• Journal of Korean Society of Forest Science
• /
• v.111 no.3
• /
• pp.365-373
• /
• 2022

We compared carbon stocks in tree biomass and soils of Quercus acutissima, Q. mongolica, Q. serrata, and Q. variabilis stands. A total of 531 plots (Q. acutissima: 110 plots, Q. mongolica: 177 plots, Q. serrata: 96 plots, Q. variabilis: 148 plots) were examined between 2016 and 2021 to determine the tree biomass and soil carbon stocks throughout the country. The carbon stocks of tree biomass were significantly higher in Q. mongolica (mean stand age, 57 years, 144.9 Mg C ha^-1) than in Q. variabilis (mean stand age, 43 years, 123.7 Mg C ha^-1), Q. serrata (mean stand age, 43 years, 120.1 Mg C ha^-1), and Q. acutissima (mean stand age, 36 years, 113.2 Mg C ha^-1) stands. The soil carbon concentration was significantly higher in Q. mongolica (A: 43.1 mg C g-1) than in Q. serrata (31.0 mg C g-1), Q. variabilis (25.31 mg C g-1), and Q. acutissima (24.4 mg C g-1) stands. The soil carbon stocks were significantly higher in Q. mongolica (116.8 Mg C ha^-1) than in Q. acutissima (49.3 Mg C ha^-1) stands. Total carbon stocks of tree biomass and soil were highest in Q. mongolica (262 Mg C ha^-1), followed by Q. serrata (218 Mg C ha^-1), Q. variabilis (211 Mg C ha^-1), and Q. acutissima (163 Mg C ha^-1) stands. Multiple linear regressions were performed to estimate the total carbon stocks of the four Quercus spp., and results showed that total carbon stocks increased with increasing elevation, mean diameter at breast height, and basal areas. Basal area and elevation of Quercus spp. stands were important explanatory variables based on multiple linear regressions for estimating carbon stocks.

• Journal of Korean Society of Forest Science
• /
• v.98 no.1
• /
• pp.94-105
• /
• 2009

Black locust (Robinia pseudoacacia) stand is representative lowland exotic plantation with low ecological quality and arrested succession in South Korea. To facilitate succession and restore natural vegetation, small canopy gaps (${\sim}57m^2$), which can modify minimally structural variables and reduce restoration related disturbances on stand, was established in the black locust stand, and oak (Quercus serrata) seedlings were introduced in the gap. Two types of varying levels were introduced for gap creation; cutting (C) and girdling (G) on canopies. Understory removal (CU and GU) treatment was applied as subtypes of structural modification. Growth (diameter, height and leaf area) of target species and responses (species composition, diversity and coverage) of understory community were monitored during study years (2007~2008). Canopy openness was different significantly among treatments but not for light availability. Based on the result of logistic regression, growth of height and leaf area of seedlings were significant variables on seedling survival. Height and leaf area of seedlings were increased during study years, although radial growth was reduced. During study years, there were no significant differences in species composition and diversity, and total coverage increased about 20%. Increase of resources by gap creation and understory removal likely affect growth of target species. Small gap creation was effective to reduce understory responses in composition and diverstiy. Synthesized, growth of target species and responses of understory community to small canopy gap creation exhibited, in short term, possibility of utilization in alternative forest restoration and management option. Long-term monitoring is necessary to certificate effect of artificial gap creation on forest restoration.

• Korean Journal of Remote Sensing
• /
• v.31 no.2
• /
• pp.127-136
• /
• 2015

This study aims to quantify the stand-level above ground biomass in intact tropical rain forest of Brunei using airborne LiDAR data. Twenty four sub-plots with the size of 0.09ha ($30m{\times}30m$) were located in the 25ha study area along the altitudinal gradients. Field investigated data (Diameter at Breast Height (DBH) and individual tree position data) in sub-plots were used. Digital Surface Model (DSM), Digital Terrain Model (DTM) and Canopy Height Model (CHM) were constructed using airborne LiDAR data. CHM was divided into 24 sub-plots and 12 LiDAR height metrics were built. Multiple regression equation between the variables extracted from the LiDAR data and biomass calculated by using a allometric equation was derived. Stand-level biomass estimated from LiDAR data were distributed from 155.81 Mg/ha to 597.21 Mg/ha with the mean value of 366.48 Mg/ha. R-square value of the verification analysis was 0.84.

