• Journal of Korean Society of Forest Science
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• v.102 no.3
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• pp.437-445
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• 2013

This study was conducted to develop site index equations and to estimate productive areas of Quercus acutissima by ecoprovince in Korea using environmental factors. Using the large data set from both a digital forest site map and a climatic map, a total of 48 environmental factors including 19 climatic variables were regressed on site index to develop site index equations. Four to six environmental factors for Quercus acutissima by ecoprovince were selected as independent variables in the final site index equations. The result showed that the coefficients of determination for site index equations were ranged from 0.30 to 0.41, which seem to be relatively low but good enough for the estimation of forest stand productivity. The site index equations developed in this study were also verified by three evaluation statistics such as the estimation bias of model, precision of model, and mean square error of measurement. According to the evaluation statistics, it was found that the site index equations fitted well to the test data sets with relatively low bias and variation. As a result, it was concluded that the site index equations were well capable of estimating site quality. Based on the site index equations of Quercus acutissima by ecoprovince, the productive areas by ecoprovince were estimated by applying GIS technique to the digital forest site map and climate map. In addition, the distribution of productive areas by ecoprovince was illustrated by using GIS technique.

• Journal of Korean Society of Forest Science
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• v.101 no.3
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• pp.395-404
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• 2012

This study was conducted to develop site index equations and to estimate productive areas for major coniferous species in Korea such as Pinus densiflora Sieb. et. Zucc, Pinus densiflora for. erect, Larix leptolepis and Pinus koraiensis using environmental factors. Using the large data set from both a digital forest site map and a climatic map, a total of 43 environmental factors including 15 climatic variables were regressed on site index by tree species to develop site index equations. Six environmental factors by species were selected as independent variables in the final site index equations. The result showed that the coefficients of determination for site index equations by species were ranged from 0.36 to 0.56, which seem to be relatively low but good enough for the estimation of forest stand productivity. The site index equations developed in this study were also verified by three evaluation statistics such as the estimation bias of model, precision of model, and mean square error of measurement. According to the evaluation statistics, it was found that the site index equations by species fitted well to the test data sets with relatively low bias and variation. As a result, it was concluded that the site index equations by species were well capable of estimating site quality. Based on the site index equations, the productive areas by species for all forest areas were estimated by applying GIS technique to the digital forest site map and climate map. In addition, the distribution of productive areas by species was illustrated by using GIS technique.

• Journal of Korean Society of Forest Science
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• v.98 no.6
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• pp.633-638
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• 2009

This study was conducted to develop stem taper equations and stem volume tables for Eucalyptus pellita and Acacia mangium plantations in Kalimantan, Indonesia. To derive a most adequate taper equation for the plantations, three models - Max & Burkhart, Kozak, and Lee models - were applied and their fitness were statistically analyzed by using fitness index, bias, and standard error of bias. The result showed that there is no significant difference between the three models, but the fitness index was slightly higher in the Kozak model. Therefore, the Kozak model was chosen for generating stem taper equations and stem volume tables for the Eucalyptus pellita and Acacia mangium plantations. The resulted stem volume table was compared to the local volume table used in Kalimantan regions, but no significant difference was found in the stem volume estimation. It is expected that the results of this study would provide a good information about the tree growth in abroad plantations and support a reliable decision-making for their management.

• Journal of Korea Water Resources Association
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• v.51 no.11
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• pp.1031-1041
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• 2018

ANFIS-based methodology for improving GloSea5 ensemble weather forecast is developed and evaluated in this study. The proposed method consists of two steps: pre & post processing. For ensemble prediction of GloSea5, weights are assigned to the ensemble members based on Optimal Weighting Method (OWM) in the pre-processing. Then, the bias of the results of pre-processed is corrected based on Model Output Statistics (MOS) method in the post-processing. The watershed of the Chungju multi-purpose dam in South Korea is selected as a study area. The results of evaluation indicated that the pre-processing step (CASE1), the post-processing step (CASE2), pre & post processing step (CASE3) results were significantly improved than the original GloSea5 bias correction (BC_GS5). Correction performance is better the order of CASE3, CASE1, CASE2. Also, the accuracy of pre-processing was improved during the season with high variability of precipitation. The post-processing step reduced the error that could not be smoothed by pre-processing step. It could be concluded that this methodology improved the ability of GloSea5 ensemble weather forecast by using ANFIS, especially, for the summer season with high variability of precipitation when applied both pre- and post-processing steps.

