• Journal of the Korean Society for Advanced Composite Structures
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• v.6 no.3
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• pp.8-13
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• 2015

This study investigates the application of a synthetic resine based net-hose system to sustain vegetated embankment slope reinforcement. The net-hose system is designated to improve water supply to the vegetation that can suffer the lack of water in case of extreme drying condition or rock slope where water supply is relatively insufficient to ensure the growth of vegetation. A series of laboratory tests were conducted to check the structural adequacy and effectiveness of net-hose system. The results indicated that the model slope equipped with net-hose system seemed to provide better water supply resulting in more vegetated areas and higher matric suction due to active water uptake capacity, which might be contributed to greater shear strength of slope surface. A limited numerical analysis was conducted to verify the effect of water uptake on vegetated root system that generally yields better slope stability.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.34-36
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• 2003

In boreal conifers in China's Northeast area, maximum latewood density (MXD) of tree-ring varies in response to growing season temperature. Forest net productivity can be estimated using the Normalized-difference Vegetation Index (NDVI) calculated from satellite sensor data. MXD from the Mohe site in this area was compared with estimates of NPP for 1982-1999 produced by the NDVI model, which was established based on the relationship of leaf area index (LAI) and NDVI. The result shows that the MXD series correlated significantly with the NDVI model estimates series, suggesting that MXD appeared to be an appropriate index for productivity or canopy growth in region where forest productivity is strongly temperature-related.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.4
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• pp.75-86
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• 2020

The purpose of this study is to develop a technology for estimating rice growth and damage effect according to bacterial leaf blight using UAV multi-spectral imagery. For this purpose, we analyzed the change of aerial images, rice growth factors (plant height, dry weight, LAI) and disease effects according to disease occurrence by using UAV images for 3 rice varieties (Milyang23, Sindongjin-byeo, Saenuri-byeo) from 2017 to 2018. The correlation between vegetation index and rice growth factor during vegetative growth period showed a high value of 0.9 or higher each year. As a result of applying the growth estimation model built in 2017 to 2018, the plant height of Milyang23 showed good error withing 10%. However, it is considered that studies to improve the accuracy of other items are needed. Fixed wing unmanned aerial photographs were also possible to estimate the damage area after 2 to 4 weeks from inoculation. Although sensing data in the multi-spectral (Blue, Green, Red, NIR) band have limitations in early diagnosis of rice disease, for rice varieties such as Milyang23 and Sindongjin-byeo, it was possible to construct the equation of infected leaf area ratio and rice yield estimation using UAV imagery in early and mid-September with high correlation coefficient of 0.8 to 0.9. The results of this study are expected to be useful for farming and policy support related to estimating rice growth, rice plant disease and yield change based on UAV images.

• Korean Journal of Environment and Ecology
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• v.21 no.5
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• pp.400-414
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• 2007

This study has analyzed the vegetation structure to suggest a vegetation ecological restoration model by using the case of the afforestation for erosion control area with Pinus koreaiensis and Betula platyphylla, etc., on the hills of the Young-in mountains after its great fire in 2000. Of the area having a dimension of $1,152,404.3m^2$ selected as a survey site for the existing vegetation, the forest fire area accounted for 69.2% among which, brushwoods accounted the most for 24.67%. As a result of analysis of the 27 surveyed unit plots[unit dimension: $100m^2$] set up in consideration of the existing vegetation pattern and damaged state from the forest fire, the surveyed area was classified into 10 communities. Shrub layer's vegetation was found to be dominant in forest fire areas and the surveyed sites were classified into 5 plant communities, i.e. P. koraiensis community, Quercus variabilis community, P. thunbergii community, Q. serrata community, B. platyphylla community in forest fire areas, while non-forest fire areas were classified into 5 plant communities, such as P. densiflora community, Q. acutissima community, Q. serrata community, Q. mongolica-Q. serrata community, B. platyphylla community. Species diversity of forest fire areas was $0.3679{\sim}0.5907$ and that of non-forest fire areas was $0.5728{\sim}0.8865$. In addition, the number of the species in the forest fire areas was $5{\sim}8$ and that of non-forest areas was $8{\sim}12$; however, the population of forest fire areas$(156{\sim}456)$ was higher than that of non-forest fire areas$(61{\sim}227)$. In the analysis of growth density per layer$[of\;100m^2]$, there appeared $1{\sim}8$ trees of Q. mongolica and $3{\sim}5$ trees of Q. serrata in the upper layer species; $2{\sim}4$ trees of Q. serrata and one tree of Q. mongolica in the canopy layer. As for the characteristics of soil, acidity of forest fire areas was pH 5.45 and that of non-forest fire was pH 5.25. By setting up the middle D.B.H range of Q. mongolica-Q. serrata community as the vegetation restoration model, planting species, planting density and planting models are suggested.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.2
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• pp.95-106
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• 2010

