• Korean Journal of Soil Science and Fertilizer
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• v.17 no.3
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• pp.212-217
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• 1984

Spatial variabilities of particle size distribution of 96 samples from Hwadong SiCL and Jungdong Sl were studied by using geostatistical concepts. The measurement was made at the nodes of the regular grid consisting of 12 rows and 8 columns. Sample spacing within rows and columns was 3 and 2 meters, respectively. The results are summarized as follows. 1. Variograms of Hwadong SiCL were fitted for the linear model and those of Jungdong SL for the spherical model. 2. Variograms of properties for Hwadong and clay for Jungdong showed the pure nugget effect. Those of silt and clay for Jungdong, however, appeared the nugget effect. 3. The minimum number of samples necessary to reproduce results similar to the true mean of the 96 measured values was approximately estimated. The minimum sample sizes of silt, clay, and sand in Hwadong SiCL were 27, 13, and 6, respectively. And the minimum sample size of clay in Jungdong SL was 17. 4. The approximate number of samples required to detect the difference of 5% of the true mean with 0.95 confidence level was estimated. The resulting number of samples for silt and sand in Jungdong was 14, and 26, respectively.

• Journal of the Korean earth science society
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• v.32 no.6
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• pp.525-536
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• 2011

In any applications using various types of spatial data, it is very important to account for the scale differences among available data sets and to change the scale to the target one as well. In this paper, we propose to use a geostatistical downscaling approach based on vaiorgram deconvloution and block simulation to generate fine-scale categorical thematic maps from coarse-scale fraction data. First, an iterative variogram deconvolution method is applied to estimate a point-support variogram model from a block-support variogram model. Then, both a direct sequential simulation based on area-to-point kriging and the estimated point-support variogram are applied to produce alternative fine-scale fraction realizations. Finally, a maximum a posteriori decision rule is applied to generate the fine-scale categorical thematic maps. These analytical steps are illustrated through a case study of land-cover mapping only using the block fraction data of thematic classes without point data. Alternative fine-scale fraction maps by the downscaling method presented in this study reproduce the coarse-scale block fraction values. The final fine-scale land-cover realizations can reflect overall spatial patterns of the reference land-cover map, thus providing reasonable inputs for the impact assessment in change of support problems.

• Journal of Korea Water Resources Association
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• v.42 no.6
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• pp.465-480
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• 2009

In this study, single and multiple linear regression model were used to derive the relationship between precipitation and altitude, latitude and longitude in Jejudo. The single linear regression analysis was focused on whether orographic effect was existed in Jejudo by annual average precipitation, and the multiple linear regression analysis on whether orographic effect was applied to each duration and return period of quantile from regional frequency analysis by index flood method. As results of the regression analysis, it shows the relationship between altitude and precipitation strongly form a linear relationship as the length of duration and return period increase. The multiple linear regression precipitation estimates(which used altitude, latitude, and longitude information) were found to be more reasonable than estimates obtained using altitude only or altitude-latitude and altitude-longitude. Especially, as results of spatial distribution analysis by kriging method using GIS, it also provides realistic estimates for precipitation that the precipitation was occurred the southeast region as real climate of Jejudo. However, the accuracy of regression model was decrease which derived a short duration of precipitation or estimated high region precipitation even had long duration. Consequently the other factor caused orographic effect would be needed to estimate precipitation to improve accuracy.

• Geophysics and Geophysical Exploration
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• v.17 no.1
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• pp.28-33
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• 2014

We investigate the spatial distribution of highly conductive layer using the one-dimensional inversions of the new magnetotelluric (MT) measurements obtained at the mid-mountain (400 ~ 900 m in elevation) western area of Jeju Island and the previous MT data over Jeju Island, Korea. The conductive layer indicates the sedimentary layer comprised of Seoguipo Fomation and U Formation. There is a definite positive correlation between the top of conductive layer and the earth surface in elevation. On the contrary, the bottom of conductive layer has a negative correlation with the surface elevation. In other words, the conductive layer has a shape of convex lens, which is thickest in the central part. The basement beneath the conductive layer could be concave in the central part of Jeju Island. A kriging considering the correlation between the layer boundary and the surface elevation provides a reliable geoelectric structure model of Jeju Island. However, further studies, i.e. three-dimensional modeling and interpretation integrated with other geophysical or logging data, are required to reveal the possible presence of three-dimensional conductive body near the subsurface vent of Mt. Halla and the causes of the bias in the depths of layer estimated from MT and core log data.

• Journal of the Korean Geotechnical Society
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• v.38 no.3
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• pp.35-42
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• 2022

The N-value from the Standard Penetration Test (SPT), which is one of the representative in-situ test, is an important index that provides basic geological information and the depth of the bearing layer for the design of geotechnical structures. In the aspect of time and cost-effectiveness, there is a need to carry out a representative sampling test. However, the various variability and uncertainty are existing in the soil layer, so it is difficult to grasp the characteristics of the entire field from the limited test results. Thus the spatial interpolation techniques such as Kriging and IDW (inverse distance weighted) have been used for predicting unknown point from existing data. Recently, in order to increase the accuracy of interpolation results, studies that combine the geotechnics and deep learning method have been conducted. In this study, based on the SPT results of about 22,000 holes of ground survey, a comparative study was conducted to predict the depth of the bearing layer using deep learning methods and IDW. The average error among the prediction results of the bearing layer of each analysis model was 3.01 m for IDW, 3.22 m and 2.46 m for fully connected network and PointNet, respectively. The standard deviation was 3.99 for IDW, 3.95 and 3.54 for fully connected network and PointNet. As a result, the point net deep learing algorithm showed improved results compared to IDW and other deep learning method.

