• Journal of Korean Society for Atmospheric Environment
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• v.14 no.5
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• pp.465-478
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• 1998

In this study, seasonal variations of the dry deposition velocity and deposition flux for the sulfur dioxide were analysed. The field observation was performed during one year (from November 1, 1995 to October 31, 1996) in Chunchon basin. The turbulence data were measured by 3-dimensional sonic anemometer/thermometer, and were estimated by mean meteorological data obtained at two heights (2.5 m and 10 m) of meteorological tower. Also, the estimation methods were evaluated by comparing the turbulence data. The results showed that the estimated dry deposition velocity and turbulence parameter such as uc and sensible heat flux using mean meteorological data were relatively similar to the sonic measurements, but all showed somewhat large differences. The dry deposition velocity was large in summer and small in winter mainly due to canopy resistance (rc). The major factor which affects diurnal variation of the velocity was aerodynamic resistance (rw). The SO2 dry deposition flux was large in winter and small in summer in Chunchon.

• Korean Journal of Environmental Agriculture
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• v.14 no.1
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• pp.1-6
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• 1995

This experiment was carried out to clarify the evapotranspiration and water use efficiency in rice plant canopy. Two rice cultivars, Daechungbyo(japonica type) and Samgangbyo(Tongil) were planted on the field of Suwon Weather Forecast Station in 1989. Evapotranspiration, dry matter production and leaf area of rice plant were measured to investigate the water use efficiency. There was significant correlation between cumulative evapotranspiration and dry matter production of aboveground. The parameter of linear regression was 4.13. The ratio of cumulative top dry matter production per cumulative evapotranspiration was increased until $5.5{\sim}5.9$ leaf area index. The de Wit's "m" value revealed maximum record at heading-flowering stage. At the harvest, the values were ranged from 175.5 to 191.7. The parameter of cumulative solar radiation to dry matter production was $1.011{\sim}1.248$. The evapotranspiration ratio(g.water/g.DW) of Samgangbyo(278) was higher than that of Daechungbyo (299.9). The efficiency of evapotranspiration(g.DW/g. water) was 1.58 in Daechungbyo and 1.98 in Samgangbyo.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.387-397
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• 2023

Plant height is a growth parameter that provides visible insights into the plant's growth status and has a high correlation with yield, so it is widely used in crop breeding and cultivation research. Investigation of the growth characteristics of crops such as plant height has generally been conducted directly by humans using a ruler, but with the recent development of sensing and image analysis technology, research is being attempted to digitally convert growth measurement technology to efficiently investigate crop growth. In this study, the canopy height of rice grown at various nitrogen fertilization levels was measured using a laser scanner capable of precise measurement over a wide range, and a comparative analysis was performed with the actual plant height. As a result of comparing the point cloud data collected with a laser scanner and the actual plant height, it was confirmed that the estimated plant height measured based on the average height of the top 1% points showed the highest correlation with the actual plant height (R² = 0.93, RMSE = 2.73). Based on this, a linear regression equation was derived and used to convert the canopy height measured with a laser scanner to the actual plant height. The rice growth curve drawn by combining the actual and estimated plant height collected by various nitrogen fertilization conditions and growth period shows that the laser scanner-based canopy height measurement technology can be effectively utilized for assessing the plant height and growth of rice. In the future, 3D images derived from laser scanners are expected to be applicable to crop biomass estimation, plant shape analysis, etc., and can be used as a technology for digital conversion of conventional crop growth assessment methods.