The performance of Community Land Model version 3.5 - Dynamic Global Vegetation Model (CLM-DGVM) was evaluated through a comparison with the observation over temperate deciduous forest in Gwangneung, Korea. Influence of plant phenology, composition of plant functional type, and climate variability on carbon exchanges was also examined through sensitivity test. To get equilibrium carbon storage, the model was run for 400 years driven by the observed atmospheric data at the deciduous forest of the year 2006. We run the model for 2006 with the equilibrium carbon storage at Gwangneung forest and compared the model output with the observation. A comparison of leaf area index (LAI) between the model and observation indicated that the simulated phenology poorly represented the timing of budburst, leaf-fall, and evolution of LAI. Senescence of the phenology was delayed about four weeks and the simulated maximum LAI (of 5.8 $m^2$ $m^{-2}$) was greater than the observed value (of 4.5 $m^2$ $m^{-2}$). The overestimated LAI contributed to overestimation of both gross primary productivity (GPP) and ecosystem respiration $(R_e)$ through increased photosynthesis and foliar autotropic respiration $(R_a)$, respectively. Despite the discrepancy between the simulated and observed LAI, the simulated tree carbon storage amounts were comparable with the reported values at the site. Change in plant phenology from the simulated to the observed reduced more than six weeks of the plant growth period, resulting in the decreased amount of GPP and $R_e$. These values, however, were still higher (~10% of GPP and 40% of $R_e$) than the observed values. The effect of change in plant functional type composition (from dominant temperate deciduous forest to the coexistence of temperate deciduous and needle leaf forests) on the estimated amount of GPP and $R_e$ was marginal. The influence of climate variability on carbon storage amounts was not significant. The simulated inter-annual variation of GPP and $R_e$ from 1994 to 2003 depended on annual mean air temperature and total radiation but not on precipitation. Other deficiencies of CLM3.5-DGVM have been discussed.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.14 no.1
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• pp.57-65
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• 2011

The composition of species for each community of Quercus by vegetation and soil survey, the community classification by TWINSPAN, the structural characteristics of communities were used and analyzed during the period of 2000~2004 for Quercus mongolica forest. And the resulting suggestions for a subsequent planting model for forest are as follows. The Quercus mongolica community had the highest importance value for Quercus mongolica followed sequentially by Acer pseudosieboldianum, Acer mono, Rhododendron schlippenbachii, Tilia amurensis, Fraxinus rhynchophylla, and Fraxinus sieboldiana. As a result of suggesting a planting modeling for the Quercus mongolica communities in the areas with the warmth index of both $60.90{\sim}79.79^{\circ}C$ and $53.96{\sim}64.82^{\circ}C$, Quercus mongolica was absolutely dominant in case of the subtree layer for the accompaniment species of distribution in the planting modeling by tree layer in the two areas depending on the warmth index, while there were distinct differences shown in case of the lower tree layer. While Acer pseudosieboldianum, Tilia amurensis, Fraxinus rhynchophylla, Sorbus alnifolia, Acer mono, etc. were appeared in the subtree layer for the areas with the warmth index of $60.90{\sim}79.79^{\circ}C$. Cornus controversa, Quercus mongolica, Fraxinus sieboldiana, etc. were many appeared in the subtree layer for the areas with the warmth index of $53.96{\sim}64.82^{\circ}C$. And, when we made ecological Quercus mongolica community, subtree layer planting is different by warmth index.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.327-336
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• 2019

Soybean is one of the most important crops of which the grains contain high protein content and has been consumed in various forms of food. Soybean plants are generally cultivated on the field and their yield and quality are strongly affected by climate change. Recently, the abnormal climate conditions, including heat wave and heavy rainfall, frequently occurs which would increase the risk of the farm management. The real-time assessment techniques for quality and growth of soybean would reduce the losses of the crop in terms of quantity and quality. The objective of this work was to develop a simple model to estimate the growth of soybean plant using a multispectral sensor mounted on a rotor-wing unmanned aerial vehicle(UAV). The soybean growth model was developed by using simple linear regression analysis with three phenotypic data (fresh weight, dry weight, leaf area index) and two types of vegetation indices (VIs). It was found that the accuracy and precision of LAI model using GNDVI (R²= 0.789, RMSE=0.73 ㎡/㎡, RE=34.91%) was greater than those of the model using NDVI (R²= 0.587, RMSE=1.01 ㎡/㎡, RE=48.98%). The accuracy and precision based on the simple ratio indices were better than those based on the normalized vegetation indices, such as RRVI (R²= 0.760, RMSE=0.78 ㎡/㎡, RE=37.26%) and GRVI (R²= 0.828, RMSE=0.66 ㎡/㎡, RE=31.59%). The outcome of this study could aid the production of soybeans with high and uniform quality when a variable rate fertilization system is introduced to cope with the adverse climate conditions.

