomes problematic. Here, we review previous studies to identify diverse factors that potentially induce the presence of rSAC in macroecological and biogeographical models. Furthermore, an emphasis is put on the quantification of rSAC by seeking to unveil the magnitude to which the presence of SAC in model residuals becomes detrimental to the modeling process. It turned out that five categories of factors can drive the presence of SAC in model residuals: ecological data and processes, scale and distance, missing variables, sampling design, and assumptions and methodological approaches. Additionally, we noted that more explicit and elaborated discussion of rSAC should be presented in species distribution modeling. Future investigations involving the quantification of rSAC are recommended in order to understand when rSAC can have an adverse effect on the modeling process.

• Journal of the Korean Geographical Society
• /
• v.39 no.3
• /
• pp.360-373
• /
• 2004

The purpose of this study is establishing how to build the area of local agents and regional offices in the oil company using GIS technique by reviewing on the spatial distribution pattern and characteristics of the sales area of oil products. Location-allocation and spatial interaction model are cooperated in order to establish sales area of petroleum products distribution system. Location-allocation model is used in the capital region where local agents are concentrated on like Kyoung-gi local agent. Spatial interaction model is used in the rest of the area in Korea to analyze the sales range of the regional offices in oil company. Each office made a big difference in registered cars and population because of the level of petroleum consumption in each sales area.

• Advances in Computational Design
• /
• v.8 no.3
• /
• pp.219-236
• /
• 2023

In this paper, finite element modeling of the laser ultrasonics (LU) process in ablation regime is of interest. The momentum resulting from the removal of material from the specimen surface by the laser beam radiation in ablation regime is modeled as a pressure pulse. To model this pressure pulse, two equations are required: one for the spatial distribution and one for the temporal distribution of the pulse. Previous researchers have proposed various equations for the spatial and temporal distributions of the pressure pulse in different laser applications. All available equations are examined and the best combination of the temporal and spatial distributions of the pressure pulse that provides the most accurate results is identified. This combination of temporal and spatial distributions has never been used for modeling laser ultrasonics before. Then by using this new model, the effects of variations in pulse duration and laser spot radius on the shape, amplitude, and frequency spectrum of ultrasonic waves are studied. Furthermore, the LU in thermoelastic regime is simulated by this model and compared with LU in ablation regime. The interaction of ultrasonic waves with a defect is also investigated in the LU process in ablation regime. Good agreement of the results obtained from the new finite element model and available experimental data confirms the accuracy of the proposed model.

• New & Renewable Energy
• /
• v.7 no.1
• /
• pp.22-28
• /
• 2011

The surface solar radiations were calculated and analyzed with spatial resolutions (4 km and 1 km) using by GWNU (Gangneung-Wonju National University) solar radiation model. The GWNU solar radiation model is used various data such as aerosol optical thickness, ozone amount, total precipitable water and cloud factor are retrieved from Moderate Resolution Imaging Spectrometer (MODIS), Ozone Monitoring Instrument (OMI), MTSAT-1R satellite data and output of the Regional Data Assimilation Prediction System(RDAPS) model by Korea Meteorological Administration (KMA), respectively. The differences of spatial resolutions were analyzed with input data (especially, cloud factor from MTSAT-1R satellite). And the Maximum solar radiation by GWNU model were found in Andong, Daegu and Jinju regions and these results were corresponded with the MTSAT-1R cloud factor.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.53 no.11
• /
• pp.604-609
• /
• 2004

This paper suggests a long-term distribution area load forecasting algorithm which offers basic data for distribution planning of power system. To build forecasting model, 4-level hierarchical spatial structure is introduced: System, Region, Area, and Substation. And, each spatial load can be decided proportional to its portion in the higher level. This paper introduces the horizon year loads to improve the forecasting results. And, this paper also introduces an effective load transfer algorithm to improve forecasting stability in case of new or stopped substations. The proposed model is applied to the load forecasting of KEPCO system composed of 16 regions, 85 areas and 761 substations, and the results are compared with those of econometrics model to verify its validity.

• Korean Journal of Remote Sensing
• /
• v.19 no.3
• /
• pp.247-253
• /
• 2003

The mainly used technique to correct satellite images with geometric distortion is to develop a mathematical relationship between pixels on the image and corresponding points on the ground. Polynomial models with various transformations have been designed for defining the relationship between two coordinate systems. GCP based geometric correction has peformed overall plane to plane mapping. In the overall plane mapping, overall structure of a scene is considered, but local variation is discarded. The Region with highly variant height is rectified with distortion on overall plane mapping. To consider locally variable region in satellite image, TIN-based rectification on a satellite image is proposed in this paper. This paper describes the relationship between GCP distribution and rectification model through experimental result and analysis about each rectification model. We can choose a geometric correction model as the structural characteristic of a satellite image and the acquired GCP distribution.