• 한국데이터정보과학회:학술대회논문집
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• 2003.05a
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• pp.77-88
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• 2003

Cluster analysis has been widely used in many applications, such that data analysis, pattern recognition, image processing, etc. But clustering requires many hours to get clusters that we want, because it is more primitive, explorative and we make many data an object of cluster analysis. In this paper we propose a new clustering method, 'Clustering algorithm using a center of gravity for grid-based sample'. It is more fast than any traditional clustering method and maintains accuracy. It reduces running time by using grid-based sample and keeps accuracy by using representative point, a center of gravity.

• Korean Journal of Remote Sensing
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• v.21 no.1
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• pp.51-57
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• 2005

The currently operating NASA/GFZ Gravity Recovery and Climate Experiment (GRACE) mission is designed to measure small mass changes over a large spatial scale, including the mapping of continental water storage changes and other geophysical signals in the form of monthly temporal gravity field. The European Space Agency's Gravity field and steady state Ocean Circulation Explorer (GOCE) space gravity gradiometer (SGG) mission is anticipated to determine the mean Earth gravity field with an unprecedented geoid accuracy of several cm (rms) with wavelength of 130km or longer. In this paper, we present a summary of present GRACE studies for the recovery of hydrological signals in the Amazon basin using alternative processing and filtering techniques, and local inversion to enhance the temporal and spatial resolutions by two-folds or better. Simulation studies for the potential GRACE detection of slow deformations due to Nazca-South America plate convergence and glacial isostatic adjustment (GIA) signals show that these signals are at present difficult to detect without long-term data averaging and further improvement of GRACE measurement accuracy.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.4
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• pp.383-388
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• 2002

This study suggests a data processing method for precise geoid height calculation through sea gravity data of mid-Yellow Sea provided by Haeyang 2000 and satellite altimetry data and the EGM96 geopotential model from GSFC/DMA in USA. Also it compared sea gravity data with satellite altimetry gravity data. As a result, precise geoidal undulation of the mid-Yellow Sea presented from calculating and integrating EGM96 geopotential model in degree and order 167 and a relative geoid by integral radius of 27km respectively It has a mean value of 18.339m, varying from 13.564m to 22.785m. the comparison between sea gravity data and satellite altimetry data shows that the former is more precise than the latter, which showed an anomaly of 0.56m0Gal and RMSE of 4.195m.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.2
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• pp.129-138
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• 2009

The lunar gravity field is an important source to understand the lunar interior structure, dichotomy and magma ocean of the moon, furthermore it can be used to study the origin and evolution history of the moon. In this paper, we firstly investigated the history of lunar exploration were performed for determining the lunar gravity field, in addition to investigating the procedure of progress related with the lunar gravity field model and gravity observations techniques. After, we determined practically the gravity anomalies of the moon using the new lunar gravity model, SGM90d (SELENE Gravity Model), which were developed by processing the tracking data from SELENE, the japanese lunar mission. Finally, we compared the lunar gravity anomalies from SGM90d model to the those from existing lunar gravity model (LP165P). As results from the comparison, we can make a sense that 4-way Doppler observations of SELENE is very effective to measure the gravity field on the farside of the moon. The precise lunar gravity field model including the farside of the moon which can be more helpful to understand the dichotomy of moon and to establish the detailed distribution of lunar gravity field, such as a mascon.

• Economic and Environmental Geology
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• v.40 no.4
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• pp.445-459
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• 2007

Superconducting Gravimeter(SG) was installed and has been successfully operated at MunGyung, Kyungsang province in Korea in March 2005. It was registered as the 21st observatory of the Global Geodynamics Project. Since SG can precisely measure the gravity variations below the 1mHz frequency band, it has the outstanding capability to sense and resolve many different periodic gravity components from each other. From the raw data collected between 18 March 2005 and 21 February 2006 diurnal and semi-diurnal tidal band's residual gravity components were analyzed. During this process, the instrumental noises, air pressure, and ground water corrections were carried out. Values of $-3.18nm/s^2/hPa\;and\;17nm/s^2/m$ were used respectively in the air pressure and groundwater corrections. Hartmann-Wenzel and Whar-Dehant Earth tide models were adopted to compute the residual gravity for Q1, O1, P1, K1, M2, N2, S2, K2 tidal bands. For the ocean loading correction, SCW80, FES952, and FES02 models were used and compared. As a result, FES02 ocean loading model has shown the best match for the data processing at MunGyung SG MunGyung SG gravity was compared with GRACE satellite gravity. The correlation coefficient between the two gravity after groundwater correction was 0.628, which is higher than before ground water correction. To evaluate sensitivity at MunGyung SG gravity statition, the gravity data measured during 2005 Indodesian earthquake was compared with STS-2 broad band seismometer data. The result clearly revealed that the SG could recorded the same period of earthquake with seismometer event and a few after-shock events those were detected by seismometer.