• Journal of Ecology and Environment
• /
• v.34 no.2
• /
• pp.149-156
• /
• 2011

Phenological variables derived from remote sensing are useful in determining the seasonal cycles of ecosystems in a changing climate. Satellite remote sensing imagery is useful for the spatial continuous monitoring of vegetation phenology across broad regions; however, its applications are substantially constrained by atmospheric disturbances such as clouds, dusts, and aerosols. By way of contrast, a tower-based ground remote sensing approach at the canopy level can provide continuous information on canopy phenology at finer spatial and temporal scales, regardless of atmospheric conditions. In this study, a tower-based ground remote sensing system, called the "Phenological Eyes Network (PEN)", which was installed at the Gwangneung Deciduous KoFlux (GDK) flux tower site in Korea was introduced, and daily phenological progressions at the canopy level were assessed using ratios of red, green, and blue (RGB) spectral reflectances obtained by the PEN system. The PEN system at the GDK site consists of an automatic-capturing digital fisheye camera and a hemi-spherical spectroradiometer, and monitors stand canopy phenology on an hourly basis. RGB data analyses conducted between late March and early December in 2009 revealed that the 2G_RB (i.e., 2G - R - B) index was lower than the G/R (i.e., G divided by R) index during the off-growing season, owing to the effects of surface reflectance, including soil and snow effects. The results of comparisons between the daily PEN-obtained RGB ratios and daily moderate-resolution imaging spectroradiometer (MODIS)-driven vegetation indices demonstrate that ground remote sensing data, including the PEN data, can help to improve cloud-contaminated satellite remote sensing imagery.

• Journal of Korean Society of Forest Science
• /
• v.79 no.2
• /
• pp.173-186
• /
• 1990

To investigate the structure of the plant community of Soribong area in Kwangnung forest, forty-six plots were set up by the clumped sampling method. The classification by TWINSPAN and four kinds of multivariate ordination(PO, PCA, RA, DCA) were applied to the study area in order to classify them into several groups based on woody plants and environmental variables. The classification had been successfully overlayed on an ordination of the same data using DCA. The plots can be classified into four groups by TWINSPAN and DCA. The successional trends of tree species by both techniques seem to be from Pinus densiflora through Quercus mongolica, Q. serrata, Q. aliena, Carpinus laxiflora, Sorbus alnifolia to C. cordata, Fraxinus rhynchophylla, Cornus controversa in the canopy layer, and from Rhododendron mucronulatum, Rhus triohocarpa, Lespeoleza cyrtobotrya, Weigela subsessilis through Corylus sieboldiana, Lindera obtusiloba to Slaphylea bumalda, Callicarpa japonica, Lonicera maackii in the understory layer. As a result of the analysis for the relationship between the stand scores of DCA and environmental variables, they had a tendancy to increase significantly from the P. densiflora community to C. cordata community that was soil pH and the amount of humus, total nitrogen and exchangeable cations.

• Journal of Korean Society of Forest Science
• /
• v.110 no.4
• /
• pp.678-688
• /
• 2021

This study was conducted to provide growth characteristics and stand information in preparation for natural regeneration method and silvicultural treatment of seed tree method in Korean red pine stands by using the field inventoried data 18 years after the seed tree regeneration method in 2001 and analyzing the stand and sapling characteristics. The study area was located in the Research Forest of Kangwon National University, Chuncheon-si, Gangwon-do. In November 2018, we collected tree measurement factors, such as diameter at breast height (DBH), height, crown class, stem quality, tree age, and annual height increment on the established plots. We calculated the basal area, volume, height-diameter ratio (HD ratio), and additional stand density variables such as the relative density and %stocking to analyze the managed stands. The number of mother trees was 58 trees/ha, with a 17.7% stocking level, whereas the number of saplings was 2,330 trees/ha, with a 79.0% stocking level. In germination, the age distribution of saplings ranged from 2001 to 2007, with most belonging to 15-16 years. The development condition of saplings was 10 cm in DBH and 8 m in height. DBH and height were higher as the crown class is more dominant, and this difference was statistically significant in the analysis of variance and Duncan's multiple comparison test (p<0.0001). HD ratio ranged mostly between 80% and 90%, and more than 95% of sapling stems were of high quality, with a straight, unbroken top, non-sweep, and non-diseased stem. On average, the annual height increment of saplings was 21.9 cm at 1 year, 43.3 cm at 5 years, 54.3 cm at 10 years, and 64.3 cm at 15 years. The overall height growth with age increased smoothly. According to the analysis of covariance, the annual height growth by crown class differed significantly. The regression analysis parameters revealed that annual height growth increased with age and dominant crown class.

