• Korean Journal of Soil Science and Fertilizer
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• v.40 no.5
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• pp.429-434
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• 2007

This study was conducted to estimate site productivity of Quercus acutissima and Quercus mongolica by four forest climatic zones. We used site environmental variables (28 geographical and pedological factors) and site index as a site productivity indicator from nation-wide 23,315 stands. Based on multiple regression analysis between site index and major environmental variables, the best-fit multivaliate models were made by each species and forest climatic zone. Most of site index prediction models by species were regressed with seven to eight factors, including altitude, relief, soil depth, and soil moisture etc. For those models, three evaluation statistics such as mean difference, standard deviation of difference, and standard error of difference were applied to the test data set for the validation of the results. According to the evaluation statistics, it was found that the models by climatic zones and species fitted well to the test data set with relatively low bias and variation. Also having above middle of site index range, total area of productive sites for the two Quercus spp. estimated by those models would be about 6% of total forest area. Northern temperate forest zone and central temperate forest zone had more productive area than southern temperate forest zone and warm temperate forest zone. As a result, it was concluded that the regressive prediction with site environmental variables by climatic zones and species had enough estimation capability of forest site productivity.

• Journal of Forest and Environmental Science
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• v.24 no.3
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• pp.155-158
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• 2008

Site index is the essential tool for forest management to estimate the productivity of forest land Generally, site index equation is developed and used by relationship between stand age and dominant tree heights. However, there is a limit to use the site index equation in the application of variable ages, environmental influence, and estimation of site index for unstocked land. Therefore, it was attempted to develop a new site index equations based on various environmental factors including site and topographical variables. This study was conducted to develop regional site index equations based on the relationship between site index and soil factors for Pinus densiflora. Environmental factors that obtained from GIS application, were selected by stepwise-regression. Site index Equation was estimated by multiple regression from selected factors. Four environmental factors were selected in the final site index equations by stepwise regression. It was observed that coefficients of determination for site index equations were ranged from 0.34 which seem to be relatively low but good enough for estimation of forest stand productivity. The site index equations developed in this study were also verified to be useful by three evaluation statistics such as model's estimation bias, model's precision and mean square error type of measure.

• Korean Journal of Soil Science and Fertilizer
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• v.42 no.3
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• pp.160-166
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• 2009

We estimated site productivity for unstocked land based on the relationship between site index (i.e., average height of dominant trees at fixed age) and soil physico-chemical properties of Pinus densiflora stands. Site index relates to a direct method of determining a tree's response to a specific environment such as forest soil and climate conditions. We selected 78 sites in 22 P. densiflora stands of central temperate forest zone, and sampled soils for physicochemical analyzing. And 13 properties of soils were statistically treated by stepwise regression. In the degree of contribution of the variables to site index, the highly effective variables in A horizon were OM, clay content, sand content, available $P_2O_5$, and Exch. $Ca^{{+}{+}}$ inorder, and in B horizon T.N., O.M., Soil pH, cation exchange capacity(C.E.C.), and sand content in order. In both A and B horizon of the soil for P. densiflora stands, the variables commonly contributed to the site index were sand content and OM. These results may be useful to provide not only important criteria for establishment of Pinus densiflora stand sespecially in unstocked land but also aguidance for reforestation.

• Journal of Korean Society of Forest Science
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• v.112 no.1
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• pp.23-31
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• 2023

Predicting forest productivity is essential to evaluate sustainable forest management or to enhance forest ecosystem services. Ordinary least squares (OLS) and partial least squares (PLS) regression models were used to develop predictive models for forest productivity (site index) from the site characteristics and soil profile, along with soil physical and chemical properties, of 112 Quercus mongolica stands. The adjusted coefficients of determination (adjusted R²) in the regression models were higher for the site characteristics and soil profile of B horizon (R²=0.32) and of A horizon (R²=0.29) than for the soil physical and chemical properties of B horizon (R²=0.21) and A horizon (R²=0.09). The PLS models (R²=0.20-0.32) were better predictors of site index than the OLS models (R²=0.09-0.31). These results suggest that the regression models for Q. mongolica can be applied to predict the forest productivity, but new variables may need to be developed to enhance the explanatory power of regression models.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.2
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• pp.89-97
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• 2012

