• Journal of Bio-Environment Control
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• v.29 no.1
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• pp.43-51
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• 2020

For developing a canopy photosynthesis model, an efficient method to measure the photosynthetic rate in a growth chamber is required. The objective of this study was to develop a method for establishing canopy photosynthetic rate curves of romaine lettuce (Lactuca sativa L.) with light intensity and CO₂ concentration variables using controlled growth chamber. The plants were grown in plant factory modules, and the canopy photosynthesis rates were measured in sealed growth chambers made of acrylic (1.0 × 0.8 × 0.5 m). First, the canopy photosynthetic rates of the plants were measured, and then the time constants were compared between two application methods: 1) changing light intensity (340, 270, 200, and 130 μmol·m^-2·s^-1) at a fixed CO₂ concentration (1,000 μmol·mol^-1) and 2) changing CO₂ concentration (600, 1,000, 1,400, and 1,800 μmol·mol^-1) at a fixed light intensity (200 μmol·m^-2·s^-1). Second, the canopy photosynthetic rates were measured by changing the light intensity at a CO₂ concentration of 1,000 μmol·mol^-1 and compared with those measured by changing the CO₂ concentration at a light intensity of 200 μmol·m^-2·s^-1. The time constant when changing the CO₂ concentration at the fixed light intensity was 3.2 times longer, and the deviation in photosynthetic rate was larger than when changing the light intensity. The canopy photosynthetic rate was obtained stably with a time lag of one min when changing the light intensity, while a time lag of six min or longer was required when changing the CO₂ concentration. Therefore, changing the light intensity at a fixed CO₂ concentration is more appropriate for short-term measurement of canopy photosynthesis using a growth chamber.

• Journal of electromagnetic engineering and science
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• v.5 no.4
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• pp.183-188
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• 2005

A simple microwave backscattering model for vegetation canopies on earth surfaces is developed in this study. A natural earth surface is modeled as a two-layer structure comprising a vegetation layer and a ground layer. This scattering model includes various scattering mechanisms up to the first-order multiple scattering( double-bounce scattering). Radar backscatter from ground surface has been modeled by the polarimetric semi-empirical model (PSEM), while the backscatter from the vegetation layer modeled by the vector radiative transfer model. The vegetation layer is modeled by random distribution of mixed scattering particles, such as leaves, branches and trunks. The number of input parameters has been minimized to simplify the scattering model. The computation results are compared with the experimental measurements, which were obtained by ground-based scatterometers and NASA/JPL air-borne synthetic aperture radar(SAR) system. It was found that the scattering model agrees well with the experimental data, even though the model used only ten input parameters.

• Journal of Bio-Environment Control
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• v.17 no.2
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• pp.83-89
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• 2008

A wind tunnel test was conducted at Protected Horticulture Experiment Station of National Horticultural Research Institute in Busan to find the aerodynamic resistance and quadratic resistance coefficient of chrysanthemum in greenhouse. The internal plants of the CFD model has been designed as a porous media because of the complexity of its physical shapes. Then the aerodynamic resistance value should be input for analyzing CFD model that crop is considered while the value varies by crops. In this study, the aerodynamic resistance value of chrysanthemum canopy was preliminarily found through wind tunnel test. The static pressure at windward increased as wind velocity and planting density increased. The static pressure at leeward decreased as wind velocity increased but was not significantly affected by planting density. The difference of static pressure between windward and leeward increased as wind velocity and planting density increased. The aerodynamic resistance value of chrysanthemum canopy was found to be 0.22 which will be used later as the input data of Fluent CFD model. When the planting distances were $9{\times}9\;cm$, $11{\times}11\;cm$, and $13{\times}13\;cm$, the quadratic resistance coefficients of porous media were found to be 2.22, 1.81, and 1.07, respectively. These values will be used later as the input data of CFX CFD model.

• Journal of the Korean earth science society
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• v.42 no.2
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• pp.135-148
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• 2021

The purpose of this study was to evaluate the urban heat island (UHI) intensity and the corresponding surface temperature forecast obtained using the local data assimilation and prediction system (LDAPS) of the Korea Meteorological Administration (KMA) against the AWS observation. The observed UHI intensity in Seoul increases during spring and winter, while it decreases during summer. It is found that the diurnal variability of the UHI intensity peaks at dawn but reaches a minimum in the afternoon. The LDAPS overestimates the UHI intensity in summer but underestimates it in winter. In particular, the model tends to overestimate the UHI intensity during the daytime in summer but underestimate it during the nighttime in winter. Moreover, surface temperature errors decrease in summer but increase in winter. The underestimation of the winter UHI intensity appears to be associated with weak forecasting of urban temperature in winter. However, the overestimated summer UHI intensity results from the underestimation of the suburban temperature forecast in summer. In order to improve the predictability of the UHI intensity, an urban canopy model (MORUSES) that considers urban effects was combined with LDAPS and used for simulation for the summer of 2017. The surface temperature forecast for the city was improved significantly by adopting MORUSES, and there were remarkable improvements in urban surface temperature morning forecasts. The urban canopy model produced an improvement effect that weakened the intensity of the UHI, which showed an overestimation during summer.

