• Journal of Environmental Science International
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• v.5 no.6
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• pp.727-738
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• 1996

An one dimensional atmosphere-canopy-soil interaction model is developed to estimate of the heat budget parameter in the atmospheric boundary layer. The canopy model is composed of the three balance equations of energy, temperature, moisture at ground surface and canopy layer with three independent variables of Tf(foliage temperature), Tg(ground temperature), and qg(ground specific humidity). The model was verilied by comparative study with OSUID(Oregon State University One Dimensional Model) proved in HAPEX-MOBILHY experiment. Also we applied this model in two dimensional land-sea breeze circulation. According to the results of this study, surface characteristics considering canopy acted importantly upon the simulation of meso-scale circulation. The factors which used in the numerical experiment are as follows ; the change for a sort of soil(sand and peat), the change for shielding factor, and the change for a kind of vegetation.

• Korean Journal of Soil Science and Fertilizer
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• v.36 no.2
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• pp.92-103
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• 2003

Research and technological advances in the field of remote sensing have greatly enhanced the ability to detect and quantify physical and biological stresses that affect the productivity of agricultural crops. Reflectance in specific visible and near-infrared regions of the electromagnetic spectrum have proved useful in detection of nutrient deficiencies. Especially crop canopy sensors as a ground remote sensing measure the amount of light reflected from nearby surfaces such as leaf tissue or soil and is in contrast to aircraft or satellite platforms that generate photographs or various types of digital images. Multi-spectral vegetation indices derived from crop canopy reflectance in relatively wide wave band can be used to monitor the growth response of plants in relation to environmental factors. The normalized difference vegetation index (NDVI), where NDVI = (NIR-Red)/(NIR+Red), was originally proposed as a means of estimating green biomass. The basis of this relationship is the strong absorption (low reflectance) of red light by chlorophyll and low absorption (high reflectance and transmittance) in the near infrared (NIR) by green leaves. Thereafter many researchers have proposed the other indices for assessing crop vegetation due to confounding soil background effects in the measurement. The green normalized difference vegetation index (GNDVI), where the green band is substituted for the red band in the NDVI equation, was proved to be more useful for assessing canopy variation in green crop biomass related to nitrogen fertility in soils. Consequently ground remote sensing as a non destructive real-time assessment of nitrogen status in plant was thought to be useful tool for site specific crop nitrogen management providing both spatial and temporal information.

• Journal of Wetlands Research
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• v.11 no.1
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• pp.105-113
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• 2009

Heat energy exchange is very important processes in the coastal wetland ecosystems. We observed and analyzed the net radiation flux, the sensible heat flux, the latent heat flux and the soil heat flux, which are balanced in the heat energy balance, over a reclaimed land covered with reeds at Goheung, Jeonllanamdo where is horizontally plane. The atmospheric turbulence had been measured in order to estimate the heat transfer during 5 intensive observation periods (IOPs). It was considered that the soil consists of water, fine particles, and vegetation canopy that changes color and density according to the season. We examined the characteristics of the heat flux and the vegetation effect on the air temperature control. It was noted that the heat was transported mainly by latent heat flux in the summer season and the vegetation canopy decreased the daily temperature range due to the heat storage. The air temperature was lower at the IOPs site than near urban area. This showed that the coastal wetland covered with the vegetation control the thermal environment.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.325-328
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• 2007

We discuss the Normalized Difference Vegetation Index (NDVI) of the forest canopy and floor separately based on airborne spectral reflectance measurements and simultaneous airborne land surface images acquired around Yakutsk, Siberia in 2000. The aerial land surface images were visually classified into four forest types: no-green canopy and snow floor (Type-1), green canopy and snow floor (Type-2), no-green canopy and no-snow floor (Type-3), and green canopy and no-snow floor (Type-4). The mean NDVI was calculated for these four types. Although Type-2 had green canopy, the NDVI was rather small (0.17) because of high reflection from the snow cover on the floor. Type-3, which had no green canopy, indicated considerably large NDVI (0.45) due to the greenness of the floor. Type-4 had the largest NDVI (0.75) because of the greenness of both the canopy and floor. These results reveal that the NDVI depends considerably on forest floor greenness and snow cover in addition to canopy greenness.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.3
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• pp.260-267
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• 2010

As sloped farmland is subject to runoff and soil erosion and consequently require appropriate vegetative coverage to conserve soil and water, a field study was carried out to evaluate the impact of crop canopy coverage on soil loss and runoff from the experimental plot with three different textural types (clay loam, loam, and sandy loam). The runoff and soil loss were examined at lysimeters with 15% slope, 5 m in length, and 2 m in width for five months from May to September 2009 in Suwon ($37^{\circ}$ 16' 42.67" N, $126^{\circ}$ 59' 0.11" E). Red pepper (Capsicum annum L. cv. Daechon) seedlings were transplanted on three different dates, May 4 (RP1), 15 (RP2), and 25 (RP3) to check vegetation coverage. During the experimental period, the vegetation coverage and plant height were measured at 7 day-intervals and then the 'canopy cover subfactor' (an inverse of vegetation cover) was subsequently calculated. After each rainfall ceased, the amounts of soil loss and runoff were measured from each plot. Under rainfall events >100 mm, both soil loss and runoff ratio increased with increasing canopy cover subfactor ($R^2$=0.35, p<0.01, $R^2$=0.09, p<0.1), indicating that as vegetation cover increases, the amount of soil loss and runoff reduces. However, the soil loss and runoff were depending on the soil texture and rainfall intensity (i. e., $EI_{30}$). The red pepper canopy cover subfactor was more highly correlated with soil loss in clay loam ($R^2$=0.83, p<0.001) than in sandy loam ($R^2$=0.48, p<0.05) and loam ($R^2$=0.43, p<0.1) plots. However, the runoff ratio was effectively mitigated by the canopy coverage under the rainfall only with $EI_{30}$<1000 MJ mm $ha^{-1}hr^{-1}$ ($R^2$=0.34, p<0.05). Therefore, this result suggested that soil loss from the red pepper field could be reduced by adjusting seedling transplanting dates, but it was also affected by the various soil textures and $EI_{30}$.

