• Journal of Korean Society for Geospatial Information Science
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• v.18 no.4
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• pp.119-129
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• 2010

The joint use of remotely sensed data and field measurements has been widely used to estimate aboveground carbon stock in many countries. Recently, Korea Forest Research Institute has developed new carbon emission factors for kind of tree, thus more accurate estimate is possible. In this study, the aboveground carbon stock of Danyang area in South Korea was estimated using k-Nearest Neighbor(kNN) algorithm with the 5th National Forest Inventory(NFI) data. Considering the spectral response of forested area under the climate condition in Korea peninsular which has 4 distinct seasons, Landsat TM seasonal satellite images were collected. As a result, the estimated total carbon stock of Danyang area was ranged from 3542768.49tonC to 3329037.51tonC but seasonal trends were not found.

• Journal of agriculture & life science
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• v.43 no.3
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• pp.7-14
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• 2009

Some results of the 5th Korean National Forest Inventory Program measured in 2007 were used to analyze annual diameter growth characteristics for major tree species distributed in Chungnam province. A total of 717 sample trees from 49 plots distributed in Chungnam province were measured and analyzed for annual diameter growth characteristics. As stand age and stand density increased, annual diameter growth rates for major species tended to decrease. The species of Prunus sargentii(2.14mm/yr) showed the best annual diameter growth rates and the others are Quercus serrata(2.10mm/yr), Pinus thunbergii(2.03mm/yr), Pinus densiflora(1.91mm/yr), and Castanea crenata(1.90mm/yr) in order. This information could be very useful to understand annual diameter growth characteristics for major species distributed in Chungnam province.

• Journal of Climate Change Research
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• v.4 no.2
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• pp.177-188
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• 2013

In this research, forest cover distribution change, forest volume and carbon stock in Yongin-city, Gyeonggi procince were estimated focused on the forest of Yongin-City using forest type map and HyTAG model in relation to climate change. Present forest volume of Yongin-city was estimated using the data from $5^{th}$ Forest Type Map and Korean National Forest Inventory (NFI). And for the future 100 years potential forest distribution by 10-year interval were estimated using HyTAG model. Forest volume was also calculated using algebraic differences form of the growth model. According to the $5^{th}$ Forest Type Map, present needleleaf forest occupied 37.8% and broadleaf forest 62.2% of forest area. And the forest cover distribution after 30 years would be changed to 0.13% of needleleaf forest and 99.97% of broadleaf forest. Finally, 60 years later, whole forest of Yongin-city would be covered by broad-leaf forest. Also the current forest carbon stocks was measured 1,773,862 tC(56.79 tC/ha) and future carbon stocks after 50 years was predicted to 4,432,351 tC(141.90 tC/ha) by HyTAG model. The carbon stocks after 100 years later was 6,884,063 tC (220.40 tC/ha). According to the HyTAG model prediction, Pinus koraiensis, Larix kaempferi, Pinus rigida, and Pinus densiflora are not suitable to the future climate of 10-year, 30-year, 30-year, and 50-year later respectively. All Quercus spp. was predicted to be suitable to the future climate.

• Journal of Climate Change Research
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• v.5 no.2
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• pp.127-137
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• 2014

The main purpose of this study is to estimate tradial growth response and to predict the potential spatial distribution of major tree species(Pinus densiflora, Quercus mongolica, Quercus spp., Castanea crenata and Larix kaempferi) in South Korea, considering climate and topographic factors. To estimate radial growth response, $5^{th}$ National Forest Inventory data, Topographic Wetness Index (TWI) and climatic data such as temperature and precipitation were used. Also, to predict the potential spatial distribution of major tree species, RCP 8.5 Scenario was applied. By our analysis, it was found that the rising temperature would have negative impacts on radial growth of Pinus densiflora, Castanea crenata and Larix kaempferi, and positive impacts on that of Quercus mongolica, Quercus spp.. Incremental precipitation would have positive effects on radial growth of Pinus densiflora and Quercus mongolica. When radial growth response considered by RCP 8.5 scenario, it was found that the radial growth of Pinus densiflora, Castanea crenata and Larix kaempferi would be more vulnerable than that of Quercus mongolica and Quercus spp. to temperature. According to the climate change scenario, Quercus spp. including Quercus mongolica would be expected to have greater abundance than its present status in South Korea. The result of this study would be helpful for understanding the impact of climatic factors on tree growth and for predicting the distribution of major tree species by climate change in South Korea.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.4
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• pp.81-99
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• 2015

