• Journal of Climate Change Research
• /
• v.8 no.4
• /
• pp.385-391
• /
• 2017

This study was conducted to estimate litter carbon stock change from the National Forest Inventory (NFI) data for national greenhouse gas inventory report. Litter carbon stocks were calculated from the NFI dataset in NFI5 (2008) and NFI6 (2013) in Gangwon province. Total carbon stock change of litter was $0.68{\pm}0.71\;t\;C/ha$ from NFI5 (2008) to NFI6 (2013), however, there was no significant difference between the both dataset at 2008 and 2013 year. Litter carbon stock of coniferous stands was higher than deciduous stands in NFI5 (2008) and NFI6 (2013) (P<0.05). This study was limited to pilot study, so we will assess litter carbon stock using more complete data from NFI systems. It can be used as data sources for national greenhouse gas inventory report on forest sector.

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

• Korean Journal of Agricultural Science
• /
• v.43 no.3
• /
• pp.299-319
• /
• 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 Environmental Impact Assessment
• /
• v.19 no.6
• /
• pp.573-581
• /
• 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.

• Journal of Climate Change Research
• /
• v.7 no.4
• /
• pp.485-492
• /
• 2016

For reporting national greenhouse gas inventory in forest sector, the forest growing stock from the National Forest Inventory (NFI) system has used as activity data sources. The National Forest Inventory system was changed from rotation system by province to annual system by 5 years across the country. The forest growing stocks based on the new inventory system produced a different trend compared to the previous estimations. This study was implemented to recalculate previous forest growing stocks for time series consistency at a national level. The recalculation of forest growing stock was conducted in an overlap approach by the IPCC guideline. In order to support the more consistency data, we used calibration factors between applied stand volumes in 1985 and 2012, respectively. As a result, the time series of recalculated forest growing stock was to be consistency using the overlap approach and the calibration factor with the lower middle/middle site index. According to the applied overlap period, however, we will recalculate activity data using more complete data from national forest inventory system.

• Journal of Korean Society of Forest Science
• /
• v.110 no.2
• /
• pp.233-243
• /
• 2021

Considering worldwide efforts to mitigate repercussions of climate change, the South Korean government has declared to reach net zero by 2050 to achieve a carbon-neutral sustainable society. For full implementation of NDCs, the government has actively reflected its forestry sector into these strategies. Since coarse woody debris (CWD) in forests represents an enduring carbon storage, it is of particular significance to determine characteristics of changes in carbon stocks of CWD by utilizing data on dead trees monitored in permanent sample plots within national forest inventories (NFIs). In this study, therefore, both occurrence and carbon stocks of CWD were estimated in such plots using data on CWD from the 5^th, 6^th, and 7^th NFIs. Subsequently, characteristics of changes in carbon stocks over time were analyzed. Based on the analysis of 2,021 plots available for monitoring in each NFI of Gangwon Province, the volume of CWD (m³ ha^-1) was found to be 4.71 in the 5^th NFI and 4.09 in the 6^th NFI. However, the volume of CWD declined to 3.09 in the 7^th NFI. Moreover, the annual carbon stocks of CWD (ton C ha^-1) were estimated to be 0.67 in 2009, 0.64 in 2014, and 0.41 in 2019, showing a downward trend over time. This study provides a basis for future research to investigate long-term changes and estimate carbon stocks of CWD in South Korea forests.

• Journal of Korean Society of Forest Science
• /
• v.99 no.6
• /
• pp.827-835
• /
• 2010

Reliable forest statistics provides important information to meet the UNFCCC. In this respect, the national forest inventory has played a crucial role to provide the reliable forest statistics for several decades. However, the previous forest statistics calculated by administrative district has not provided spatial information in a small scale. Thus, this study focused on developing models to estimate an explicit spatial distribution of forest growing stock. For this, first, stand volume model by stand types was developed using National Forest Inventory(NFI) data. Second, forest type map was integrated with this model. NFI data were used to calculate plot-level stand volume and basal area. The stand types of NFI plot including the species composition, age class, DBH class and crown density class are very crucial data to be connected with forest type map. Finally, polygonlevel stand volume map was developed with spatial uncertainty map. Average stand volume was estimated at 85.7 $m^3$/ha in the study area, and at 95% significance interval it was ranged from 79.7 $m^3$/ha to 91.8 $m^3$/ha.