• Journal of Biosystems Engineering
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• v.33 no.5
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• pp.362-369
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• 2008

There is developing interest in precision agriculture in Korea, despite the fact that typical Korean fields are less than 1 ha in size. Describing within-field variability in typical Korean production settings is a fundamental first step toward determining the size of management zones and the inter-relationships between limiting factors, for establishment of site-specific management strategies. Measurements of rice (Oriza Sativa L) yield, chlorophyll content, and soil properties were obtained in a small (100-m by 30-m) Korean rice paddy field. Yield data were manually collected on 10-m by 5-m grids (180 samples with 3 samples in each of 60 grid cells) and chlorophyll content was measured using a Minolta SPAD 502 in 2-m by 2-m grids. Soil samples were collected at 275 points to compare results from sampling at different scales. Ten soil properties important for rice production in Korea were determined through laboratory analyses. Variogram analysis and point kriging with and without median polishing were conducted to determine the variability of the measured parameters. Influence of variogram model selection and other parameters on the interpretation of the data was investigated. For many of the data, maximum values were greater than double the minimum values, indicating considerable spatial variability in the small paddy field, and large-scale spatial trends were present. When variograms were fit to the original data, the limits of spatial dependency for rice yield and SP AD reading were 11.5 m and 6.5 m, respectively, and after detrending the limits were reduced to 7.4 m and 3.9 m. The range of spatial dependency for soil properties was variable, with several having ranges as short as 2 m and others having ranges greater than 30 m. Kriged maps of the variables clearly showed the presence of both large-scale (trend) variability and small-scale variability in this small field where it would be reasonable to expect uniformity. These findings indicate the potential for applying the principles and technology of precision agriculture for Korean paddy fields. Additional research is needed to confirm the results with data from other fields and crops.d similar tendency with the result for the frequency less than 20 Hz, but the width of change was reduced highly.

• Korean Journal of Remote Sensing
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• v.24 no.2
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• pp.107-115
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• 2008

Recently, a considerable number of studies have been conducted on the high resolution imagery showing the boundaries of objects clearly. When urban areas are analyzed in detail using the high resolution imagery, the size of analyzed zone is apt to be decided arbitrarily. Sufficient prior information about study area makes the decision of analysis zone possible; otherwise, it is difficult to determine the optimized analysis zone using only satellite imagery. In this study, the variograms of artificial simple images are analyzed before applying to the real satellite images. As a result of the analysis of simple images, the sill has an effect on the density of objects and also the size of objects and spacing influence the range. The variograms of real satellite images are analyzed with reference to the result of model test and are applied to determining the optimized analysis zone. This study shows that variogram can be applied to determining effectively the optimized analysis zone in case of no prior information on study area; moreover it will be expected to be used for an index to express the characteristics of urban imagery as well as conventional kriging and simulation.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.4
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• pp.118-129
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• 2016

Many epidemiological studies, relying on administrative air pollution monitoring data, have reported the association between particulate matter ($PM_{10}$) air pollution and human health. These monitoring data were collected at a limited number of fixed sites, whereas government-generated health data are aggregated at the area level. To link these two data types for assessing health effects, it is necessary to estimate area-level concentrations of $PM_{10}$. In this study, we estimated district (Gu)-level $PM_{10}$ concentrations using a previously developed pointwise exposure prediction model for $PM_{10}$ and three types of point locations in Seoul, Korea. These points included 16,230 centroids of the largest census output residential areas, 422 community service centers, and 610 centroids on the 1km grid. After creating three types of points, we predicted $PM_{10}$ annual average concentrations at all locations and calculated Gu averages of predicted $PM_{10}$ concentrations as representative Gu-estimates. Then, we compared estimates to each other and to measurements. Prediction-based Gu-level estimates showed higher correlations with measurement-based estimates as prediction locations became more population representative ($R^2=0.06-0.59$). Among the three estimates, grid-based estimates gave lowest correlations compared to the other two(0.35-0.47). This study provides an approach for estimating area-level air pollution concentrations and assesses air pollution health effects using national-scale administrative health data.

• Korean Journal of Soil Science and Fertilizer
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• v.39 no.3
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• pp.123-135
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• 2006

Spatial variability and distribution map of soil properties and the relationships between soil properties and crop yields are not well characterized in agroecosystems that have been land leveled to facilitate more cultivation of the new reclaimed sloping highland. Potato, onion, carrot, Chinese cabbage and radish were grown on the coarse sandy loam soil in 2004. Soil moisture content, soil penetration resistance and crop yield were sampled in the $10m{\times}50m$ field consisted of five plots. Sampling sites of each cultivation plot were 33 for the soil moisture, 11 for the soil penetration and 33 for the crop yield. The results of semivariance analysis, most of models were shown spherical equation. The significant ranges of each spatial variability model for the soil moisture, soil penetration and crop yield were broad as 33-35 meters in the potato cultivation plot, and that in the Chinese cabbage cultivation plot was narrow as 5-6 meters. The coefficient of variances (C.V.) of moisture, penetration and yield were various from 14 to 59 percents in five cultivation plots. The highest C.V. of potato yield was 59 percents, and that of the radish cultivation plot was as low as 14 percents. The required sample numbers for the determination of soil moisture content, soil penetration resistance and crop yield with error 10% at 0.05 significant level were ranged 8-40 for soil moisture, 7-25 for soil penetration and 424-4,678 for crop yield. The variogram and distribution map by kriging described field characteristics well so that the spatial variability would be useful for soil management for better efficiency and precision agriculture in the reclaimed highland.