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A Comparison of Systematic Sampling Designs for Forest Inventory
Yim, Jong Su,Kleinn, Christoph,Kim, Sung Ho,Jeong, Jin-Hyun,Shin, Man Yong Korean Society of Forest Science 2009 한국산림과학회지 Vol.98 No.2
This study was conducted to support for determining an efficient sampling design for forest resources assessments in South Korea with respect to statistical efficiency. For this objective, different systematic sampling designs were simulated and compared based on an artificial forest population that had been built from field sample data and satellite data in Yang-Pyeong County, Korea. Using the k-NN technique, two thematic maps (growing stock and forest cover type per pixel unit) across the test area were generated; field data (n=191) and Landsat ETM+ were used as source data. Four sampling designs (systematic sampling, systematic sampling for post-stratification, systematic cluster sampling, and stratified systematic sampling) were employed as optimum sampling design candidates. In order to compute error variance, the Monte Carlo simulation was used (k=1,000). Then, sampling error and relative efficiency were compared. When the objective of an inventory was to obtain estimations for the entire population, systematic cluster sampling was superior to the other sampling designs. If its objective is to obtain estimations for each sub-population, post-stratification gave a better estimation. In order to successfully perform this procedure, it requires clear definitions of strata of interest per field observation unit for efficient stratification.
Comparison of Plot Sizes for Forest Inventory in Natural Deciduous Forest In Korea
Yim, Jong-Su,Shin, Man Yong Korean Society of Forest Science 2006 한국산림과학회지 Vol.95 No.5
The plot design influences the budgets and the precision of forest inventory results. The objective of this study is to determine the efficiency of estimating forest variables such as tree density, basal area, volume, and species richness based on various plot sizes using fixed-area plot sampling in the natural deciduous forest of Pyeong-Chang County, Gang-won Province, Korea. In this study, 108 reference plots were established with a fixed plot size and shape of 0.09 ha ($30m{\times}30m$). In order to determine the optimal plot size for the interest of variables, each sample plot was established using different shapes (square, circle, and rectangle) and was divided into different plot sizes from 100 to $900m^2$. The mean relative difference (MRD) for the sum of the basal area and volume, and tree density per hectare decreased as plot size increased. But the MRD for three variables were only below 13% at the plot size of $500m^2$. Species richness for each reference stand observed ranging from 2 to 15 species, demonstrated highly positive significant relationships with plot size. The minimum plot size for the estimation of tree density, the sum of the BA and volume was determined to be about $400m^2$, whereas the estimation of species richness required a minimum plot size of $500m^2$.
Integration of Digital Satellite Data and Forest Inventory Data for Forest Cover Mapping in Korea
( Jong Su Yim ),( Christoph Kleinn ),( Hyun Kook Cho ),( Man Yong Shin ) 한국산림과학회 2010 Forest Science And Technology Vol.6 No.2
Forest cover maps are a major product of the National Forest Inventory (NFI) system in Korea. The main objective of this study is to evaluate the potential of digital satellite imagery in combination with field plot data from the NFI to support forest cover classification. Field plot data from the NFI and Landsat TM for a test area were used to generate a forest cover map through pixel-wise classifiers. For classification, two pixel-wise classifiers, the Nearest Neighbor (NNC) and the Maximum likelihood (MLC) were applied and their results were compared with a classification from field plot data per sub-plot (n=970). The NNC yielded higher accuracy than the MLC. The estimated kappa for NNC was about twice as high as for MLC. The NNC classified image was also assessed using existing digital forest map derived from aerial photo interpretation as a reference. The accuracy, however, was modest (=0.28). The goodness-of-fit test indicates that the digital forest map and the MLC classified image differ significantly from the result of field plots, while a statistically significant difference between field data and the NNC classified image was not found.
국가산림자원조사 고정표본점 자료를 활용한 산림자원변화평가에 관한 고찰
임종수 ( Jong Su Yim ),김은숙 ( Eun Sook Kim ),김철민 ( Chel Min Kim ),손영모 ( Yeong Mo Son ) 한국산림과학회 2015 한국산림과학회지 Vol.104 No.2
Since 2006, new national forest inventory in Korea has been restructured to assess current status and and monitor the changes in forest resources based on permanent sample plots. The objective of estimate this study is to assess changes in forest resources such as land use/cover categories and forest stand variables. For this study, permanent plot data were collected between 2006-2008 and 2011-2013 in Chungcheongbuk-do, respectively. In order to produce land use/cover change matrix which plays an important role as an activity data for estimating GreenHouse Gas inventory, permanent plots were classified into six land use/cover categories. Additionally, matrixes for assessing the changes in age class and dominant tree species can provide more detailed information. For forest stand variables(tree density, basal area, growing stock, mean diameter at breath height, and mean height), their growth and change were assessed. The periodic annual growth ratios for tree density and basal area were slightly declined whereas that of growing stock was estimated to be about 3.7%. The uncertainty of changes in forest stand variables is less than 5%, except for tree density (RSE: 58%). The variation of tree density is relatively high compared to the other variables.
위성영상자료 및 국가 산림자원조사 자료를 이용한 산림 바이오매스 추정
임종수 ( Jong Su Yim ),한원성 ( Won Sung Han ),황주호 ( Joo Ho Hwang ),정상영 ( Sang Young Chung ),조현국 ( Hyun Kook Cho ),신만용 ( Man Yong Shin ) 대한원격탐사학회 2009 大韓遠隔探査學會誌 Vol.25 No.4
본 연구는 전라북도 무주군을 대상으로 제5차 국가산림자원조사 자료와 위성영상(Landsat TM-5)자료를 이용하여 산림 바이오매스를 추정하고 이를 토대로 바이오매스 주제도를 작성하고자 하였다. 먼저 국가산림자원조사의 야외 표본점 자료를 이용하여 조사표본점의 단위면적 당 축적을 산출하고, 바이오매스변환계수를 적용하여 산림 바이오매스를 추정하였다. 본 연구에서는 위성영상 자료를 이용한 산림 바이오매스 추정을 위해 회귀모형을 이용하는 방법과 최근린 기법(k-Nearest Neighbor)을 이용하는 두 가지 방법을 사용하였는데, 이 두 가지 방법에 의해 추정된 산림 바이오매스를 국가산림자원조사 자료에 의한 추정치와 비교하여 최적의 방법을 선정하였다. 추정된 바이오매스 통계량의 비교를 위해 교차대조법을 이용하여 RMSE(Root Mean Square Error)와 평균편의(Mean Bias)를 산출하였는데, 그 결과 두 방법 모두 유사한 추정오차(RMSE: 63.75~67.26ton/ha)와 편차(±1 ton/ha)를 보여 정확성 면에서는 큰 차이가 없는 것으로 나타났다. 하지만 최근린 기법을 이용하여 산림 바이오매스를 추정하는 것이 효율성 측면에서 보다 유리할 것으로 평가되었다. 최근린 기법에 의해 추정된 무주군의 산림 바이오매스는 약 839만 톤으로 나타났으며 단위면적당 평균은 149톤/ha인 것으로 분석되었다. 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 5th 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 k-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 (63.75~67.26ton/ha) and mean bias (±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.