This study was conducted to estimate forest site productivity and productive areas of Quercus acutissima and Quercus mongolica using environmental factors including climatic variables. Using the data set from digital forest site map and forest climatic map, a total of 42 environmental variables were regressed on site index for developing the best site index equations for Quercus acutissima and Quercus mongolica. Five to six environmental factors by species were selected as independent variables in the best site index equations. For the site index equations, three evaluation statistics (i.e., mean difference, standard deviation of difference, and standard error of difference) were applied to the test data set for the validation of the results, The site index equations fitted well to the test data set 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. Finally, based on the site index equations, the productive areas by species were estimated by applying GIS technique to the digital forest maps. In addition, the distribution of productive areas by species was illustrated.

• Journal of Korean Society of Forest Science
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• v.112 no.2
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• pp.209-216
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• 2023

This study aimed to use national forest inventory data to develop a forest productivity index and yield prediction model of a Tilia amurensis stand. The site index displaying the forest productivity of the Tilia amurensis stand was developed as a Schumacher model, and the site index classification curve was generated from the model results; its distribution growth in Korea ranged from 8-16. The growth model using age as an independent variable for breast height and height diameter estimation was derived from the Chapman-Richards and Weibull model. The Fitness Indices of the estimation models were 0.32 and 0.11, respectively, which were generally low values, but the estimation-equation residuals were evenly distributed around 0, so we judged that there would be no issue in applying the equation. The stand basal area and site index of the Tilia amurensis stand had the greatest effect on the stand-volume change. These two factors were used to derive the Tilia amurensis stand yield model, and the model's determination coefficient was approximately 94%. After verifying the residual normality of the equation and autocorrelation of the growth factors in the yield model, no particular problems were observed. Finally, the growth and yield models of the Tilia amurensis stand were used to produce the makeshift stand yield table. According to this table, when the Tilia amurensis stand is 70 years old, the estimated stand-volume per hectare would be approximately 208 m³ . It is expected that these study results will be helpful for decision-making of Tilia amurensis stands management, which have high value as a forest resource for honey and timber.

• Journal of Korean Society of Forest Science
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• v.111 no.3
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• pp.428-434
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• 2022

This study was conducted to derive the site index of forest productivity of Robinia pseudoacacia (honey plant) to characterize suitable planting sites and to investigate the effect of the site environmental factors on the site index using the quantification theory I method. The data used in the analysis were growth factors (stand age, dominant height, etc.) of the 6th national forest resources survey and various site environmental factors of a forest soil map (1:5,000). The average site index value of the R. pseudoacacia stand in Korea was 14 (range, 8 to 18). The environmental factors affecting the site index were parent rock, climatic zone, soil texture, local topography, and altitude. The accuracy of the estimation model using quantification theory I was only 33%. However, the correlation between the site index and the site environmental factors was statistically significant at the 1% level. Results of quantification analysis between site index and site environmental factors revealed that metamorphic and igneous rocks received high grades as parent rocks, climate zones received higher grades than central temperate zone, clay loam and silt loam received high grades in soil texture, and hillside received a high grade in local topography. Analysis of the partial correlation between site topographical factors and forest productivity (site index) found that soil class and altitude were partially correlated to x by 0.4129 and 0.4023, respectively, indicating that these factors are the most influential variables.

• 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.95 no.1
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• pp.38-44
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• 2006

Using GJS and fuzzy sets, a model was developed for evaluating the site-suitability of forest stands for extracting sap of Acer pictum Thunb. var. mono in Mt. Baekun area. In the model, the productivity of sap extraction was expressed as the function of biotic and abiotic site factors. Among the factors, the topographic terrain conditions and accessibility of forest stands were chosen to consider working environment of the sap extraction. The difference in measurements of the factors between sap-extraction and non-sap-extraction forest stands was used in determining the weight of the relative importance for sap extraction productivity. The weight for distance-to-stream, vegetation type and shading condition turned out relatively higher than those for tree age, distance-to-road and DBH. Based on the results, a site-suitability map in Mt. Baekun area for sap extraction was built.