• Economic and Environmental Geology
• /
• v.48 no.1
• /
• pp.51-63
• /
• 2015

I produced a secular variation model of geomagnetic field by using the magnetic component data from four geomagnetic observatories located in Northeast Asia during the years between 1997 and 2011. The Earth's magnetic field varies with time and location due to the dynamics of fluid outer core and the magnetic observatories on the surface measure in time series. To adequately represent the magnetic field or secular variations of the Earth, a spatio-temporal model is required. In making a global model, satellite observations as well as limited observatory data are necessary to cover the regions and time intervals. However, you need a considerable work and time to process a huge amount of the dataset with complicated signal separation procedures. When you update the model, the same amount of chores is demanded. Besides, the global model might be affected by the measurement errors of each observatory that are biased and the processing errors in satellite data so that the accuracy of the model would be degraded. In this study, as considered these problems, I introduced a localized method in modeling secular variation of the Earth's magnetic field over Northeast Asia region. Secular variation data from three Japanese observatories and one Chinese observatory that are all in the INTERMAGNET are implemented in the model valid between 1997 to 2011 with the interval of 6 months. With the resulting model, I compared with the global model called CHAOS-4, which includes the main, secular variation and secular acceleration models between 1997 to 2013 by using the three satellites' databases and INTERMAGNET observatory data. Also, the geomagnetic 'jerk' which is known as a sudden change in the time derivatives of the main field of the Earth, was discussed from the localized secular acceleration coefficients derived from spline models.

• The Journal of Engineering Geology
• /
• v.32 no.4
• /
• pp.611-625
• /
• 2022

One of the applications of geomagnetic paleo-secular variation (PSV) is the age dating of archeological remains (i.e., the archeomagnetic dating technique). This application requires the local model of PSV that reflects non-dipole fields with regional differences. Until now, the tentative Korean paleosecular variation (t-KPSV) calculated based on JPSV (SW Japanese PSV) has been applied as a reference curve for individual archeomagnetic directions in Korea. However, it is less reliable due to regional differences in the non-dipole magnetic field. Here, we present PSV curves for AD 1 to 600, corresponding to the Korean Three Kingdoms (including the Proto Three Kingdoms) Period, using the results of archeomagnetic studies in the Korean Peninsula and published research data. Then we compare our PSV with the global geomagnetic prediction model and t-KPSV. A total of 49 reliable archeomagnetic directional data from 16 regions were compiled for our PSV. In detail, each data showed statistical consistency (N > 6, 𝛼₉₅ < 7.8°, and k > 57.8) and had radiocarbon or archeological ages in the range of AD 1 to 600 years with less than ±200 years error range. The compiled PSV for the initial six centuries (KPSV0.6k) showed declination and inclination in the range of 341.7° to 20.1° and 43.5° to 60.3°, respectively. Compared to the t-KPSV, our curve revealed different variation patterns both in declination and inclination. On the other hand, KPSV0.6k and global geomagnetic prediction models (ARCH3K.1, CALS3K.4, and SED3K.1) revealed consistent variation trends during the first six centennials. In particular, the ARCH3K.1 showed the best fitting with our KPSV0.6k. These results indicate that contribution of the non-dipole field to Korea and Japan is quite different, despite their geographical proximity. Moreover, the compilation of archeomagnetic data from the Korea territory is essential to build a reliable PSV curve for an age dating tool. Lastly, we double-check the reliability of our KPSV0.6k by showing a good fitting of newly acquired age-controlled archeomagnetic data on our curve.

• Korean Journal of Remote Sensing
• /
• v.33 no.5_2
• /
• pp.721-732
• /
• 2017

With the increasing socio-economic importance of rice as a global staple food, several models have been developed for rice yield estimation by combining remote sensing data with carbon cycle modelling. In this study, we aimed to estimate rice yield in Korea using such an integrative model using satellite remote sensing data in combination with a biophysical crop growth model. Specifically, daily meteorological inputs derived from MODIS (Moderate Resolution imaging Spectroradiometer) and radar satellite products were used to run a light use efficiency based crop growth model, which is based on the MODIS gross primary production (GPP) algorithm. The modelled biomass was converted to rice yield using a harvest index model. We estimated rice yield from 2003 to 2014 at the county level and evaluated the modelled yield using the official rice yield and rice straw biomass statistics of Statistics Korea (KOSTAT). The estimated rice biomass, yield, and harvest index and their spatial distributions were investigated. Annual mean rice yield at the national level showed a good agreement with the yield statistics with the yield statistics, a mean error (ME) of +0.56% and a mean absolute error (MAE) of 5.73%. The estimated county level yield resulted in small ME (+0.10~+2.00%) and MAE (2.10~11.62%),respectively. Compared to the county-level yield statistics, the rice yield was over estimated in the counties in Gangwon province and under estimated in the urban and coastal counties in the south of Chungcheong province. Compared to the rice straw statistics, the estimated rice biomass showed similar error patterns with the yield estimates. The subpixel heterogeneity of the 1 km MODIS FPAR(Fraction of absorbed Photosynthetically Active Radiation) may have attributed to these errors. In addition, the growth and harvest index models can be further developed to take account of annually varying growth conditions and growth timings.

