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

• Journal of the Korean Geographical Society
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• v.48 no.1
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• pp.37-55
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• 2013

Previous studies have shown that Foehn was mainly observed in Young-seo area in Korea. However, they have failed to indicate the area where Foehn can be observed most frequently in Young-seo area and how Foehn is distributed in that area. This study targets HongCheon area in Young-seo province and examines the frequency and extent of Foehn in local scale through documenting a daily maximum air temperature map of Foehn. The period examined in this study is the months between March and June from 2003 to 2012. CoKriging method, which uses temperature and the altitude above sea, generates a higher level of accuracy in making daily maximum air temperature map of Foehn occurring days. We have found that Foehn is observed in certain areas, not all areas of HongCheon region, by compiling the daily maximum air temperature map. In particular, Foehn was found to be frequent and strong in the downstream of HongCheon river. In addition, we surveyed the residents of HongCheon about their perception of Foehn. They did not know whether high temperature and dryness in spring are caused by Foehn. The methods and techniques used to examine Foehn in local climate scale by this study will enhance the understanding of regional climate and contribute towards the research in this area. In particular, they can be applied to high temperature that recently occurred between spring and summer, excessive hotness in summers, agricultural plant growth in springs and etc.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.22 no.3
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• pp.74-81
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• 2014

The coverage area of GNSS regional ionospheric correction model is mainly determined by the disribution of GNSS ground monitoring stations. Outside the coverage area, GNSS users may receive ionospheric correction signals but the correction does not contain valid correction information. Extrapolation of the correction information can extend the coverage area to some extent. Three interpolation methods, Kriging, biharmonic spline and cubic spline, are tested to evaluate the extrapolation accuracy of the ionospheric delay corrections outside the correction coverage area. IGS (International GNSS Service) ionosphere map data is used to simulate the corrections and to compute the extrapolation error statistics. Among the three methods, biharmonic method yields the best accuracy. The estimation error has a high value during Spring and Fall. The error has a high value in South and East sides and has a low value in North side.

• Economic and Environmental Geology
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• v.32 no.5
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• pp.503-517
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• 1999

The purpose of this study is to verfify a more effecive techique for calculating geothermal gradient. this study examines 370 data of temperature-logging having been collected since 1985. The daya are divided into three different grades grades according to the type of temperature-depth plots: 204 data show typical linear gradient (Grade A); 126 data do not explicitily show the gradient becase of various external effects such as water flow (Grade B); and the rest 40 data do not show the gradient at all (Grade D). The new technique for calculating geothermal gradient is to be required to use Greade-B data more effctiviely. This new technique includes (1) calculating the independer depth of atmospheric temperature in the earth; (2) drawing a distribution map of subsurface tempurature by using the distribution map of subsurface temperature by using Grade-A data at the independent depth; and (3) recalculating geothermal gradient of Grade-B data by using the distrbution map of subsurface temperature, borehole depth, and bottom temperature of Grade-B data by using the distribution map of subsurface temperature, borehole depth, and bottom temperature of Grade-B data. As a result, 330 data-both Grade-A and Grade-B data--can be used to draw a distribution map of hot spradient. The map clearly distinguishes anomaly areas, and helps interpret their relations to the distribution of hot springs, geology, geological structures, and geophysical anomaly areas. These new results reveal that the average of geothermal in south Korea is 25.6$^{\circ}C$/km, when calculated to the Kriging method.

• Journal of the Korean Society of Groundwater Environment
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• v.1 no.2
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• pp.113-120
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• 1994

One of the delicate problems in aquifer management is the identification of the spatial distribution of tile hydrological parameters. The observed data are insufficient to identify the distribution of transmissivities in LAN aquifer. To determine the distribution of the transmissivity in LAN aquifer, it would be required to transform the observed heads at the pilot points into transmissivities. Therefore, three procedures wire tackled for the identification of the spatial distribution of the hydrological parameters; geostatistical estimate of the parameter field on the basis of known well point, heads reconstructed by a numerical model, and modification of the values at pilot points by a minimization algorithm. The variogram of Kriging has been applied to a total of 258 transmissivity value in attempt to quantify their distribution of LAN aquifer. Variogram of the observed and optimized transmissivities at pilot points are adapted to the exponential form. So, it is fitted by theoretical one with coefficients of w=0.623, a=2.743. Values of head obtained through numerical analysis are adjusted to the observed values so that heads have been transformed completely into the transmissivities at the observation wells. The procedure represented contour map of the estimated transmissivities and the calculated head.