The acceleration of global warming has required better understanding of carbon cycles over local and regional areas such as the Korean peninsula. Since forests serve as a carbon sink, which stores a large amount of terrestrial carbon, there has been a demand to accurately estimate such forest carbon sequestration. In Korea, the National Forest Inventory(NFI) has been used to estimate the forest carbon stocks based on the amount of growing stocks per hectare measured at sampled location. However, as such data are based on point(i.e., plot) measurements, it is difficult to identify spatial distribution of forest carbon stocks. This study focuses on urban areas, which have limited number of NFI samples and have shown rapid land cover change, to estimate grid-based forest carbon stocks based on UNFCCC Approach 3 and Tier 3. Land cover change and forest carbon stocks were estimated using Landsat 5 TM data acquired in 1991, 1992, 2010, and 2011, high resolution airborne images, and the 3rd, 5th~6th NFI data. Machine learning techniques(i.e., random forest and support vector machines/regression) were used for land cover change classification and forest carbon stock estimation. Forest carbon stocks were estimated using reflectance, band ratios, vegetation indices, and topographical indices. Results showed that 33.23tonC/ha of carbon was sequestrated on the unchanged forest areas between 1991 and 2010, while 36.83 tonC/ha of carbon was sequestrated on the areas changed from other land-use types to forests. A total of 7.35 tonC/ha of carbon was released on the areas changed from forests to other land-use types. This study was a good chance to understand the quantitative forest carbon stock change according to the land cover change. Moreover the result of this study can contribute to the effective forest management.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.4
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• pp.69-85
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• 2014

Carbon stocks of NFI plots can be accurately estimated using field survey information. However, an accurate estimation of carbon stocks in other unsurveyed sites is very difficult. In order to fill this gap, various spatial information can be used as an ancillary data. In South Korea, there is the 1:5,000 forest type map that was produced by digital air-photo interpretation and field survey. Because this map contains very detailed forest information, it can be used as the high-quality spatial data for estimating carbon stocks. In this study, we compared three upscaling methods based on the 1:5,000 forest type map and 5th national forest inventory data. Map algebra(method 1), RK(Regression Kriging)(method 2), and GWR(Geographically Weighted Regression)(method 3) were applied to estimate forest carbon stock in Chungcheong-nam Do and Daejeon metropolitan city. The range of carbon stocks from method 2(1.39~138.80 tonC/ha) and method 3(1.28~149.98 tonC/ha) were more similar to that of previous method(1.56~156.40 tonC/ha) than that of method 1(0.00~93.37 tonC/ha). This result shows that RK and GWR considering spatial autocorrelation can show spatial heterogeneity of carbon stocks. We carried out paired t-test for carbon stock data using 186 sample points to assess estimation accuracy. As a result, the average carbon stocks of method 2 and field survey method were not significantly different at p=0.05 using paired t-test. And the result of method 2 showed the lowest RMSE. Therefore regression kriging method is useful to consider spatial variations of carbon stocks distribution in rugged terrain and complex forest stand.

• Journal of Korean Society of Forest Science
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• v.97 no.6
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• pp.627-633
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• 2008

This study was conducted to estimate volume growth rates for major Quercus species distributed in Korea, and based on the data collected from the 5th National Forest Inventory. Volume growth rates were estimated by each age class for each species, and their similarity or distinction was statistically analyzed. It was also intended to compare the resulted volume growth rates with the existing growth rates, and to develope a volume growth rate estimation model for the Quercus species. Six major Quercus species were considered in this study; Quercus acutissima, Quercus aliena, Quercus serrata, Quercus variabilis, Quercus dentata, and Quercus mongolica. Based on the data collected from the 5th National Forest Inventory, the diameter growth rates and the height growth rates were estimated for each species, and then the volume growth rates were estimated with the given diameter and height growth rates. To examine the distinction between species or age classes, statistical analyses such as ANOVA and Duncan's multiple range test were applied. The results indicated that the volume growth rate was 10% in the age class II, 6% in the age class III, and lower in the subsequent classes. In addition, the volume growth rates of Quercus acutissima, Quercus aliena, and Quercus serrata were relatively high compared to those of Quercus variabilis, Quercus dentata, and Quercus mongolica. According to their growth rates, the six Quercus species were classified into two groups; high-growth-rate group and low-growth-rate group. Statistical analysis conducted to examine the difference between and within the groups showed that there is no significant difference within groups, while significant between groups. Based on the results, volume growth rate estimation model were finally developed for each group. The classification of the Quercus species suggested in this study was not the same with that of existing volume growth estimation. Thus, it is necessary to improve the existing volume growth rate or its estimation system.

