• Journal of Korean Society of Forest Science
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• v.81 no.4
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• pp.372-382
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• 1992

Recreation planning is essential activity to meet changing demands and to protect the resources. The recreation opportunity specturm(ROS) system is a principal part of a recreational management planning. In this study, the basic concepts and tenets of the ROS system described and reviewed the feasibility of applying to forest recreation planning to the Korean national forest. In Korea, the forest land as a major recreation place has used without the rational planning process. The control for the laissez-faire use on the forest area, the classification of recreational opportunity settings is the most important process and then it make a useful tool for providing proper recreational opportunity and site development guidance. Opportunity settings classification can help maintain diversity and enhance protection of forest resources. It can also improve the quality of recreational experiences and the management action guidances. GIS technology using the ARC/INFO could be useful in current attempts to identify analysis areas for predictive modeling of forest recreation site planning.

• Korean Journal of Remote Sensing
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• v.23 no.5
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• pp.483-491
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• 2007

One of the major obstacles to classify and validate Land Cover maps is the high cost of acquiring reference data. In case of inaccessible areas such as North Korea, the high resolution satellite imagery may be used for reference data. The objective of this paper is to investigate the possibility of utilizing QuickBird high resolution imagery of North Korea that can be obtained from Google Earth data via internet for reference data of land cover classification. Monthly MODIS NDVI data of nine months from the summer of 2004 were classified into L=54 cluster using ISODATA algorithm, and these L clusters were assigned to 7 classes - coniferous forest, deciduous forest, mixed forest, paddy field, dry field, water, and built-up areas - by careful use of reference data obtained through visual interpretation of the high resolution imagery. The overall accuracy and Kappa index were 85.98% and 0.82, respectively, which represents about 10% point increase of classification accuracy than our previous study based on GCP point data around North Korea. Thus we can conclude that Google Earth may be used to substitute the traditional reference data collection on the site where the accessibility is severely limited.

• 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.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.341-344
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• 2007

A major obstacle to classify and validate Land Cover maps is the high cost of generating reference data or multiple thematic maps for subsequent comparative analysis. In case of inaccessible area such as North Korea, the high resolution satellite imagery may be used as in situ data so as to overcome the lack of reliable reference data. The objective of this paper is to investigate the possibility of utilizing QuickBird (0.6m) of North Korea obtained from Google Earth data provided thru internet. Monthly NDVI images of nine months from the summer of 2004 were classified into L=54 cluster using ISODATA algorithm, and these L clusters were assigned to 7 classes; coniferous forest, deciduous forest, mixed forest, paddy field, dry field, water and built-up area. The overall accuracy and Kappa index were 85.98% and 0.82, respectively, which represents about 10% point increase of classification accuracy than our previous study based on GCP point data around North Korea. Thus we can conclude that Google Earth may be used to substitute the traditional in situ data collection on the site where the accessibility is severely limited.

• The Korean Journal of Ecology
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• v.17 no.2
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• pp.185-201
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• 1994

The Quercus mongolica forest vegetation of Mt. Myongji was classified into two communities including four subunit communities and one typical subunit community by the Z-M method as follows: Acer pseudo-sieboldianum-Quercus mongolica community group Quercus mongolica - Isodon excisus community Quercus mongolica - Styrax obassia community Quercus mongolica - Lespedeza bicolor subunit coummunity Quercus mongolica - Aconitum longecassidatum subunit community Quercus mongolica - Rhododendrom schlippenbachii subunit community Quercus mongolica - Cornus controversa subunit community Quercus mongolica - Styrax obassia typical subunit community Acer pseudo-sieboldianum - Quercus mongolica community group was distributed over the upper region of the altitude 400m, and the differential species in the community were Carex siderosticata, Sephanandra incisa, Tripterygium regelii, and Fraxinus rhynchophylla. The vegetation patterns for the slope and azimuth showed that the highest importance value for Quercus mongolica forest was observed on the broad subxeric area, and for Carpinus cordata and Acer pseudo-sieboldianum on the wet site, for Acer mono, Styrax obassia, Fraxinus rhynchophylla and Symplocos chinensis for. pilosa on the xeric site. The best habitat condition for Quercus mongolica was found at a subxeric site at the altitude of 700-900m on southern slope and that for Acer pseudo-sieboldianum at the 700-1100m on northern slope.

• Journal of Korean Society of Forest Science
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• v.86 no.3
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• pp.365-377
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• 1997

Much of the Cumberland Plateau of Tennessee, USA is in mixed hardwoods for which there are no applicable growth and yield predictors. Use of site index as a variable in growth and yield prediction models is limited in most stands because their history is not known and many may not be even-aged. Landtypes may offer an alternative to site index for these mixed stands because they were designed to include land of about equal productivity. To determine vegetation by landtype, dependency between landtype and detailed forest type was tested with Chi-square. Differences in productivity among landtypes were tested by employing regression analyses and analysis of variance(ANOVA). Basal area growth was fitted to the nonlinear models developed by Moser and Hall(1969). Basal area growth and volume growth were also predicted as a function of initial total basal area and initial volume with linear regression by landtype and by landtype class. Differences in basal area growth and volume growth by landtype were tested with ANOVA. Dependency between site class and landtype was tested with Chi-square. Vegetation types seem to be related to landtypes in the study area although the validity of the test is questionable because of a high proportion of sparsely occupied cells. No statistically significant differences in productivity among landtypes were found in this study.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.433-438
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• 1999