• Journal of Korea Water Resources Association
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• v.49 no.5
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• pp.423-429
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• 2016

This study aims at assessing the quality of the Advanced Microwave Scanning Radiometer 2 (AMSR2) soil moisture products onboard GCOM-W1 satellite based on Land Parameter Retrieval Model (LPRM) soil moisture retrieval algorithm with field measurements in South Korea from March to September, 2014. Results of mean bias and root mean square error between AMSR2 LPRM soil moisture products (X-band) and ground measurements showed reasonable value of 0.03 and 0.16. Also, the maximum of the Pearson correlation coefficients was 0.67, which showed good agreement in terms of temporal variability with ground measurements. By comparing AMSR2 soil moisture with in-situ measurement according to the overpass time and band frequency, X-band products on the ascending time outperformed than those of C1-band and C2-band. Furthermore, this study offers an insight into the applicability of the AMSR2 soil moisture products for monitoring various natural disasters at a large scale such as drought and flood.

• Korea journal of population studies
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• v.21 no.1
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• pp.162-183
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• 1998

This study examines the sampling bias that may have resulted from the large number of missing observations. Despite well-designed and reliable sampling procedures, the observed sample values in DSFH(Demographic Survey on Changes in Family and Household Structure, Japan) included many missing observations. The head administerd survey method of DSFH resulted in a large number of missing observations regarding characteristics of elderly non-head parents and their children. In addition, the response probability of a particular item in DSFH significantly differs by characteristics of elderly parents and their children. Furthermore, missing observations of many items occurred simultaneously. This complex pattern of missing observations critically limits the ability to produce an unbiased analysis. First, the large number of missing observations is likely to cause a misleading estimate of the standard error. Even worse, the possible dependency of missing observations on their latent values is likely to produce biased estimates of covariates. Two models are employed to solve the possible inference biases. First, EM algorithm is used to infer the missing values based on the knowledge of the association between the observed values and other covariates. Second, a selection model was employed given the suspicion that the probability of missing observations of proximity depends on its unobserved outcome.

• Journal of Astronomy and Space Sciences
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• v.34 no.4
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• pp.271-280
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• 2017

This study presents the application of satellite laser ranging (SLR) to orbit determination (OD) of high-Earth-orbit (HEO) satellites. Two HEO satellites are considered: the Quasi-Zenith Satellite-1 (QZS-1), a Japanese elliptical-inclinedgeosynchronous-orbit (EIGSO) satellite, and the Compass-G1, a Chinese geostationary-orbit (GEO) satellite. One week of normal point (NP) data were collected for each satellite to perform the OD based on the batch least-square process. Five SLR tracking stations successfully obtained 374 NPs for QZS-1 in eight days, whereas only two ground tracking stations could track Compass-G1, yielding 68 NPs in ten days. Two types of station bias estimation and a station data weighting strategy were utilized for the OD of QZS-1. The post-fit root-mean-square (RMS) residuals of the two week-long arcs were 11.98 cm and 10.77 cm when estimating the biases once in an arc (MBIAS). These residuals were decreased significantly to 2.40 cm and 3.60 cm by estimating the biases every pass (PBIAS). Then, the resultant OD precision was evaluated by the orbit overlap method, yielding three-dimensional errors of 55.013 m with MBIAS and 1.962 m with PBIAS for the overlap period of six days. For the OD of Compass-G1, no station weighting strategy was applied, and only MBIAS was utilized due to the lack of NPs. The post-fit RMS residuals of OD were 8.81 cm and 12.00 cm with 49 NPs and 47 NPs, respectively, and the corresponding threedimensional orbit overlap error for four days was 160.564 m. These results indicate that the amount of SLR tracking data is critical for obtaining precise OD of HEO satellites using SLR because additional parameters, such as station bias, are available for estimation with sufficient tracking data. Furthermore, the stand-alone SLR-based orbit solution is consistently attainable for HEO satellites if a target satellite is continuously trackable for a specific period.