• Journal of Korean Society of Forest Science
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• v.105 no.3
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• pp.351-359
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• 2016

This study was conducted to analyze the effect of climate change on the tree-ring growth of Pinus koraiensis in Korea. Annual tree-ring growth data of P. koraiensis collected by the $5^{th}$ National Forest Inventory were first organized to analyze yearly growth patterns of the species. When tree-ring growth data were analyzed through cluster analysis based on similarity of climatic conditions, five clusters were identified. Yearly growing degree days and standard precipitation index based on daily mean temperature and precipitation data from 1951 to 2010 were calculated by cluster. Using the information, yearly temperature effect index(TEI) and precipitation effect index(PEI) by cluster were estimated to analyze the effect of climatic conditions on the growth of the species. Tree-ring growth estimation equations by cluster were developed by using the product of yearly TEI and PEI as independent variable. The tree-ring growth estimation equations were applied to the climate change scenarios of RCP 4.5 and RCP 8.5 for predicting the changes in tree-ring growth by cluster of P. koraiensis from 2011 to 2100. The results of this study are expected to provide valuable information necessary for estimating local growth characteristics of P. koraiensis and for predicting changes in tree-ring growth patterns caused by climate change.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.1
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• pp.35-44
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• 2015

Forests contain a huge amount of carbon (C) and climate change could affect forest C dynamics. This study was conducted to predict the C dynamics of Pinus densiflora and Quercus variabilis forests, which are the most dominant needleleaf and broadleaf forests in Korea, using the Korean Forest Soil Carbon (KFSC) model under the two climate change scenarios (2012-2100; Constant Temperature (CT) scenario and Representative Concentration Pathway (RCP) 8.5 scenario). To construct simulation unit, the forest land areas for those two species in the 5th National Forest Inventory (NFI) data were sorted by administrative district and stand age class. The C pools were initialized at 2012, and any disturbance was not considered during the simulation period. Although the forest C stocks of two species generally increased over time, the forest C stocks under the RCP 8.5 scenario were less than those stocks under the CT scenario. The C stocks of P. densiflora forests increased from 260.4 Tg C in 2012 to 395.3 (CT scenario) or 384.1 Tg C (RCP 8.5 scenario) in 2100. For Q. variabilis forests, the C stocks increased from 124.4 Tg C in 2012 to 219.5 (CT scenario) or 204.7 (RCP 8.5 scenario) Tg C in 2100. Compared to 5th NFI data, the initial value of C stocks in dead organic matter C pools seemed valid. Accordingly, the annual C sequestration rates of the two species over the simulation period under the RCP 8.5 scenario (65.8 and $164.2g\;C\;m^{-2}\;yr^{-1}$ for P. densiflora and Q. variabilis) were lower than those values under the CT scenario (71.1 and $193.5g\;C\;m^{-2}\;yr^{-1}$ for P. densiflora and Q. variabilis). We concluded that the C sequestration potential of P. densiflora and Q. variabilis forests could be decreased by climate change. Although there were uncertainties from parameters and model structure, this study could contribute to elucidating the C dynamics of South Korean forests in future.

• Journal of Korean Society of Forest Science
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• v.106 no.2
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• pp.249-257
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• 2017

This study was conducted to analyze the relationship between tree-ring growth of Pinus densiflora and climate factors based on national forest inventory(NFI) data. Annual tree-ring growth data of P. densiflora collected by the $5^{th}$ NFI were first organized to analyze yearly growth patterns of the species. Yearly growing degree days and standard precipitation index based on daily mean temperature and precipitation data from 1951 to 2010 were calculated. Using the information, yearly temperature effect index(TEI) and precipitation effect index(PEI) were estimated to analyze the effect of climate conditions on the tree-ring growth of the species. A tree-ring growth estimation equation appropriate for P. densiflora was then developed by using the TEI and PEI as independent variables. The tree-ring growth estimation equation was finally applied to the climate change scenarios of RCP 4.5 and RCP 8.5 for predicting the changes in tree-ring growth of P. densiflora from 2011 to 2100. The results indicate that tree-ring growth of P. densiflora is predicted to be decreased over time when the tree-ring growth estimation equation is applied to the climate change scenarios of RCP 4.5 and RCP 8.5. It is predicted that the decrease of tree-ring growth over time is relatively small when RCP 4.5 is applied. On the other hand, the steep decrease of tree-ring growth was found in the application of RCP 8.5, especially after the year of 2050. The results of this study are expected to provide valuable information necessary for estimating local growth characteristics of P. densiflora and for predicting changes in tree-ring growth patterns caused by climates change.