• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.330-330
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• 2016

The quantification of dry season evaporation in regions, where the magnitude of dry season flows is key to the regional water supply, is essential for good water management. Also, tree transpiration has a significant role in the water balance of a catchment whenever it is tree populated, especially in water limited environments. Such is the case in the Middle Mountains of Nepal where dry season flows play a significant role in downstream water provisioning and their proper functioning is key to the welfare of millions of people. This research seeks to study the transpiration of a pine forest stand in the Jikhu Khola Watershed in the Middle Mountains of Nepal. To the author's knowledge, no single study has been made so far to estimate the dry season evaporation from the planted forest stand in the Middle Mountains of Nepal. The study was carried out in planted pine forest embedded within the Jikhu Khola Catchment. Field campaigns of sap flow measurements were carried out from September, 2010 to February, 2011 in the selected plot of 15*15m dimension, to characterize dry season evaporation. This was done by measuring sap fluxes and sapwood areas over the six trees of different Diameter at Breast Height (DBH) classes. The sap flux was assessed using Granier's thermal dissipation probe (TDP) technique while sapwood area was determined using several incremental core(s) taken with a Pressler borer and immediately dyeing with methyl orange for estimating the actual depth of sapwood area. Transpiration of the plot was estimated by considering the contribution of each tree class. For this purpose, sap flux density, sapwood area and the proportion of total canopy area were determined for each tree class of the selected plot. From these data, hourly and diurnal transpiration rates for the plot were calculated for experimental period. Finally, Cienciala model was parameterized using the data recorded by the ADAS and other terrain data collected in the field. The calibrated model allowed the extrapolation of Sap flux density (v) over a six month period, from September 2010 to February 2011. The model given sap flux density was validated with the measured sap flux density from Grainier method.

• 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.

• Journal of Korean Society of Forest Science
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• v.84 no.2
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• pp.258-265
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• 1995

Regeneration process of edaphic pine(Pinus densiflora) climax forest in Bulyung-gyegog, Uljin-gun, Kyungsangbuk-do, was studied. The height of dominant trees in the stands are 12 15m. Upper layers are highly dominated by pine trees and are randomly distributed. Pine trees in lower layer grow in a patch type. In the upper layer, the age distribution is likely one model type with mode of 60 and 80 years. In the horizontal distribution of these trees, some of the even-aged cluster constituted of several tree were found. For the first 25 years, the stem diameter increment rates in upper layer are higher than those in the middle layer. It could be concluded that after the forest canopy had been broken out, the seedlings established densely in a patch in the gap with the decreasing density and some of them, distributed in random, would constitute the canopy.

• Journal of Environmental Impact Assessment
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• v.21 no.5
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• pp.665-681
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• 2012

This study investigates the influence of anthropogenic heat (AH) release on urban boundary layer in the Gyeong-In region using the Weather Research and Forecasting model that includes the Seoul National University Urban Canopy Model (SNUUCM). The gridded AH emission data, which is estimated in the Gyeong-In region in 2002 based on the energy consumption statistics data, are implemented into the SNUUCM. The simulated air temperature and wind speed show good agreement with the observed ones particularly in terms of phase for 11 urban sites, but they are overestimated in the nighttime. It is found that the influence of AH release on air temperature is larger in the nighttime than in the daytime even though the AH intensity is larger in the daytime. As compared with the results with AH release and without AH release, the contribution of AH release on urban heat island intensity is large in the nighttime and in the morning. As the AH intensity increases, the water vapor mixing ratio decreases in the daytime but increases in the nighttime. The atmospheric boundary layer height increases greatly in the morning (0800 - 1100 LST) and midnight (0000 LST). These results indicate that AH release can have an impact on weather and air quality in urban areas.

