• Journal of Forest and Environmental Science
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• v.24 no.3
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• pp.159-164
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• 2008

Forest inventory is a commercial term meaning the preparation of detailed descriptive list of articles with number, quantity and value of each item included. Forest inventory deals with the measurement of trees and stands, the estimation of their volume, growth prediction, biomass, carbon stocks and the description tree characteristics, as well as the land upon which they are growing. National Forest Inventory Center (NFIC) in Korea conducts national forest inventory every 5 years to obtain accurate baseline data for national forest policy. The permanent sample plot data used in were collected by NFI. The objective of this study was to develop methods for quantifying forest resources at national scale based on $5^{th}$ National Forest Inventory (NFI) data in Korea. Forest land area decreased from 6.44 to 6.38 million ha between 1997 and 2007, continuing a slight downward trend in area beginning in the late 1990s. However forest resources of the Korea have continued improving in general condition and quality, as measured by increased average size and volume of trees. Growing-stock volume of the Korea increased from 17 to 123.79 cubic meter per ha between 1976 and 2007. The biomass in Korea was estimated to be 153.81 tons per hectare and carbon stocks in Korea was estimated to be 84.36 tons per hectare by NFI data. This information is important for government officials, public administration, the private business sector, and the researcher. Forest Inventory should be implemented in a way to be able to monitor and assess the forests continuously.

• Journal of Korean Society of Forest Science
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• v.95 no.6
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• pp.690-695
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• 2006

This study was carried out to develop a system for forest resources inventory using PDA. The Forest Inventory Software running on PDA was developed based on a Forest Resources Inventory Method by Korea Forestry Service and 4th National Forest Inventory Method. The forest inventory data stored in PDA contains sea level and GPS positioning data. Forest inventory input items are 34 tree species, 18 diameter class by each tree species, number of trees, tree height per each diameter class, thickness of bark, and annual growth of tree. Application test of the software with the forest workers shorted that, hours of forest works were remarkably reduced. It is possible to do forest inventory effectively using Forest Inventory Software developed by this study. Therefore, investigation and management expenses can be reduced and labor productivity will be improved.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.4
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• pp.77-88
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• 2017

This study developed an inventory, using GIS-based resource assessment, for assisting forest management planning. The major inventory contents were relationally integrated, using field sample plots, to extract and calculate attributes such as general status, forest stand condition, forest site condition, forest site and soil area (ha) and growing stock (weight, in tons). Evaluating the efficiency of forest management plan implementations is critical to effective health and sustainability at a larger functional level, specifically in bamboo forests. This inventory is a valuable tool for decision-making, such as developing a long-term management plan for sustainably managing bamboo resources.

• Journal of Korean Society of Forest Science
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• v.110 no.4
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• pp.496-503
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• 2021

Pinus densiflora is an essential tree species native to the Republic of Korea (ROK) and covers most of the total natural forest areas in the ROK. This study was conducted to understand the site characteristics and stand structure of P. densiflora forests distributed at sites where P. densiflora covered over 50% of the stand basal area during the 7th National Forest Inventory (NFI) period from 2016 to 2020. P. densiflora dominated 3,665 circular sample plots (400 m²). P. densiflora forests predominated at elevations less than 600 m above sea level (a.s.l). However, most P. densiflora forests were distributed at the slopes facing south and west over 800 m a.s.l. At altitudes below 800 m, they were distributed at all slopes but dominated at the southern and western slopes. P. densiflora grew mainly in the soils of sandy loam, loam, or silt loam with relative infertility. Dominant tree species distributed with P. densiflora were Quercus mongolica, Q. variabilis, Q. serrata, Prunus serrulata var. pubescens and Castanea crenata by the descending order. P. densiflora, P. thunbergii, and P. rigida were grown in large DBH classes, Quercus species and Fraxinus rhynchophylla in middle DBH classes, while Juniperus rigida and Styrax japonicus in small DBH classes. Dominant tree species distributed mainly at the lower layer of P. densiflora stands were Rhododendron mucronulatum, Q. serrata, Lindera obtusiloba, Fraxinus sieboldiana, Toxicodendron trichocarpum and Rhododendron schlippenbachii by the descending order.

• Journal of Korean Society of Forest Science
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• v.111 no.1
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• pp.100-107
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• 2022

Quercus mongolica is an important deciduous tree species in the Republic of Korea; it covers most of the total natural deciduous forest area in the country. In this study, the site characteristics and stand structure of Q. mongolica forests were investigated at sites where Q. mongolica occupied >50% of the total basal area during the 7th National Forest Inventory period (2016-2020). The total number of circular sample plots (400 m²) of Q. mongolica forests was 1,421. These forests were mainly dominant at >800 m above sea level (a.s.l). However, they were also distributed on north-facing slopes at <600 m a.s.l. and gradually on southern slopes with ascending altitudes. Quercus mongolica forests were distributed in silt loam, loam, or sandy loam soils with relatively high fertility. Dominant species distributed with Q. mongolica included Pinus densiflora, Quercus variabilis, Acer pseudosieboldianum, Fraxinus rhynchophylla, and Quercus serrata. Pinus densiflora and Q. variabilis grew in large DBH classes, Q. serrata grew in middle DBH classes, and A. pseudosieboldianum and F. rhynchophylla grew in small DBH classes. The dominant species distributed at the lower layer of Q. mongolica forests were Sasa borealis, Lindera obtusiloba, Rhododendron mucronulatum, Rhododendron schlippenbachii, Q. mongolica, and Fraxinus sieboldiana.