• Journal of the Korean Geographical Society
• /
• v.49 no.5
• /
• pp.761-778
• /
• 2014

There has been relatively little study to model price for commercial property because of its low transaction volume in the market. Despite of this thin market character, this paper tried to estimate prices for commercial lots as accurate as possible. We constructed a model whose components consist of mean structure(global trend), exponential covariance function and a pure error term, and applied it to actual sales price data of Seoul. We explicitly took account of spatial autocorrelation of land price by utilizing a kriging technique, a representative method of spatial interpolation, because the land price of commercial lots has feature of differential price forming pattern depending on submarkets they belong to. In addition, we chose to apply a bayesian kriging to overcome data scarcity by incorporating experts' knowledge into prior probability distribution. The chosen model's excellent performance was verified by the result from validation data. We confirmed that the excellence of the model is attributed to incorporating both autocorexperts' knowledge and spatial autocorrelation in the model construction. This paper is differentiated from previous studies in the sense that it applied the bayesian kriging technique to estimate price for commercial lots and explicitly combined experts' knowledge with data. It is expected that the result of this paper would provide a useful guide for the circumstances under which property price has to be estimated reliably based on sparse transaction data.

• Journal of Astronomy and Space Sciences
• /
• v.25 no.2
• /
• pp.227-238
• /
• 2008

GNSS (Global Navigation Satellite System) Ground Station monitors navigation satellite signal, analyzes navigation result, and uploads correction information to satellite. GNSS Ground Station is considered as a main object for constructing GNSS infra-structure and applied in various fields. ETRI (Electronics and Telecommunications Research Institute) is developing Monitoring and Control subsystem, which is subsystem of GNSS Ground Station. Monitoring and Control subsystem acquires GPS and Galileo satellite signal and provides signal monitoring data to GNSS control center. In this paper, the configurations of GNSS Ground Station and Monitoring and Control subsystem are introduced and the preliminary design of Monitoring and Control subsystem is performed. Monitoring and Control subsystem consists of data acquisition module, data formatting and archiving module, data error correction module, navigation solution determination module, independent quality monitoring module, and system operation and maintenance module. The design process uses UML (Unified Modeling Language) method which is a standard for developing software and consists of use-case modeling, domain design, software structure design, and user interface structure design. The preliminary design of Monitoring and Control subsystem enhances operation capability of GNSS Ground Station and is used as basic material for detail design of Monitoring and Control subsystem.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.14 no.4
• /
• pp.137-149
• /
• 2011

In this study, we analyzed the effects of seismic displacements due to the mega thrust earthquake occurred near Tohoku-Oki area on Mar. 11, 2011 with Mw 9.0 magnitude in the context of evaluation of position change by the earthquake on the Korean and Asian GPS permanent stations. For this, two weeks GPS data observed around the event of Tohoku-Oki earthquake (Mar. 4 ~ Mar. 18, 2011) were obtained from 22 GPS permanent stations in the vicinity of epicenter (Korea, Japan, Russia, China and Taiwan) and 284 IGS global stations. All available GPS data were processed and adjusted by GAMIT/GLOBK software to estimate the co-seismic horizontal displacements at each station. As the results of GPS analysis, the co-seismic displacements due to Tohoku-Oki earthquake were clearly revealed in the GPS stations of Asian region, Japan and its neighboring countries, and even to affect the horizontal position of GPS station (WUHN in China) which are located about 2,702km away from the epicenter. In conclusion, it was found that the Tohoku-Oki earthquake had resulted in the horizontal displacements ranging from 14.9 mm to 58.3 mm in Korea. So, these displacements can cause the position error of GPS geodetic survey up to 20 mm without updating the coordinates of Korean geodetic network.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.20 no.3
• /
• pp.125-140
• /
• 2017

Until recently, regression based spatial interpolation methods and Kriging based spatial interpolation methods have been largely used to estimate land price or housing price, but less attention has been paid on comparing the performance of these spatial interpolation methods. In this regard, this research applied regression based spatial interpolators and Kriging based spatial interpolators for estimating the land prices in Dalseo-gu, Daegu metropolitan city and evaluated the accuracy of eight spatial interpolators. OLS, SLM, SEM, and GWR were used as regression based spatial interpolators while SK, OK, UK, and CK were employed as Kriging based spatial interpolators. The global accuracy was statistically evaluated by RMSE, adjusted RMSE, and COD. The relative accuracy was visually compared by three-dimensional residual error map and scatterplot. Results from statistical and visual analyses indicate that GWR reflecting the spatial non-stationarity was a relatively more accurate spatial predictor to estimate land prices in the study area than SAR and Kriging based spatial interpolators considering the spatial dependence. The findings from this research will contribute to the secondary research into analyzing the urban spatial structure with land prices.