• Atmosphere
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• v.25 no.2
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• pp.339-351
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• 2015

The purpose of this study is for the fundamental understandings about building morphological parameters and aerodynamic roughness parameters of Seoul, Korea using the detailed urban geographic information datasets. Applied roughness parameter calculations are based on a digital map of buildings with lot area polygons. The quality of the developed roughness length ($z_0$) of Seoul was evaluated with densely installed 107 automatic weather stations. The correlation coefficient results between averaged wind speeds of AWS data and averaged $z_0$ is -0.303 in night and -0.398 in day (200 m radii circles case). Further $z_0$ enhancement should follow by considering other surface features such as high tree and orography of Seoul. However, this study would meet the needs to for local- or meso-scale meteorological modeling applications of Seoul. However, further studies would require for enhancing the $z_0$ applications of Seoul.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.6
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• pp.547-555
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• 2015

The vegetation index is a crucial parameter in many biophysical studies of vegetation, and is also a valuable content in ecological processes researching. The OVIs (Optical Vegetation Index) that of using multispectral and hyperspectral data have been widely investigated in the literature, while the RVI (Radar Vegetation Index) that of considering volume scattering measurement has been paid relatively little attention. Also, there was only some efforts have been put to fuse the OVI with the RVI as an integrated vegetation index. To address this issue, this paper presents a novel FVI (Fusion Vegetation Index) that uses multispectral and full-PolSAR (Polarimetric Synthetic Aperture Radar) data. By fusing a NDVI (Normalized Difference Vegetation Index) of RapidEye and an RVI of C-band Radarsat-2, we demonstrated that the proposed FVI has higher separability in different vegetation types than only with OVI and RVI. Also, the experimental results show that the proposed index not only has information on the vegetation greenness of the NDVI, but also has information on the canopy structure of the RVI. Based on this preliminary result, since the vegetation monitoring is more detailed, it could be possible in various application fields; this synergistic FVI will be further developed in the future.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.4
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• pp.232-245
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• 2017

In this study, the high-resolution numerical simulation results considering landuse characteristics are analyzed by using single layer Urban Canopy Model (UCM) in Weather Research Forecast (WRF). For this, the impact of urban parameters such as roughness length and anthropogenic heat in UCM is analyzed. These values are adjusted to Seoul metropolitan area in Korea. The results of assessment are verified against observation from surface and flux tower. Forecast system equipped with UCM shows an overall improvement in the simulations of meteorological parameters, especially temperature at 2 m, surface sensible and latent heat flux. Major contribution of UCM is appreciably found in urban area rather than non-urban. The non-urban area is indirectly affected. In simulated latent heat flux, applying UCM is possible to simulate the change similarly with observations on urban area. Anthropogenic heat employed in UCM shows the most realistic results in terms of temperature and surface heat flux, indicating thermodynamic treatment of UCM could enhance the skills of high resolution forecast model in urban and non-urban area.

• Korean Journal of Remote Sensing
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• v.40 no.4
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• pp.397-418
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• 2024

The Land Surface Temperature (LST) is a crucial parameter in identifying drought. It is essential to identify how LST can increase its accuracy, particularly in mountainous and hill areas. Increasing the LST accuracy can be achieved by applying early data processing in the correction phase, specifically in the context of topographic correction on the Lambertian model. Empirical evidence has demonstrated that this particular stage effectively enhances the process of identifying objects, especially within areas that lack direct illumination. Therefore, this research aims to examine the application of the Lambertian model in estimating LST using the Multi-Channel Method (MCM) across various physiographic regions. Lambertian model is a method that utilizes Lambertian reflectance and specifically addresses the radiance value obtained from Sun-Canopy-Sensor(SCS) and Cosine Correction measurements. Applying topographical adjustment to the LST outcome results in a notable augmentation in the dispersion of LST values. Nevertheless, the area physiography is also significant as the plains terrain tends to have an extreme LST value of ≥ 350 K. In mountainous and hilly terrains, the LST value often falls within the range of 310-325 K. The absence of topographic correction in LST results in varying values: 22 K for the plains area, 12-21 K for hilly and mountainous terrain, and 7-9 K for both plains and mountainous terrains. Furthermore, validation results indicate that employing the Lambertian model with SCS and Cosine Correction methods yields superior outcomes compared to processing without the Lambertian model, particularly in hilly and mountainous terrain. Conversely, in plain areas, the Lambertian model's application proves suboptimal. Additionally, the relationship between physiography and LST derived using the Lambertian model shows a high average R² value of 0.99. The lowest errors(K) and root mean square error values, approximately ±2 K and 0.54, respectively, were achieved using the Lambertian model with the SCS method. Based on the findings, this research concluded that the Lambertian model could increase LST values. These corrected values are often higher than the LST values obtained without the Lambertian model.

