• Journal of Korean Society of Forest Science
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• v.96 no.5
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• pp.591-601
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• 2007

Spatial information on forest biomass is an important factor to evaluate the capability of forest as a carbon sequestrator and is a core independent variable required to drive models which describe ecological processes such as carbon budget, hydrological budget, and energy flow. The objective of this study is to understand the relationship between satellite image and field data, and to quantitatively estimate and map the spatial distribution of forest biomass. Landsat Enhanced Thematic Mapper (ETM+) derived vegetation indices and field survey data were applied to estimate the biomass distribution of mountainous forest located in Gwangneung Experimental Forest (230 ha). Field survey data collected from the ground plots were used as the dependent variable, forest biomass, while satellite image reflectance data (Band 1~5 and Band 7), Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and RVI (Ratio Vegetation Index) were used as the independent variables. The mean and total biomass of Gwangneung catchment area were estimated to be about 229.5 ton/ha and $52.8{\times}10^3$ tons respectively. Regression analysis revealed significant relationships between the measured biomass and Landsat derived variables in both of deciduous forest ($R^2=0.76$, P < 0.05) and coniferous forest ($R^2=0.75$, P < 0.05). However, there still exist many uncertainties in the estimation of forest ecosystem parameters based on vegetation remote sensing. Developing remote sensing techniques with adequate filed survey data over a long period are expected to increase the estimation accuracy of spatial information of the forest ecosystem.

• Journal of Environmental Science International
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• v.19 no.12
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• pp.1375-1384
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• 2010

The purpose of this research is to understand the change of runoff characteristics by estimated spatial rainfall. Therefore, this paper largely composed of two parts. First, we compared the simulated result according to estimation method, ID(Inverse Distance Method, ID2(Inverse Square Distance Method), and Kr(General Covariance Kriging Method), after letting miss rainfall data to the observed data. Second, we reviewed the runoff characteristics of the distributed runoff model according to the estimated spatial rainfall. On the basis of Yuseong water level station, we select the target basin as Gabchun watershed. We assumed 1 point or 2 point of the 6 rainfall gauge stations in watershed were missed. We applied the spatial rainfall distributed by Kr to Hy-GIS GRM, distributed runoff model. When 1 point rainfall data is missed, Kr is superior to others in point rainfall estimation and runoff estimation of Hy-GIS GRM. However, in case rainfall data of 2 points is missed, all of three methods did not give suitable result for them. In conclusion, Kr showed better applicability than other estimated methods if rainfall's data less than 2 points is missed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.10C
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• pp.787-797
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• 2008

In this paper, we propose a fast disparity estimation method considering temporal and spatial redundancy based on a dynamic programming for stereo matching. For the first step, the dynamic programming is performed to estimate disparity vectors with correlation between neighboring pixels in an image. Next, we efficiently compensate regions, which disparity vectors are not allocated, with neighboring disparity vectors assuming that disparity vectors in same object are quite similar. Moreover, in case of video sequence, we can decrease a complexity with temporal redundancy between neighboring frames. For performance comparison, we generate an intermediate-view image using the estimated disparity vector. Test results show that the proposed algorithm gives $0.8{\sim}2.4dB$-increased PSNR(peak signal to noise ratio) compared to a conventional block matching algorithm, and the proposed algorithm also gives approximately 0.1dB-increased PSNR and $48{\sim}68%$-lower complexity compared to the disparity estimation method based on general dynamic programming.

• Journal of KIBIM
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• v.4 no.4
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• pp.13-23
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• 2014

After being introduced, Building Information Modeling (BIM) has been actively applied to the cost estimation of construction projects, and various studies on BIM based quantity take-off have been carried out. In practice, however, these calculations take considerable time, because BIM based quantity take-off is further conducted along with 2D-based quantity take-off. Studies on the quantity take-off using BIM spatial objects have been carried out on early stages of projects, but how this method differs from the existing quantity take-off method and how accurate it is in comparison have rarely been verified. Therefore, by comparing 2D based quantities with quantities through BIM spatial objects, this study analyzed the accuracy of quantity take-off using BIM spatial objects. To this end, the properties of BIM spatial objects and quantity calculable spatial types were analyzed, and existing 2D-based quantities and quantities extracted from BIM spatial objects were compared through a case study. As a result, the quantity of spatial objects found to be more by about 7.13% in 0.05% and therefore, this difference should be considered during quantity take-off using BIM spatial objects. Through the results of this study, we can improve the accuracy of quantity take-off using BIM spatial objects in the early stage of a construction project.