• Journal of Bio-Environment Control
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• v.32 no.4
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• pp.366-376
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• 2023

This study was conducted to develop a model for predicting the growth of kimchi cabbage using image data and environmental data. Kimchi cabbages of the 'Cheongmyeong Gaual' variety were planted three times on July 11th, July 19th, and July 27th at a test field located at Pyeongchang-gun, Gangwon-do (37°37' N 128°32' E, 510 elevation), and data on growth, images, and environmental conditions were collected until September 12th. To select key factors for the kimchi cabbage growth prediction model, a correlation analysis was conducted using the collected growth data and meteorological data. The correlation coefficient between fresh weight and growth degree days (GDD) and between fresh weight and integrated solar radiation showed a high correlation coefficient of 0.88. Additionally, fresh weight had significant correlations with height and leaf area of kimchi cabbages, with correlation coefficients of 0.78 and 0.79, respectively. Canopy coverage was selected from the image data and GDD was selected from the environmental data based on references from previous researches. A prediction model for kimchi cabbage of biomass, leaf count, and leaf area was developed by combining GDD, canopy coverage and growth data. Single-factor models, including quadratic, sigmoid, and logistic models, were created and the sigmoid prediction model showed the best explanatory power according to the evaluation results. Developing a multi-factor growth prediction model by combining GDD and canopy coverage resulted in improved determination coefficients of 0.9, 0.95, and 0.89 for biomass, leaf count, and leaf area, respectively, compared to single-factor prediction models. To validate the developed model, validation was conducted and the determination coefficient between measured and predicted fresh weight was 0.91, with an RMSE of 134.2 g, indicating high prediction accuracy. In the past, kimchi cabbage growth prediction was often based on meteorological or image data, which resulted in low predictive accuracy due to the inability to reflect on-site conditions or the heading up of kimchi cabbage. Combining these two prediction methods is expected to enhance the accuracy of crop yield predictions by compensating for the weaknesses of each observation method.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1043-1059
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• 2021

Forest and agricultural land are very important factors in the environmental ecosystem and securing food resources. Forest and agricultural land should be monitored regularly. CAS500-4 data are expected to be effectively used as a supplement of monitoring forest and agricultural land. Prior to the launch of the CAS500-4, the relative canopy height error analysis of the digital elevation model on South Korea was performed to determine the vertical target accuracy. Especially, by considering area of interest of the CAS500-4 (mountainous or agricultural area), it is conducted that vertical error analysis according to the slope and canopy. For Gongju, Jeju, and Samcheok, the average root mean squared differences were calculated compared to the drone LiDAR digitalsurface models, which were filmed in autumn and winter and the 5 m digital elevation model from the National Geographic Information Institute. As a result, the Shuttle radar topography mission digital elevation model showed a root mean squared differences of about 8.35, 8.19, and 7.49 m, respectively, while the Copernicus digital elevation model showed a root mean squared differences of about 5.65, 6.73, and 7.39 m, respectively. In addition, the root mean squared difference of shuttle radar topography mission digital elevation model and the Copernicus digital elevation model according to the slope angle were estimated on South Korea compared to the 5 m digital elevation model from the National Geographic Information Institute. At the slope angle of between 0° to 5°, root mean squared differences of the Shuttle radar topography mission digital elevation model and the Copernicus digital elevation model showed 3.62 and 2.52 m, respectively. On the other hands root mean squared differences of the Shuttle radar topography mission digital elevation model and the Copernicus digital elevation model respectively showed about 10.16 and 11.62 m at the slope angle of 35° or higher.

• Journal of the Korean Institute of Landscape Architecture
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• v.28 no.6
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• pp.1-15
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• 2001

The purpose of this study is to figure out the structural characteristics of urban plant community and suggest restoration model of Quercus mongolica in the case of Korean national Capital Region. The investigation areas were selected from urban area of Mt. Nam at Chung-Gu, suburban areas of Mt. Bong at Eunpyoung-GU, Mt. Sungju at Buchon City and non-urban areas of Mt. Suri at Kunpu City and Mt. Chonma t namyangju-City. After the main study field had been classified into the evaluation of the ecological characteristics and the modeling of the vegetation. We analyzed to evaluate the ecological characteristics of the forest structure -- successional stage, naturalness, multi-layer structure of the forest and species diversity, and the plant community structures. We have proposed vegetation restoration model based on the selection of proper plants, the number of individuals, diameter short area of breast height, the shortest distance between plants in non-urban area. As for successional stage, It was judged that the ecological succession may not be followed like the present stage of the surveyed areas in urban, suburban and non-ruban areas. As for the retention of naturalness and multi-layer structures of vegetation, In Quercus mongolica community, Robinia pseudo-acacia and Ailanthus altissima occurred in each layers at Mt. Nam, Mt. Bong and Mt. Sungju, and Eupatorium rugosum occurred in herbaceous layer at Mt. Nam. Consequently, the ecological restoration plan following the structure of the vegetation in Mt. Chonma seemed to be advisable in Q. mongolica community, there were less number of species and individuals in urban areas than those of non-urban areas. Planting of trees following the simulated native plant community of non-urban areas seemed to be required to promote the plants in urban areas. Considering the number of individuals up to three layers in each 400$m^2$ area, it was composed of twenty nine in canopy layer, forth nine in understory layer, 367 in shrub layer and 33.7% herbaceous ground cover in the Q.mongolica community. The suggested restoration model in this study is nan applicable model for the introduction in the cities, and this study shows that continuous experiments and field investigation on this model should be performed in the future.