• Korean Journal of Soil Science and Fertilizer
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• v.40 no.6
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• pp.435-441
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• 2007

Ground-based optical sensing over the crop canopy provides information on the mass of plant body which reflects the light, as well as crop nitrogen content which is closely related to the greenness of plant leaves. This method has the merits of being non-destructive real-time based, and thus can be conveniently used for decision making on application of nitrogen fertilizers for crops standing in fields. In the present study relationships among leaf nitrogen content of rice canopy, crop growth status, and Normalized Difference Vegetation Index (NDVI) values were investigated. We measured Green normalized difference vegetation index($gNDVI=({\rho}0.80{\mu}m-{\rho}0.55{\mu}m)/({\rho}0.80{\mu}m+{\rho}0.55{\mu}m)$) and NDVI($({\rho}0.80{\mu}m-{\rho}0.68{\mu}m)/({\rho}0.80{\mu}m+{\rho}0.68{\mu}m)$) were measured by using two different active sensors (Greenseeker, NTech Inc. USA). The study was conducted in the years 2005-06 during the rice growing season at the experimental plots of National Institute of Agricultural Science and Technology located at Suwon, Korea. The experiments carried out with randomized complete block design with the application of four levels of nitrogen fertilizers (0, 70, 100, 130kg N/ha) and same amount of phosphorous and potassium content of the fertilizers. gNDVI and rNDVI increased as growth advanced and reached to maximum values at around early August, G(NDVI) were a decrease in values of observed with the crop maturation. gNDVI values and leaf nitrogen content were highly correlated at early July in 2005 and 2006. On the basis of this finding we attempted to estimate the leaf N contents using gNDVI data obtained in 2005 and 2006. The determination coefficients of the linear model by gNDVI in the years 2005 and 2006 were 0.88 and 0.94, respectively. The measured and estimated leaf N contents using gNDVI values showed good agreement ($R^2=0.86^{***}$). Results from this study show that gNDVI values represent a significant positive correlation with leaf N contents and can be used to estimate leaf N before the panicle formation stage. gNDVI appeared to be a very effective parameter to estimate leaf N content the rice canopy.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2008.06a
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• pp.310-317
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• 2008

Although aerial LiDAR had been launched commercially several years ago, it is still difficult to study data acquisition conditions and effects with various datasets because of its acquisition cost. Thus, this research was performed to study data acquisition conditions and effects with virtually various datasets. For this research, 3D tree models and forest stand models were built to represent graded tree sizes and tree plantation densities. Also, a variable aerial LiDAR acquisition model was developed. Then, through controlling flight height parameter, one of the data acquisition parameters, virtual datasets were collected for various data acquisition densities. From those datasets, forest canopy volumes and maximum tree heights were estimated and the estimated results were compared. As the results, the estimated is getting closer to the expected during the data acquisition density increase. This research would be helpful to perform further studios on relations between forest inventory accuracy and LiDAR cost.

• Spatial Information Research
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• v.20 no.3
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• pp.27-38
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• 2012

As the necessity of forest conservation and management has been increased, various forest studies using LIDAR data have been actively performed. These studies often utilize the tree height as an important parameter to measure the forest quantitatively. This study thus attempt to apply two representative methods to estimate tree height from airborne LIDAR data and compare the results. The first method based on the detection of the individual trees using a local maximum filter estimates the number of trees, the position and heights of the individual trees, and the mean tree height. The other method estimates the maximum and mean tree height, and the crown mean height for each grid cell or the entire area from the canopy height model (CHM) and height histogram. In comparison with the field measurements, 76.6% of the individual trees are detected correctly; and the estimated heights of all trees and only conifer trees show the RMSE of 1.91m and 0.75m, respectively. The tree mean heights estimated from CHM retain about 1~2m RMSE, and the histogram method underestimates the tree mean height with about 0.6m. For more accurate derivation of diverse forest information, we should select and integrate the complimentary methods appropriate to the tree types and estimation parameters.