• Journal of the Economic Geographical Society of Korea
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• v.12 no.2
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• pp.179-194
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• 2009

The spatial distribution of crime incidences in urban neighborhoods is a reflection of their socio-economic environment and spatial inter-relations. Spatial interactions between offenders and victims lead to spatial autocorrelation of the crime incidences. The spatial autocorrelation among the incidences biases the interpretation of the ecological model in OLS framework. This research investigates residential crimes using residential burglaries and robberies occurred in the city of Columbus, Ohio, for 2000. In particular, the spatial distribution of incidence rates of residential crimes are accounted in OLS framework using eigenvectors, which reflect spatial dependence in crime patterns. Result presents that handling spatial autocorrelation enhanced model estimation, and both economic deprivation and crime opportunity are turned out significant in estimating residential crime rates.

• Journal of the Korea Computer Industry Society
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• v.5 no.4
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• pp.511-516
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• 2004

In this paper, we propose a low-power motion-estimation VLSI architecture based on systolic array using partial norms and spatial correlation. Our approach reduces computational load based on eliminating invalid block-matching points.

• Structural Engineering and Mechanics
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• v.25 no.3
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• pp.291-310
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• 2007

Current seismic design guidelines in Japan are diverse in the seismic ground strain estimates, because the concepts on a horizontally propagating wave model are not consistent in various seismic design guidelines including gas, water and other underground structures. The purpose of this study is (a) to derive the analytical methods to estimate the ground strains for incident seismic waves, (b) to develop a statistical estimation technique of the ground strains, and finally (c) to compare the theoretical estimation with the observed data which was measured at 441 sites in the 1999 Chi-Chi Earthquake in Taiwan.

• Journal of the Korea Society for Simulation
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• v.2 no.1
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• pp.125-133
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• 1993

A statistical method is described for estimation of the unknown constants in a theory using both of the computer simulation data and the real experimental data, The best linear unbiased predictor based on a spatial linear model is fitted from the computer simulation data alone. Then nonlinear least squares estimation method is applied to the real experimental data using the fitted prediction model as if it were the true simulation model. An application to the computational nuclear fusion devices is presented, where the nonlinear least squares estimates of four transport coefficients of the theoretical nuclear fusion model are obtained.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.8
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• pp.602-605
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• 2004

A novel motion vector re-estimation technique for transcoding into lower spatial resolution is proposed. This technique is based on the fact that the block matching error is proportional to the complexity of the reference block with Taylor series expansion. It is shown that the motion vectors re-estimated by the proposed method are closer to optimal ones and offer better quality than those of previous techniques.

• Journal of Korean Society of Forest Science
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• v.104 no.1
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• pp.117-126
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• 2015

Forest statistics of local administrative districts have many social needs, nevertheless we have some difficulties for working out an accurate statistics because of insufficient data in small-area level. Thus, new small-area estimation method has to set aside additional data, decrease errors of statistics and consider the local forest characteristics at the same time. In this study, we researched the spatial divisions that can set aside additional data for statistics production and satisfy the major premise, which is "forest characteristics of spatial divisions have to be equal to that of small-area". And we compared synthetic estimation methods based on three different spatial divisions(provinces, neighbor districts and new expanded districts). New expanded districts were divided based on the criteria of climate, soil type and tree species composition that affects local forest characteristics. Small-area statistics were assessed in terms of the ability to estimate local forest characteristics and consistency within large-area statistics. As a result, new expanded districts synthetic estimation was assessed to calculate statistics that reflects local forest characteristics better than other two estimation methods. Moreover, this synthetic estimation method produced the statistics that was included within 95% confidence interval of large-area statistics and was the closer to large-area statistics than the neighbor districts synthetic estimation.