• Korean Journal of Exercise Nutrition
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• v.24 no.1
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• pp.9-13
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• 2020

[Purpose] This preliminary study aimed to develop a regression model to estimate the resting metabolic rate (RMR) of young and middle-aged Koreans using various easy-to-measure dependent variables. [Methods] The RMR and the dependent variables for its estimation (e.g. age, height, body mass index, fat-free mass; FFM, fat mass, % body fat, systolic blood pressure, diastolic blood pressure, mean arterial pressure, pulse pressure, and resting heart rate) were measured in 53 young (male n = 18, female n = 16) and middle-aged (male n = 5, female n = 14) healthy adults. Statistical analysis was performed to develop an RMR estimation regression model using the stepwise regression method. [Results] We confirmed that FFM and age were important variables in both the regression models based on the regression coefficients. Mean explanatory power of RMR₁ regression models estimated only by FFM was 66.7% (R²) and 66.0% (adjusted R²), while mean standard errors of estimates (SEE) was 219.85 kcal/day. Additionally, mean explanatory power of RMR₂ regression models developed by FFM and age were 70.0% (R²) and 68.8% (adjusted R²), while the mean SEE was 210.64 kcal/day. There was no significant difference between the measured RMR by the canopy method using a metabolic gas analyzer and the predicted RMR by RMR₁ and RMR₂ equations. [Conclusion] This preliminary study developed a regression model to estimate the RMR of young and middle-age healthy Koreans. The regression model was as follows: RMR₁ = 24.383 × FFM + 634.310, RMR₂ = 23.691 × FFM - 5.745 × age + 852.341.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.16 no.6 s.97
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• pp.615-621
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• 2005

In this paper, a model for simulating synthetic aperture radar(SAR) images of earth surfaces. The earth surfaces include forest area, rice crop field, other agricultural fields, grass field, road, and water surface. At first, the backscattering models are developed for bare soil surfaces, water surfaces, short vegetation fields such as rice fields and grass field, other agriculture areas, and forest areas. Then, the SAR images are generated from the digital elevation model(DEM) and digital terrain map. The DTM includes ten parameters, such as soil moisture, surface roughness, canopy height, leaf width, leaf length, leaf density, branch length, branch density, trunk length, and trunk density, if applicable. The scattering models are verified with measurements, and applied to generate an SAR image for an area.

• Journal of the Korean earth science society
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• v.41 no.2
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• pp.111-128
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• 2020

This study presents a possibility of intensification of fine dust mass concentration due to the complex urban structure using data mining technique and clustering analysis. The data mining technique showed no significant correlation between fine dust concentration and regional-use public urban data over Seoul. However, clustering analysis based on nationwide-use public data showed that building heights (floors) have a strong correlation particularly with PM₁₀. The modeling analyses using the single canopy model and the micro-atmospheric modeling program (ENVI-Met. 4) conducted that the controlled atmospheric convection in urban area leaded to the congested flow pattern depending on the building along the distribution and height. The complex structure of urban building controls convective activity resulted in stagnation condition and fine dust increase near the surface. Consequently, the residual effect through the changes in the thermal environment caused by the shape and structure of the urban buildings must be considered in the fine dust distribution. It is notable that the atmospheric congestion may be misidentified as an important implications for providing information about the residual probability of fine dust mass concentration in the complex urban area.