• Korean Journal of Remote Sensing
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• v.35 no.3
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• pp.447-455
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• 2019

Since the forest type map in Korea has been mostly constructed every five years, the forest information from the map lacks up-to-date information. Forest research has been carried out by aerial photogrammetry and field surveys, and hence it took a lot of times and money. The vertical structure of forests is an important factor in evaluating forest diversity and environment. The vertical structure is essential information, but the observation of the vertical structure is not easy because the vertical structure indicates the internal structure of forests. In this study, the index map and texture map produced from KOMPSAT-3/3A/5 satellite images and the canopy information generated by the difference between DSM (Digital Surface Model) and DTM (Digital Terrain Model) were classified using the artificial neural network. The vertical structure of forests of single and multi-layer forests was classified to identify 81.59% of the final classification result.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.33-36
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• 2008

This paper presents soil moisture retrieval from measured polarimetric backscattering coefficients of a vegetated surface. Based on the analysis of the quite complicate first-order radiative transfer scattering model for vegetated surfaces, a simplified scattering model is proposed for an inversion algorithm. Extraction of the surface-scatter component from the total scattering of a vegetation canopy is addressed using the simplified model, and also using the three-component decomposition technique. The backscattering coefficients are measured with a polarimetric L-band scatterometer during two months. At the same time, the biomasses, leaf moisture contents, and soil moisture contents are also measured. Then the measurement data are used to estimate the model parameters for vv-, hh-, and vh-polarizations. The scattering model for tall-grass-covered surfaces is inverted to retrieve the soil moisture content from the measurements using a genetic algorithm. The retrieved soil moisture contents agree quite well with the in-situ measured soil moisture data.

• Wind and Structures
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• v.9 no.1
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• pp.23-35
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• 2006

The effect of buildings on flow in urban canopy is one of the most important problems in local/micro-scale meteorology. A large eddy simulation model is used to simulate the flow structure in an urban neighborhood and the bulk effect of the buildings on surrounding flows is analyzed. The results demonstrate that: (a) The inflow conditions affect the detailed flow characteristics much in the building group, including: the distortion or disappearance of the wake vortexes, the change of funneling effect area and the change of location, size of the static-wind area. (b) The bulk effect of the buildings leads to a loss of wind speed in the low layer where height is less than four times of the average building height, and this loss effect changes little when the inflow direction changes. (c) In the bulk effect to environmental fields, the change of inflow direction affects the vertical distribution of turbulence greatly. The peak value of the turbulence energy appears at the height of the average building height. The attribution of fluctuations of different components to turbulence changes greatly at different height levels, in the low levels the horizontal speed fluctuation attribute mostly, while the vertical speed fluctuation does in high levels.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2018.06a
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• pp.87-87
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• 2018

• Journal of Crop Science and Biotechnology
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• v.11 no.2
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• pp.141-150
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• 2008

The response of grain yield(GY) and milled-rice protein content(PC) to crop growth status and nitrogen(N) rates at panicle initiation stage(PIS) is critical information for prescribing topdress N rate at PIS(Npi) for target GY and PC. Three split-split-plot experiments including various N treatments and rice cultivars were conducted in Experimental Farm, Seoul National University, Korea in 2003-2005. Shoot N density(SND, g N in shoot $m^{-2}$) and canopy reflectance were measured before N application at PIS, and GY, PC, and SND were measured at harvest. Data from the first two years(2003-2004) were used for calibrating the predictive models for GY, PC, and SND accumulated from PIS to harvest using SND at PIS and Npi by multiple stepwise regression. After that the calibrated models were used for calculating N requirement at PIS for each of nine plots based on the target PC of 6.8% and the values of SND at PIS that was estimated by canopy reflectance method in the 2005 experiment. The result showed that SND at PIS in combination with Npi were successful to predict GY, PC, and SND from PIS to harvest in the calibration dataset with the coefficients of determination ($R^2$) of 0.87, 0.73, and 0.82 and the relative errors in prediction(REP, %) of 5.5, 4.3, and 21.1%, respectively. In general, the calibrated model equations showed a little lower performance in calculating GY, PC, and SND in the validation dataset(data from 2005) but REP ranging from 3.3% for PC and 13.9% for SND accumulated from PIS to harvest was acceptable. Nitrogen rate prescription treatment(PRT) for the target PC of 6.8% reduced the coefficient of variation in PC from 4.6% in the fixed rate treatment(FRT, 3.6g N $m^{-2}$) to 2.4% in PRT and the average PC of PRT was 6.78%, being very close to the target PC of 6.8%. In addition, PRT increased GY by 42.1 $gm^{-2}$ while Npi increased by 0.63 $gm^{-2}$ compared to the FRT, resulting in high agronomic N-use efficiency of 68.8 kg grain from additional kg N. The high agronomic N-use efficiency might have resulted from the higher response of grain yield to the applied N in the prescribed N rate treatment because N rate was prescribed based on the crop growth and N status of each plot.

• Water Engineering Research
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• v.1 no.1
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• pp.25-37
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• 2000

This study presents some results of a preliminary study for the coupled precipitation and river flow prediction system. The model system in based on three numerical models, Mesoscale Atmospheric Simulation model for generating atmospheric variables. Soil-Plant-Snow model for computing interactions within soil-canopy-snow system as well as the energy and water exchange between the atmosphere and underlying surfaces, and TOPMODEL for simulating stream flow, subsurface flow, and water tabled depth in an watershed. The selected study area is the 2,703 $\alpha_4$ $\km_2$ Soyang River basin with outlet at Soyang dam site. In addition to providing the results of rainfall and stream flow predictions, some results of DEM and GIS application are presented. It is obvious that the accurate river flow predictions are highly dependant on the accurate predictation predictions.