• Journal of Korea Water Resources Association
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• v.46 no.11
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• pp.1129-1140
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• 2013

Precipitation is one of the important factors in the hydrological cycle. It needs to understand accurate of spatial precipitation field because it has large spatio-temporal variability. Precipitation data obtained through the Tropical Rainfall Monitoring Mission (TRMM) 3B43 product is inaccurate because it has 25 km space scale. Downscaling of TRMM 3B43 product can increase the accuracy of spatial precipitation field from 25 km to 1 km scale. The relationship between precipitation and the normalized difference vegetation index(NDVI) (1 km space scale) which is obtained from the Moderate Resolution Imaging Spectroradiometers (MODIS) sensor loaded in Terra satellite is variable at different scales. Therefore regression equations were established and these equations apply to downscaling. Two renormalization strategies, Geographical Difference Analysis (GDA) and Geographical Ratio Analysis (GRA) are implemented for correcting the differences between remote sensing-derived and rain gauge data. As for considering the GDA method results, biases, the root mean-squared error (RMSE), MAE and Index of agreement (IOA) is equal to 4.26 mm, 172.16 mm, 141.95 mm, 0.64 in 2009 and 17.21 mm, 253.43 mm, 310.56 mm, 0.62 in 2011. In this study, we can see the 1km spatial precipitation field map over Korea. It will be possible to get more accurate spatial analysis of the precipitation field through using the additional rain gauges or radar data.

• Journal of agriculture & life science
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• v.45 no.4
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• pp.65-72
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• 2011

The objective of this research is to develop biomass allometric equation for Pinus densiflora in central region and Quercus variabilis. To develop the biomass allometric equation by species and tree component, data for Pinus densiflora in central region is collected to 30 plots (70 trees) and for Quercus variabilis is collected to 15 plots (32 trees). This study is used two independent values; (1) one based on diameter beast height, (2) the other, diameter beast height and height. And the equation forms were divided into exponential, logarithmic, and quadratic functions. The validation of biomass allometric equations were fitness index, standard error of estimate, and bias. From these methods, the most appropriate equations in estimating total tree biomass for each species are as follows: $W=aD^b$, $W=aD^bH^c$; fitness index were 0.937, 0.943 for Pinus densiflora in central region stands, and $W=a+bD+cD^2$, $W=aD^bH^c$; fitness index were 0.865, 0.874 for Quercus variabilis stands. in addition, the best performance of biomass allometric equation for Pinus densiflora in central region is $W=aD^b$, and Quercus variabilis is $W=a+bD+cD^2$. The results of this study could be useful to overcome the disadvantage of existing the biomass allometric equation and calculate reliable carbon stocks for Pinus densiflora in central region and Quercus variabilis in Korea.

• Korean Journal of Remote Sensing
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• v.25 no.4
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• pp.311-320
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• 2009

This study was carried out to estimate forest biomass and to produce forest biomass thematic map for Muju county by combining field data from the 5$^{th}$ National Forest Inventory (2006-2007) and satellite data. For estimating forest biomass, two methods were examined using a Landsat TM-5(taken on April 28th, 2005) and field data: multi-variant regression modeling and t-Nearest Neighbor (k-NN) technique. Estimates of forest biomass by the two methods were compared by a cross-validation technique. The results showed that the two methods provide comparatively accurate estimation with similar RMSE (63.75$\sim$67.26ton/ha) and mean bias ($\pm$1ton/ha). However, it is concluded that the k-NN method for estimating forest biomass is superior in terms of estimation efficiency to the regression model. The total forest biomass of the study site is estimated 8.4 million ton, or 149 ton/ha by the k-NN technique.