• Journal of Climate Change Research
• /
• v.6 no.1
• /
• pp.33-40
• /
• 2015

Forests are to be recognized as an important carbon sink under the UNFCCC that consist of above- and below-biomass, dead organic matter (DOM) such as dead wood and litter, and soil organic matter (SOM). In order to asses for DOM and SOM, however, it is relevant to land-use change matrices over last 20 years for each land-use category. In this study, a land-use change matrix was produced and its uncertainty was assessed using a point sampling technique with permanent sample plots in national forest inventory at Chungbuk province. With point sampling estimated areas at 2012 year for each land-use category were significantly similar to the true areas by given six land-use categories. Relative standard error in terms of uncertainty of land-use change among land-use categories ranged in 4.3~44.4%, excluding the other land. Forest and cropland covered relatively large areas showed lower uncertainty compared to the other land-use categories. This result showed that selected permanent samples in the NFI are able to support for producing land-use change matrix at a national or province level. If the $6^{th}$ NFI data are fully collected, the uncertainty of estimated area should be improved.

• Journal of Korean Society of Forest Science
• /
• v.107 no.4
• /
• pp.402-411
• /
• 2018

This study was conducted to develop ingrowth estimation equations on Pinus densiflora found in Gangwon Province and in the center of Korean Peninsula, based on the National Forest Inventory (NFI)'s permanent sampling plot data. For this study, identical sampling plots in $5^{th}$ and $6^{th}$ NFI data were collected in order to identify ingrowth amounts for the last 5 years. Following two-stage approaches in developing the ingrowth estimation equations, the logistic regression model was used in the first stage to estimate the ingrowth probability. In the second stage, regression analysis on sampling plots with ingrowth occurrence was used to estimate the ingrowth amount. A candidate model was finally selected as an optimal model after a verification based on three evaluation statistics which include mean difference (MD), standard deviation of difference (SDD) and standard error of difference (SED). In results, a logistic regression model based on the number of sampling plot which did not result in ingrowth (model VI), was selected for an ingrowth probability estimation equation and exponential function including the species composition (SC) variable was optimal for an ingrowth estimation equation (model VII). The ingrowth estimation equations developed in this study also evaluated the estimation ability in various forest stand conditions, and no particular issue in fitness or applicability was observed.

• Korean Journal of Remote Sensing
• /
• v.31 no.5
• /
• pp.449-459
• /
• 2015

The conventional National Forest Inventory(NFI)-based forest carbon stock estimation method is suitable for national-scale estimation, but is not for regional-scale estimation due to the lack of NFI plots. In this study, for the purpose of regional-scale carbon stock estimation, we created grid-based forest carbon stock maps using spatial ancillary data and two types of up-scaling methods. Chungnam province was chosen to represent the study area and for which the $5^{th}$ NFI (2006~2009) data was collected. The first method (method 1) selects forest type map as ancillary data and uses regression model for forest carbon stock estimation, whereas the second method (method 2) uses satellite imagery and k-Nearest Neighbor(k-NN) algorithm. Additionally, in order to consider uncertainty effects, the final AGB carbon stock maps were generated by performing 200 iterative processes with Monte Carlo simulation. As a result, compared to the NFI-based estimation(21,136,911 tonC), the total carbon stock was over-estimated by method 1(22,948,151 tonC), but was under-estimated by method 2(19,750,315 tonC). In the paired T-test with 186 independent data, the average carbon stock estimation by the NFI-based method was statistically different from method2(p<0.01), but was not different from method1(p>0.01). In particular, by means of Monte Carlo simulation, it was found that the smoothing effect of k-NN algorithm and mis-registration error between NFI plots and satellite image can lead to large uncertainty in carbon stock estimation. Although method 1 was found suitable for carbon stock estimation of forest stands that feature heterogeneous trees in Korea, satellite-based method is still in demand to provide periodic estimates of un-investigated, large forest area. In these respects, future work will focus on spatial and temporal extent of study area and robust carbon stock estimation with various satellite images and estimation methods.