• Journal of Korean Society of Forest Science
• /
• v.111 no.1
• /
• pp.150-164
• /
• 2022

This study was conducted to provide basic information for the development of silvicultural guidelines and manuals. This was achieved through analysis of tree and stand characteristics according to the first and second thinning in Korean white pine plantations. Data were collected from permanent plots installed at Korean white pine plantations according to thinning intensity, and residual tree and stand variables, including diameter at breast height (DBH), volume, and mortality at age 19-43, were analyzed using data repeatedly collected in 4-5 measurements by experiments. According to one-way variance of analysis, tree DBH and volume were significantly different according to thinning intensity (p<0.05). DBH distribution was skewed to the left side over time as thinning intensity was heavier. Thus, tree DBH values were larger in heavy thinning plots with increased age. The periodic annual increment (PAI) of DBH was higher with heavier thinning intensity and fewer years after thinning. The PAI range by thinning intensity was 0.48-0.95 cm/year at age 19-24. In addition, the PAI increased in heavy thinning plots after the second thinning; The PAI range by thinning intensity was 0.29-0.67 cm/year after the second thinning at age 37-42. The PAI of tree volume differed according to thinning intensity, and the PAI value did not decrease obviously, in contrast to the pattern of the DBH PAI. Stand volume was generally higher in high-density stands, and the PAI of stand volume was high in unthinned and light thinning plots. Mortality was highest in unthinned plots, and the differences in mortality according to thinning intensity increased over time. Consequently, the growth of DBH and tree volume was lower as stand density increased, but this growth was facilitated with appropriate first and second thinning operations.

• Journal of Korean Society of Forest Science
• /
• v.109 no.3
• /
• pp.259-270
• /
• 2020

Extreme weather events, such as heat and drought, have occurred frequently over the past two decades. This has led to continuous reports of cases of forest damage due to physiological stress, not pest damage. In 2014, pine trees were collectively damaged in the forest genetic resources reserve of Sogwang-ri, Uljin, South Korea. An investigation was launched to determine the causes of the dieback, so that a forest management plan could be prepared to deal with the current dieback, and to prevent future damage. This study aimedto 1) understand the topographic and structural characteristics of the area which experienced pine tree dieback, 2) identify the main causes of the dieback, and 3) predict future risk areas through the use of machine-learning techniques. A model for identifying risk areas was developed using 14 explanatory variables, including location, elevation, slope, and age class. When three machine-learning techniques-Decision Tree, Random Forest (RF), and Support Vector Machine (SVM) were applied to the model, RF and SVM showed higher predictability scores, with accuracies over 93%. Our analysis of the variable set showed that the topographical areas most vulnerable to pine dieback were those with high altitudes, high daily solar radiation, and limited water availability. We also found that, when it came to forest stand characteristics, pine trees with high vertical stand densities (5-15 m high) and higher age classes experienced a higher risk of dieback. The RF and SVM models predicted that 9.5% or 115 ha of the Geumgang Pine Forest are at high risk for pine dieback. Our study suggests the need for further investigation into the vulnerable areas of the Geumgang Pine Forest, and also for climate change adaptive forest management steps to protect those areas which remain undamaged.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.18 no.4
• /
• pp.287-297
• /
• 2016

This study aims to identify the relationship between climatic factors and stand mean Diameter at Breast Height (DBH) for two major tree species; Pinus densiflora and Quercus mongolica in Andong-dam basin. Forest variables such as age, diameter distribution and number of trees per hectare from the $5^{th}$ and $6^{th}$ National Forest Inventory data were used to develop a DBH estimation model. Climate data were collected from six meteorological observatory station and twelve Automatic Weather System provided by Korea Meteorological Administration to produce interpolated daily average temperature map with Inverse Distance Weighting (IDW) method. Andong-dam basin reflects rugged mountainous terrain, so temperature were adjusted by lapse rate based correction. As a result, predictions of model were consistent with the previous studies; that the rising temperature is negatively related to the growth of Pinus densiflora whereas opposing trend is observed for Quercus mongolica.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.17 no.1
• /
• pp.80-90
• /
• 2014

The objective of this research is to estimate the stand volume of Pinus koraiensis, by using the investigated volume and the information of remote sensing(RS), in the research forest of Kangwon National University. The average volume of the research forest per hectare was $307.7m^3/ha$ and standard deviation was $168.4m^3/ha$. Before and after carrying out 3 by 3 majority filtering on TM image, eleven indices were extracted each time. Independent variables needed for linear regression equation were selected using mean pixel values by indices. The number of indices were eleven: six Bands(except for thermal Band), NDVI, Band Ratio(BR1:Band4/Band3, BR2:Band5/Band4, BR3:Band7/Band4), Tasseled Cap-Greeness. As a result, NDVI and TC G were chosen as the most suitable indices for regression before and after filtering, and R-squared was high: 0.736 before filtering, 0.753 after filtering. As a result of error verification for an exact comparison, RMSE before and after filtering was about $69.1m^3/ha$, $67.5m^3/ha$, respectively, and bias was $-12.8m^3/ha$, $9.7m^3/ha$, respectively. Therefore, the regression conducted with filtering was selected as an appropriate model because of low RMSE and bias. The estimated stand volume applying the regression was $160,758m^3$, and the average volume was $314m^3/ha$. This estimation was 1.2 times higher than the actual stand volume of Pinus koraiensis.