• Journal of Astronomy and Space Sciences
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• v.33 no.1
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• pp.29-36
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• 2016

The East African ionosphere (3°S-18°N, 32°E-50°E) was mapped using Total Electron Content (TEC) measurements from ground-based GPS receivers situated at Asmara, Mekelle, Bahir Dar, Robe, Arbaminch, and Nairobi. Assuming a thin shell ionosphere at 350 km altitude, we project the Ionospheric Pierce Point (IPP) of a slant TEC measurement with an elevation angle of >10° to its corresponding location on the map. We then infer the estimated values at any point of interest from the vertical TEC values at the projected locations by means of interpolation. The total number of projected IPPs is in the range of 24-66 at any one time. Since the distribution of the projected IPPs is irregularly spaced, we have used an inverse distance weighted interpolation method to obtain a spatial grid resolution of 1°×1° latitude and longitude, respectively. The TEC maps were generated for the year 2008, with a 2 hr temporal resolution. We note that TEC varies diurnally, with a peak in the late afternoon (at 1700 LT), due to the equatorial ionospheric anomaly. We have observed higher TEC values at low latitudes in both hemispheres compared to the magnetic equatorial region, capturing the ionospheric distribution of the equatorial anomaly. We have also confirmed the equatorial seasonal variation in the ionosphere, characterized by minimum TEC values during the solstices and maximum values during the equinoxes. We evaluate the reliability of the map, demonstrating a mean error (difference between the measured and interpolated values) range of 0.04-0.2 TECU (Total Electron Content Unit). As more measured TEC values become available in this region, the TEC map will be more reliable, thereby allowing us to study in detail the equatorial ionosphere of the African sector, where ionospheric measurements are currently very few.

• The Journal of the Korea Contents Association
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• v.8 no.2
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• pp.74-82
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• 2008

This paper investigates chrominance reconstruction methods that reconstruct subsampled chrominance information efficiently using the correlation between luminance and chrominance components in the decompression process of compressed images, and analyzes drawbacks involved in the adaptive-weighted 2-dimensional linear interpolation among the methods, which shows higher efficiency in the view of computational complexity than other methods. To improve the drawback that the spatial frequency distribution is not considered for the decompressed image and to support the application on a low-performance system in behalf of 2-dimensional linear interpolation, this paper proposes the multi-mode reconstruction method which uses three reconstruction methods having different computational complexity from each other according to the degree of edge response of luminance component. The performance evaluation on a development platform for embedded systems showed that the proposed reconstruction method supports the similar level of image quality for decompressed images while reducing the overall computation time for chrominance reconstruction in comparison with the 2-dimensional linear interpolation.

• Journal of the Korean Geographical Society
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• v.46 no.1
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• pp.67-80
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• 2011

Choropleth mapping of population distribution is based on the assumption that people are uniformly distributed throughout each enumeration unit. Dasymetric mapping technique improves choropleth mapping by refining spatially aggregated data with residential information. Further, pycnophylactic interpolation can upgrade dasymetric mapping by considering population distribution of neighboring areas, while preserving the volumes of original units. This study proposed a combined solution of dasymetric mapping and pycnophylactic interpolation to improve the accuracy of population density distribution. Specifically, the dasymetric method accounts for the spatial distribution of population within each census unit, while pycnophylactic interpolation considers population distribution of neighboring area. This technique is demonstrated with 1990 census data of the Athens, GA. with land use land cover information derived from remotely-sensed imagery for the areal extent of populated areas. The results are evaluated by comparison between original population counts of smaller census units (census block groups) and population counts of the grid map built from larger units (census tracts) aggregated to the same areal units. The estimated populations indicate a satisfactory level of accuracy. Population distribution acquired by the suggested method can be re-aggregated to any type of geographic boundaries such as electoral boundaries, school districts, and even watershed for a variety of applications.

• Journal of Korea Water Resources Association
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• v.53 no.10
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• pp.903-915
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• 2020

Long-term high-resolution hydro-meteorological data has been recognized as an essential element in establishing the water resources plan. The increasing demand for spatial precipitation in various areas such as climate, hydrology, geography, ecology, and environment is apparent. However, potential limitations of the existing area-weighted and numerical interpolation methods for interpolating precipitation in high altitude areas remains less explored. The proposed PRISM (Precipitation-Elevation Regressions on Independent Slopes Model) model can produce gridded precipitation that can adequately consider topographic characteristics (e.g., slope and altitude), which are not substantially included in the existing interpolation techniques. In this study, the PRISM model was optimized with SCEM-UA (Shuffled Complex Evolution Metropolis-University of Arizona) to produce daily gridded precipitation. As a result, the minimum impact radius was calculated 9.10 km and the maximum 34.99 km. The altitude of coastal weighted was 681.03 m, the minimum and maximum distances from coastal were 9.85 km and 38.05 km. The distance weighting factor was calculated to be about 0.87, confirming that the PRISM result was very sensitive to distance. The results showed that the proposed PRISM model could reproduce the observed statistical properties reasonably well.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.2
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• pp.96-104
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• 2001