• Journal of Environmental Impact Assessment
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• v.19 no.6
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• pp.573-581
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• 2010

Natural ecosystem is an essential part to connect with the plan for biodiversity conservation in response strategy against climate change. For connecting biodiversity conservation with climate change strategy, Europe, America, Japan, and China are making an effort to discuss protection necessity through national biodiversity valuation but precedent studies lack in Korea. In this study, we made biodiversity maps representing biodiversity distribution range using species richness in National Forest Inventory (NFI) and Forest Description data. Using regression tree algorithm, we divided various classes by decision rule and constructed biodiversity maps, which has accuracy level of over 70%. Therefore, the biodiversity maps produced in this study can be used as base information for decision makers and plan for conservation of biodiversity & continuous management. Furthermore, this study can suggest a strategy for increasing efficiency of forest information in national level.

• Korean Journal of Agricultural Science
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• v.43 no.3
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• pp.299-319
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• 2016

The National Forest Inventory (NFI) is important for providing fundamental data for basic forest planning and the establishment of forest policies for the purpose of implementing sustainable forest management. The purpose of this study is to present the development of Korea's NFI including legal basis, sampling design, and measured variables and to review the usage of NFI data. The survey methods and forestry statistics among the Unites States, Canada, Japan, China, and European countries were briefly compared. Total 140 publications utilizing NFI data between 2008 and 2015 were categorized with 15 subjects. Korea has conducted the NFI 6 times since 1971, but only the $6^{th}$ NFI is comparable with the fifth, the previous NFI, because the permanent sampling plots have been shared between the periods. The Korean Forestry Statistics contains only half as many variables as that of advanced countries in Forestry. More researches were needed to improve consistent measurement of diverse variables through implementation of advanced technologies. Additional data for Forest Health Monitoring since the NFI $6^{th}$ must be under quality control which will be an essential part of the inventories for providing the chronological change of forest health.

• Journal of Korean Society of Forest Science
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• v.100 no.1
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• pp.62-69
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• 2011

Six commonly used non-linear growth functions were fitted to individual tree height-dbh data of eight major tree species measured by the $5^{th}$ National Forest Inventory in Chungcheong province. A total of 2,681 trees were collected from permanent sample plots across Chungcheong province. The available data for each species were randomly splitted into two sets: the majority (90%) was used to estimate model parameters and the remaining data (10%) were reserved to validate the models. The performance of the models was compared and evaluated by $R^2$, RMSE, mean difference (MD), absolute mean difference (AMD) and mean difference(MD) for diameter classes. The combined data (100%) were used for final model fitting. The results showed that these six sigmoidal models were able to capture the height-diameter relationships and fit the data equally well, but produced different asymptote estimates. Sigmoidal growth models such as Chapman-Richards, Weibull functions provided the most satisfactory height predictions. The effect of model performance on stem volume estimation was also investigated. Tree volumes of different species were computed by the Forest Resources Evaluation and Prediction Program using observed range of diameter and the predicted tree total height from the six models. For trees with diameter less than 30 cm, the six height-dbh models produced very similar results for all species, while more differentiation among the models was observed for large-sized trees.

• Journal of Forest and Environmental Science
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• v.24 no.3
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• pp.127-135
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• 2008

The mission of the Forest Inventory and Analyis (FIA) program of the Forest Service, U.S. Department of Agriculture, is to conduct the national forest inventory of the United States of America for purposes of estimating the area of forest land; the volume, growth, and removal of forest resources; and the health of the forest. Users of FIA data, estimates, and related products include land managers, policy and decision-makers, forest industry, environmental organizations, and university researchers. To accomplish its mission, the FIA program has established a sampling design with an intensity of approximately one permanent plot per 2,400 ha across the entire country. Depending on the region of the country, each plot is remeasured at intervals of five or 10 years. The program releases data annually and reports estimates at the county level for each state every five years. Due to budgetary constraints and natural variability among plot observations, sufficient numbers of plots cannot be measured to satisfy precision guidelines for the estimates of many variables unless the estimation process is enhanced using ancillary data. Classified satellite imagery has been demonstrated to be a source of ancillary data that can be used with stratified estimation techniques to increase the precision of estimates with little corresponding increase in costs. A crucial factor restricting the utility of FIA data is that the exact locations of inventory plots cannot be released to the public. Thus, users are generally not able to obtain estimates for small areas or for their own areas of interest if exact plot locations are required. To compensate, satellite imagery, inventory plot data, and the k-Nearest Neighbors technique are being used to construct Internet-based maps of forest attributes from which estimates for arbitrary user-defined areas of interest may be obtained.

• Journal of Korean Society of Forest Science
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• v.98 no.2
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• pp.178-182
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• 2009

A new mixed-effects model was developed that predicts individual-tree total height for Pinus densiflora trees in Gangwon province as a function of individual-tree diameter (cm). The mixed-effects model contains two random-effects parameters. Maximum likelihood estimation was used to fit the model to 560 height-diameter observations of individual trees measured throughout Gwangwon province in 2007 as part of the National Forest Inventory Program in Korea. The new model is an improvement over fixed-effects models because it can be calibrated to a local area, such as an inventory plot or individual stand. The new model also appears to be an improvement over the Forest Resources Evaluation and Prediction Program for the ten calibration trees used in this study. An example is provided that describes how to estimate the random-effects parameters using ten calibration trees.