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

• Korean Journal of Remote Sensing
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• v.28 no.3
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• pp.297-305
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• 2012

This study was performed to estimate forest canopy density (FCD) using airborne hyperspectral data acquired in the Independence Hall of Korea in central Korea. The airborne hyperspectral data were obtained with 36 narrow spectrum ranges of visible (Red, Green, and Blue) and near infrared spectrum (NIR) scope. The FCD mapping model developed by the International Tropical Timber Organization (ITTO) uses vegetation index (VI), bare soil index (BI), shadow index (SI), and temperature index (TI) for estimating FCD. Vegetation density (VD) was calculated through the integration of VI and BI, and scaled shadow index (SSI) was extracted from SI after the detection of black soil by TI. Finally, the FCD was estimated with VD and SSI. For the estimation of FCD in this study, VI and SI were extracted from hyperspectral data. But BI and TI were not available from hyperspectral data. Hyperspectral data makes the numerous combination of each band for calculating VI and SI. Therefore, the principal component analysis (PCA) was performed to find which band combinations are explanatory. This study showed that forest canopy density can be efficiently estimated with the help of airborne hyperspectral data. Our result showed that most forest area had 60 ~ 80% canopy density. On the other hand, there was little area of 10 ~ 20% canopy density forest.

• Korean Journal of Environment and Ecology
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• v.28 no.2
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• pp.205-214
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• 2014

The purpose of this study is to suggest vegetation management method as the cultural landscape forest of Dongbaek Island which is the district monument. The study area was $20,000m^2$ around the peak area in management as the nature sabbatical area. Vegetation structure type was classified with the criteria of topography, vegetation, management and the management plan was derived from the vegetation structure analysis according to the types. Vegetation structure types were Management-Camellia japonica, Non-management-Eurya japonica, Non-management-Rugged area-Eurya japonica. As the result of vegetation structure, Pinus thunbergii dominated in canopy layer and Camellia japonica and Eurya japonica dominated in Type I and in Type II and III, respectively. Especially, Machilus thunbergii as the climax species in the warm temperate forest were distributed centering shrubs, and as the result of distribution of diameter of breast height, middle size of Celtis sinensis and Machilus thunbergii were distributed in type I, II. Machilus thunbergii were distributed in range of 4 to 44 individuals through the all types. Mean age of canopy layer was 66 year-old and sub-canopy layer was 22.9 year-old. Shanon's species diversity was analysed from 0.5472 to 0.8646. As the vegetation management direction of Dongbaek island, managed Camellia japonica forest was suggested to maintain the regular management and non-managed Eurya japonica forest was required to remove the Eurya japonica and plant the Camellia japonica. In case of non managed Eurya japonica forest in rugged area, vegetation succession was required to laurel forest.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.340-348
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• 2021

Continuous monitoring of RGB (Red, Green, Blue) vegetation indices is important to apply remote sensing technology for the estimation of crop growth. In this study, we evaluated the performance of eight vegetation indices derived from soybean RGB images with various agronomic parameters under drought stress condition. Drought stress influenced the behavior of various RGB vegetation indices related soybean canopy architecture and leaf color. In particular, reported vegetation indices such as ExGR (Excessive green index minus excess red index), Ipca (Principal Component Analysis Index), NGRDI (Normalized Green Red Difference Index), VARI (Visible Atmospherically Resistance Index), SAVI (Soil Adjusted Vegetation Index) were effective tools in obtaining canopy coverage and leaf chlorophyll content in soybean field. In addition, the RGB vegetation indices related to leaf color responded more sensitively to drought stress than those related to canopy coverage. The PLS-DA (Partial Squares-Discriminant Analysis) results showed that the separation of RGB vegetation indices was distinct by drought stress. The results, yet preliminary, display the potential of applying vegetation indices based on RGB images as a tool for monitoring crop environmental stress.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.250-255
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• 2002

This paper describes the study methods of identifying forest vegetation types, based on this study, forest vegetation classification method based on vegetation index is proposed. According to reflectance data of vegetation canopy and soil line equation NIR=1.506R+0.0076 in Jingyuetan, Changchun, China, many vegetation index are calculated and analyzed. The relationships between vegetation index and vegetation types are that PVI identifies broadleaf forest and conifer forest the most easily, the next is TSAVI and MSAVI, but their calculation is complex. RVI values of different conifer trees vary obviously, so RVI can classify conifer trees. In a word, combination of PVI and RVI is evaluated to classify different vegetation types.