• Journal of Information Processing Systems
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• v.11 no.4
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• pp.556-572
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• 2015

This paper presents the applications of spatial interpolation and assimilation methods for satellite and ground meteorological data, including temperature, relative humidity, and precipitation in regions of Vietnam. In this work, Universal Kriging is used for spatially interpolating ground data and its interpolated results are assimilated with corresponding satellite data to anticipate better gridded data. The input meteorological data was collected from 98 ground weather stations located all over Vietnam; whereas, the satellite data consists of the MODIS Atmospheric Profiles product (MOD07), the ASTER Global Digital Elevation Map (ASTER DEM), and the Tropical Rainfall Measuring Mission (TRMM) in six years. The outputs are gridded fields of temperature, relative humidity, and precipitation. The empirical results were evaluated by using the Root mean square error (RMSE) and the mean percent error (MPE), which illustrate that Universal Kriging interpolation obtains higher accuracy than other forms of Kriging; whereas, the assimilation for precipitation gradually reduces RMSE and significantly MPE. It also reveals that the accuracy of temperature and humidity when employing assimilation that is not significantly improved because of low MODIS retrieval due to cloud contamination.

• Korean Journal of Remote Sensing
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• v.26 no.1
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• pp.29-38
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• 2010

It is necessary to develop an integration model which can account for various data acquired at different measurement scales in environmental thematic mapping with high-resolution ground survey data and relatively low-resolution remote sensing data. This paper presents and applies a multi-scale geostatistical methodology for downscaling of thematic maps generated from lowresolution remote sensing data. This methodology extends a traditional ordinary kriging system to a block kriging system which can account for both ground data and remote sensing data which can be regarded as point and block data, respectively. In addition, stochastic simulation based on block kriging is also applied to describe spatial uncertainty attached to the downscaling. Two downscaling experiments including SRTM DEM and MODIS Leaf Area Index (LAI) products were carried out to illustrate the applicability of the geostatistical methodology. Through the experiments, multi-scale geostatistics based on block kriging successfully generated relatively high-resolution thematic maps with reliable accuracy. Especially, it is expected that multiple realizations generated from simulation would be effectively used as input data for investigating the effects of uncertain input data on GIS model outputs.

• Journal of the Korean Geotechnical Society
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• v.38 no.10
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• pp.17-29
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• 2022

Recently, the interest in integrated underground geospatial information mapping (IUGIM) to ensure the safety of underground spaces and facilities has been increasing. Because IUGIM is used in the fields of underground space development and underground safety management, the up-to-dateness and accuracy of information are critical. In this study, IUGIM and field data were classified, and the accuracy of IUGIM was improved by spatial interpolation. A spatial interpolation technique was used to process borehole data in IUGIM, and a quantitative evaluation was performed with mean absolute error and root mean square error through the cross-validation of seven interpolation results according to the technique and model. From the cross-validation results, accuracy decreased in the order of nonuniform rational B-spline, Kriging, and inverse distance weighting. In the case of Kriging, the accuracy difference according to the variogram model was insignificant, and Kriging using the spherical variogram exhibited the best accuracy.

• Economic and Environmental Geology
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• v.56 no.3
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• pp.331-341
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• 2023

When creating a soil contamination map using geostatistical techniques, there are various sources that can affect prediction errors. In this study, a grid-based soil contamination map was created from the sampling data of heavy metal concentrations in soil in abandoned mine areas using Ordinary Kriging. Five factors that were judged to affect the prediction error of the soil contamination map were selected, and the variation of the root mean squared error (RMSE) between the predicted value and the actual value was analyzed based on the Leave-one-out technique. Then, using a machine learning algorithm, derived the top three factors affecting the RMSE. As a result, it was analyzed that Variogram Model, Minimum Neighbors, and Anisotropy factors have the largest impact on RMSE in the Standard interpolation. For the variogram models, the Spherical model showed the lowest RMSE, while the Minimum Neighbors had the lowest value at 3 and then increased as the value increased. In the case of Anisotropy, it was found to be more appropriate not to consider anisotropy. In this study, through the combined use of geostatistics and machine learning, it was possible to create a highly reliable soil contamination map at the local scale, and to identify which factors have a significant impact when interpolating a small amount of soil heavy metal data.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.10a
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• pp.423-431
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• 2003

This study presents on generation coefficients of the RFM using GEO-level stereo images of the IKONOS satellite. 3-D positioning and DEM generation of this model on the test field. In result, the maximum error of image coordinates acquired by the upward transform of the RFM did nat exceed 8 pixels. DEM was generated with kriging interpolation extracted three dimensional ground coordinate to rational quadratic function form, me compared it to reference digital elevation model made from 1:5,000 digital map and 1:1,000 digital map, and so, could generate digital elevation model in the accuracy as average RMSE of elevation was ${\pm}$ 3∼5 m in RFM.