The land use type of Korea is high-density. So, the image classification using coarse resolution satellite image may not provide land cover classification results as good as expected. The purpose of this paper is to compare the result of visual interpretation with that of digital image classification of 20 m resolution SPOT satellite image at Kwangju-eup, Kyunggi-do, Korea. Classes are forest, cultivated field, pasture, water and residential area, which are clearly discriminated in visual interpretation. Maximum likelihood classifier was used for digital image classification. Accuracy assessment was done by comparing each classification result with ground truth data obtained from field checking. The classification result from the visual interpretation presented an total accuracy 9.23 percent higher than that of the digital image classification. This proves the importance of visual interpretation for the area with high density land use like the study site in Korea.

• Journal of Korean Society of Forest Science
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• v.111 no.2
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• pp.311-318
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• 2022

We conducted this study to derive the site index, which is a criterion for the planting of Robinia pseudoacacia, a honey plant, and to investigate the diameter distribution change by derived site index. We applied the Chapman-Richards equation model to estimate the site index of the Robinia pseudoacacia stand. The site index was distributed within the range of 16-22 when the base age was 30 years. The fitness index of the site index estimation model was low, but we judged that there was no problem in the application because the residual distribution of the equation had not shifted to one side. We used the Weibull diameter distribution function to determine the diameter distribution of the Robinia pseudoacacia stand by site index. We used the mean diameter and the dominant tree height as independent variables to present the diameter distribution, and our analysis procedure was to estimate and recover the parameters of the Weibull diameter distribution function. We used the mean diameter and the dominant tree height of the Robinia pseudoacacia stand to show distribution by diameter class, and the fitness index for dbh distribution estimation was about 80.5%. As a result of schematizing the diameter distribution by site indices as a 30-year-old, we found that the higher the site index, the more the curve of the diameter distribution moved to the right. This suggests that if the plantation were to be established in a high site index stand, considering the suitable trees on the site, the growth of Robinia pseudoacacia woul d become active, and not onl y the production of wood but al so the production of honey would increase. We therefore anticipate that the site index classification table and curve of this Robinia pseudoacacia stand will become the standard for decision making in the plantation and management of this tree.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.9 no.1
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• pp.55-63
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• 2006

This study was carried out to analyze community character and classify forest community with phytosociological method and quadrat method to forest of Mt. Busosan in Buyeo-Gun.1. Communities by phytosociological method were classified into Pinus densiflora community and Quercus sp. community. With the classification of TWINSPAN, the community was categorized into Pinus densiflora - Quercus variabilis community and Pinus densiflora - Styrax japonica community.2. The importance value of Pinus densiflora, Quercus acutissima, Prunus sargentii, Styrax japonica, Quercus serrata, Quercus variabilis, Pinus rigida, Quercus aliena in tree layer were 83.20, 41.87, 30.93, 24.85, 23.27, 20.97, 20.28, and 9.46, respectively. The relative coverage of Stephanandra incisa, Quercus serrata, Styrax japonica, Parthenocissua tricuspidata, Rhododendron mucronulatum, Lindera obtusiloba, Prunus sargentii, Quercus variabilis, Indigofera kirilowii, Quercus acutissima, Lespedeza maximowiczii, and Acer pseudosibolianum in shrub layer were 9.62%, 9.55%, 9.18%, 7.85%, 6.18%, 5.25%, 4.82%, 4.15%, 3.98%, 3.98%, 3.55%, and 2.98%, respectively.3. According to size distribution map of diameter breast height of dominant species, the dominant species of Mt. Busosan was Pinus densiflora, and Quercus sp. such as Quercus acutissima, Quercus variabilis, and Quercus serrata may compete with the Pinus densiflora in the future.4. According to the ordination analysis of Mt. Busosan forest, Pinus densiflora - Styrax japonica community was found in moist site and Pinus densiflora - Quercus variabilis community was found in dry site.

• Journal of Korean Society of Forest Science
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• v.90 no.4
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• pp.437-444
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• 2001

This paper discusses applications of neural network to forest stand field data processing and determining suitable tree species for site-specific stand characteristics. For site-specific species selection, considered were 5 major coniferous species : P. densiflora for. erecta, L. leptolepis, P. koraiensis, P. densiflora, P. thunbergii. Among 1,320 sample plot data sets, 200 data sets with the highest site index (40 data sets for each species) were chosen as the test sets for investigation. Each data set includes 13 factors describing the site characteristics of the corresponding sample plot. The results of this investigation indicate high performance of neural network in data processing procedures for extracting data sets or measurement parameters without any recognizable pattern. These data sets or measurement parameters are those which have rare effect on site-specific species suitability or disturb pattern classification procedures of neural network because of unrecognizable patterns involved. Also the results have shown high potential of neural network in determining the best-suitable tree species for site characteristics. The % accuracy of the neural network model in determining the best-suitable tree species for site characteristics ranges from 77.6% to 91.8% associated with the combination of Site factors.