• 한국데이터정보과학회:학술대회논문집
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• 2004.04a
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• pp.51-60
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• 2004

K-means clustering is an iterative algorithm in which items are moved among sets of clusters until the desired set is reached. K-means clustering has been widely used in many applications, such as market research, pattern analysis or recognition, image processing, etc. It can identify dense and sparse regions among data attributes or object attributes. But k-means algorithm requires many hours to get k clusters that we want, because it is more primitive, explorative. In this paper we propose a new method of k-means clustering using a center of gravity for grid-based sample. It is more fast than any traditional clustering method and maintains its accuracy.

• Journal of the Korean earth science society
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• v.31 no.2
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• pp.119-128
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• 2010

To make reliable interpretations on the sparse spatial data, the spatial distribution characteristics that are inevitable for spatial estimation should be properly analyzed. Variograms have been widely used for obtaining the spatial characteristics inherent to data in spatial estimation problems. But their applications were limited as the basic information for further data estimation. Therefore, the additional analysis of the meaning of variograms is required for more reliable data processing and interpretations. In this paper, we investigated the proper meaning of variogram values and the specific features of distributions which can be obtained through variogram analysis. Variograms can provide the information on both linearity and the strength changes of interrelationships between the data sets according to the direction and lag distance. First, sill and range values, which are main parameters of variograms, were analyzed. Then a similarity range using spatial auto-correlation values was introduced to verify the applicability of linearity analysis through the comparative study of spatial distribution features of gravity and magnetic data collected in Hwasan caldera. Through these analyses, we were able to identify the dissimilar patterns of gravity and magnetic data that became apparent according to the distribution and variation ranges of the data sets. It is inferred that the gravity and magnetic anomalous bodies are extended to the ground because linearity direction of gravity and magnetic data appear similarly with linearity derection of topography in Hwasan caldera.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.5
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• pp.523-530
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• 2010

Recently more gravity data is being obtained due to the increased demands from the fields of geodesy, geophysics, and military. In general, the observed gravity values are corrected for the effect of tide, instrument drift, and instrument height to generate the absolute gravity values at a point. Until yet, the models for tide and drift corrections and those procedures are not determined in Korea which led to the inconsistent data processing for different data sets. Therefore, in this study, the models for tide and drift are analyzed to select the appropriate models. Based on the analysis, it was found that there is not much difference between Longman and Tamura tide models for celestial objects. Earth tide, however, should be considered in tide correction procedure. In drift corrections, the difference between the model considering only the common points and that considering all points appears significantly large up to 0.04mGal. In this case, the model with all points should be used as it the correct one according to the adjustment theory and it generates estimates with better precision.

• Geophysics and Geophysical Exploration
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• v.14 no.1
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• pp.88-97
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• 2011

We present a method for modelling the terrain response of gravity gradiometry surveys utilising an adaptive quadtree mesh discretization. The data- and terrain-dependent method is tailored to provide rapid and accurate terrain corrections for draped and barometric airborne surveys. The surface used in the modelling of the terrain effect for each datum is discretized automatically to the largest cell size that will yield the desired accuracy, resulting in much faster modelling than full-resolution calculations. The largest cell sizes within the model occur in areas of minimal terrain variation and at large distances away from the datum location. We show synthetic and field examples for proof of concept. In the presented field example, the adaptive quadtree method reduces the computational cost by performing 351 times fewer calculations than the full model would require while retaining an accuracy of one E$\"{o}$tv$\"{o}$s for the gradient data. The method is also used for the terrain correction of the gravity field and performed 310 times faster compared with a calculation of the full digital elevation model.

• Journal of the Korean Data and Information Science Society
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• v.21 no.1
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• pp.121-128
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• 2010

K-means clustering is an iterative algorithm in which items are moved among sets of clusters until the desired set is reached. K-means clustering has been widely used in many applications, such as market research, pattern analysis or recognition, image processing, etc. It can identify dense and sparse regions among data attributes or object attributes. But k-means algorithm requires many hours to get k clusters that we want, because it is more primitive, explorative. In this paper we propose a new method of k-means clustering using a center of gravity for grid-based sample. It is more fast than any traditional clustering method and maintains its accuracy.