• Korean Journal of Remote Sensing
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• v.20 no.3
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• pp.175-188
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• 2004

The objectives of this study were to estimate leaf area index (LAI) as a function of image-derived vegetation indices, and to compare measured and estimated LAI to the results of crop model simulation. Soil moisture, crop phenology, and LAI data were obtained several times during the 2001 growing season at monitoring sites established in two central Missouri experimental fields, one planted to com (Zea mays L.) and the other planted to soybean (Glycine max L.). Hyper- and multi-spectral images at varying spatial. and spectral resolutions were acquired from both airborne and satellite platforms, and data were extracted to calculate standard vegetative indices (normalized difference vegetative index, NDVI; ratio vegetative index, RVI; and soil-adjusted vegetative index, SAVI). When comparing these three indices, regressions for measured LAI were of similar quality $(r^2$ =0.59 to 0.61 for com; $r^2$ =0.66 to 0.68 for soybean) in this single-year dataset. CERES(Crop Environment Resource Synthesis)-Maize and CROPGRO-Soybean models were calibrated to measured soil moisture and yield data and used to simulate LAI over the growing season. The CERES-Maize model over-predicted LAI at all corn monitoring sites. Simulated LAI from CROPGRO-Soybean was similar to observed and image-estimated LA! for most soybean monitoring sites. These results suggest crop growth model predictions might be improved by incorporating image-estimated LAI. Greater improvements might be expected with com than with soybean.

• Journal of Ecology and Environment
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• v.40 no.1
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• pp.55-65
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• 2016

Background: In this article, it was analyzed how snow melting affects the assembly of lichen and moss communities in a small area of the coastal region of Barton Peninsula, which is in maritime Antarctic. In the small area, even though there is a huge gap of difference of the environment between the snow-filled area and snow-melt one, the latter did not have distinctive environmental gradients. Results: Depending on the snow melting time, coverage and species diversity of lichens and mosses tend to increase remarkably. For species with significant changes depending on the snow-covered period, there are Andreaea regularis, crustose lichens, Placopsis contortuplicata, Usnea aurantiaco-atra, and snow algae. In this area, the process of vegetation assembly process has shown the directional development in the order of snow algae${\rightarrow}$crustose, lichen sub-formation${\rightarrow}$fruticose lichen, moss cushion sub-formation (Andreaea sociation)${\rightarrow}$fruticose lichen, and moss cushion sub-formation (Usnea sociation), according to the order of snow melting. These directional development stages are shown in gradual change in small area with the snow melting phenomena. However, in the snow-free area, where water is sufficiently supplied, it is expected that moss carpet sub-formation (Sanionia sociation) will be developed. Vegetation development in the small area with the snow melting phenomena, depending on differences of resistance on snow kill and moisture settled by species in according to the time of snow melting, tolerance model to form community is followed. Conclusions: The research results explain the development of vegetation in the Antarctic tundra and its spatial distribution according to the period for growth of lichens and mosses in the summer time by differences of snow melting in the small area. In the future, if research for the community development process in a large scale will be done, it will be helpful to figure out temporal and spatial dynamic of vegetation in the Antarctic tundra where snow and glaciers melt rapidly due to climatic warming.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.4
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• pp.476-482
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• 2014

In this study, we analyzed the effect of corn growth on the radar backscattering coefficient. At first, we measured the backscattering coefficients of various corn fields using a polarimetric scatterometer system. The backscattering coefficients of the corn fields were also computed using the 1st-order VRT(Vector Radiative Transfer) model with field-measured input parameters. Then, we analyzed the experimental and numerical backscattering coefficients of corn fields. As a result, we found that the backscatter from an underlying soil layer is dominant for early growing stage. On the other hand, for vegetative stage with a higher LAI(Leaf-Area-Index), the backscatter from vegetation canopy becomes dominant, and its backscattering coefficients increase as incidence angle increases because of the effect of leaf angle distribution. It was also found that the estimated backscattering coefficients agree quite well with the field-measured radar backscattering coefficients with an RMSE(Root Mean Square Error) of 1.32 dB for VV-polarization and 0.99 dB for HH-polarization. Finally, we compared the backscattering characteristics of vegetation and soil layers with various LAI values.