• Economic and Environmental Geology
• /
• v.36 no.3
• /
• pp.213-223
• /
• 2003

We estimated the Moho depth of Korean Peninsula from gravity anomalies and digital elevation model. The satellite radar altimetry-derived global free-air gravity model was used to ensure the homogeneity in both data and frequency domains of the original data. Two different methods were implemented to calculate the Moho depth; the wavenumber correlation analysis (Kim et al., 2000a) and the power spectrum analysis. The former method calculates depth-to-the-Moho by correlating topographic gravity effect with free-air gravity anomaly in the wavenumber domain under the assumption that the study area is not isostatically compensated. The latter one, on the other hand, considers the different density layers (i.e., Conrad and Moho), using complete Bouguer gravity anomaly in the Frequency domain of the Fourier transform. The correlation coefficient of the two Moho model is 0.53, and methodology and numerical error are mainly responsible for any mismatch between the two models. In order to integrate the two independentely-estimated models, we applied least-squares adjustment using the differenced depth. The resultant model has mean and standard deviation Moho depths of 32.0 km and 2.5 km with (min, max) depths of (20.3, 36.6) kms. Although this result does not include any topographic gravity effect, however, the validity of isostasy and the role of local stress field in the study area should be further studied.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.36 no.5
• /
• pp.395-401
• /
• 2018

Recently, most of mobile devices are equipped with GNSS (Global Navigation Satellite System). When the GNSS signal is available, it is easy to obtain position information. However, GNSS is not suitable solution for indoor localization, since the signals are normally not reachable inside buildings. A wide varieties of technology have been developed as a solution for indoor localization such as Wi-Fi, beacons, and inertial sensor. With the increased sensor combinations in mobile devices, mobile devices also became feasible to provide a solution, which based on PDR (Pedestrian Dead Reckoning) method. In this study, we utilized the combination of three sensors equipped in mobile devices including accelerometer, digital compass, and gyroscope and applied three representative PDR methods. The proposed methods are done in three stages; step detection, step length estimation, and heading determination and the final indoor localization result was evaluated with terrestrial LiDAR (Light Detection And Ranging) data obtained in the same test site. By using terrestrial LiDAR data as reference ground truth for PDR in two differently designed experiments, the inaccuracy of PDR methods that could not be found by existing evaluation method could be revealed. The firstexperiment included extreme direction change and combined with similar pace size. Second experiment included smooth direction change and irregular step length. In using existing evaluation method which only checks traveled distance, The results of two experiments showed the mean percentage error of traveled distance estimation resulted from three different algorithms ranging from 0.028 % to 2.825% in the first experiment and 0.035% to 2.282% in second experiment, which makes it to be seen accurately estimated. However, by using the evaluation method utilizing terrestrial LiDAR data, the performance of PDR methods emerged to be inaccurate. In the firstexperiment, the RMSEs (Root Mean Square Errors) of x direction and y direction were 0.48 m and 0.41 m with combination of the best available algorithm. However, the RMSEs of x direction and y direction were 1.29 m and 3.13 m in the second experiment. The new evaluation result reveals that the PDR methods were not effective enough to find out exact pedestrian position information opposed to the result from existing evaluation method.

• The KIPS Transactions:PartB
• /
• v.11B no.1
• /
• pp.27-34
• /
• 2004

This paper proposes a method to trace and interpret a moving object based on the information which can be directly obtained from MPEG-2 compressed video stream without decoding process. In the proposed method, the motion flow is constructed from the motion vectors included in compressed video. We calculate the amount of pan, tilt, and zoom associated with camera operations using generalized Hough transform. The local object motion can be extracted from the motion flow after the compensation with the parameters related to the global camera motion. Initially, a moving object to be traced is designated by user via bounding box. After then automatic tracking Is performed based on the accumulated motion flows according to the area contributions. Also, in order to reduce the cumulative tracking error, the object area is reshaped in the first I-frame of a GOP by matching the DCT coefficients. The proposed method can improve the computation speed because the information can be directly obtained from the MPEG-2 compressed video, but the object boundary is limited by macro-blocks rather than pixels. Also, the proposed method is proper for approximate object tracking rather than accurate tracing of an object because of limited information available in the compressed video data.