Usage of ecosystem models has been extended to landscape scales for understanding the effects of environmental factors on natural and agro-ecosystems and for serving as their management decision tools. Accurate prediction of spatial variation in daily temperature is required for most ecosystem models to be applied to landscape scales. There are relatively few empirical evaluations of landscape-scale temperature prediction techniques in mountainous terrain such as Korean Peninsula. We derived a periodic function of seasonal lapse rate fluctuation from analysis of elevation effects on daily temperatures. Observed daily maximum and minimum temperature data at 63 standard stations in 1999 were regressed to the latitude, longitude, distance from the nearest coastline and altitude of the stations, and the optimum models with $r^2$ of 0.65 and above were selected. Partial regression coefficients for the altitude variable were plotted against day of year, and a numerical formula was determined for simulating the seasonal trend of daily lapse rate, i.e., partial regression coefficients. The formula in conjunction with an inverse distance weighted interpolation scheme was applied to predict daily temperatures at 267 sites, where observation data are available, on randomly selected dates for winter, spring and summer in 2000. The estimation errors were smaller and more consistent than the inverse distance weighting plus mean annual lapse rate scheme. We conclude that this method is simple and accurate enough to be used as an operational temperature interpolation scheme at landscape scale in Korea and should be applicable to elsewhere.

• 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 the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.1
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• pp.51-66
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• 2022

SST (Sea Surface Temperature) is based on the atmosphere-ocean interaction, one of the most important mechanisms for the Earth system. Because it is a crucial oceanic and meteorological factor for understanding climate change, gap-free grid data at a specific spatial and temporal resolution is beneficial in SST studies. This paper examined the production of daily SST grid maps from 137 stations in 2020 through the ordinary kriging with variogram optimization and their accuracy assessment. The variogram optimization was achieved by WLS (Weighted Least Squares) method, and the blind tests for the interpolation accuracy assessment were conducted by an objective and spatially unbiased sampling scheme. The four-round blind tests showed a pretty high accuracy: a root mean square error between 0.995 and 1.035℃ and a correlation coefficient between 0.981 and 0.982. In terms of season, the accuracy in summer was a bit lower, presumably because of the abrupt change in SST affected by the typhoon. The accuracy was better in the far seas than in the near seas. West Sea showed better accuracy than East or South Sea. It is because the semi-enclosed sea in the near seas can have different physical characteristics. The seasonal and regional factors should be considered for accuracy improvement in future work, and the improved SST can be a member of the SST ensemble around South Korea.

• Journal of the Korean association of regional geographers
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• v.18 no.4
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• pp.414-432
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• 2012

Land price is a kind of text to read urban spatial structure. The purpose of this paper is to inquire into the characteristics of Daegu's urban structure and its change in time through exploring spatio-temporal variations of land price with a detailed spatial and temporal resolution. To achieve this, land value surfaces were represented using the officially assessed land price every other year from 1995 to 2011. Through mapping and exploring spatio-temporal patterns and fluctuation rates of land price for this period, changes in urban structure, the effects of local decision makings such as Greenbelt adjustment, housing site development, and gentrification, and the effects of business fluctuations or policies at global or national scales could be caught. In addition, the trends for suburbanization and multi-centric urban form could be examined from the results of a negative exponential model explaining the effect of distance from an urban center on spatial variation of land price. These results demonstrate that urban analysis using land price mirroring spatial decision making at various scales could deepen understanding for internal structure and change of a city and provide useful information for establishing regional and urban development policies and evaluating their effects.

• Spatial Information Research
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• v.22 no.2
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• pp.63-71
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• 2014

Ocean leisure sports have recently emerged as one of so-called blue ocean industries. They are sensitive to diverse environmental conditions such as current, temperature, and salinity, which can increase needs of forecasting data as well as in-situ observations for the ocean. In this context, a Web-based geovisualization system for coastal information produced by model forecasts was implemented for use in supporting various ocean activities. First, FVCOM(Finite Volume Coastal Ocean Model) was selected as a forecasting model, and its data was preprocessed by a spatial interpolation and sampling library. The interpolated raster data for water surface elevation, temperature, and salinity were stored in image files, and the vector data for currents including speed and direction were imported into a distributed DBMS(Database Management System). Web services in REST(Representational State Transfer) API(Application Programming Interface) were composed using Spring Framework and integrated with desktop and mobile applications developed on the basis of hybrid structure, which can realize a cross-platform environment for geovisualization.

• Wind and Structures
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• v.14 no.4
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• pp.301-319
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• 2011

The full-scale measurements are compared with the wind tunnel test results for the long-span roof latticed spatial structure of Shenzhen Citizen Center. A direct comparison of model testing results to full-scale measurements is always desirable, not only in validating the experimental data and methods but also in providing better understanding of the physics such as Reynolds numbers and scale effects. Since the quantity and location of full-scale measurements points are different from those of the wind tunnel tests taps, the weighted proper orthogonal decomposition technique is applied to the wind pressure data obtained from the wind tunnel tests to generate a time history of wind load vector, then loads acted on all the internal nodes are obtained by interpolation technique. The nodal mean wind pressure coefficients, root-mean-square of wind pressure coefficients and wind pressure power spectrum are also calculated. The time and frequency domain characteristics of full-scale measurements wind load are analyzed based on filtered data-acquisitions. In the analysis, special attention is paid to the distributions of the mean wind pressure coefficients of center part of Shenzhen Citizen Center long-span roof spatial latticed structure. Furthermore, a brief discussion about difference between the wind pressure power spectrum from the wind tunnel experiments and that from the full-scale in-site measurements is compared. The result is important fundament of wind-induced dynamic response of long-span spatial latticed structures.