• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.3
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• pp.190-198
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• 2006

Radiation use efficiency (RUE), the amount of biomass produced per unit intercepted photosynthetically active radiation (PAR), constitutes a main part of crop growth simulation models. The objective of the present study was to evaluate the variation of RUE of rice plants under various nitrogen nutritive conditions. from 1998 to 2000, shoot dry weight (DW), intercepted PAR of rice canopies, and nitrogen nutritive status were measured in various nitrogen fertilization regimes using japonica and Tongil-type varieties. These data were used for estimating the average RUEs before heading and the relationship between RUE and the nitrogen nutritive status. The canopy extinction coefficient (K) increased with the growth of rice until maximum tillering stage and maintained constant at about 0.4 from maximum tillering to heading stage, rapidly increasing again after heading stage. The DW growth revealed significant linear correlation with the cumulative PAR interception of the canopy, enabling the estimation of the average RUE before heading with the slopes of the regression lines. Average RUE tended to increase with the increased level of nitrogen fertilization. RUE increased approaching maximum as the nitrogen nutrition index (NNI) calculated by the ratio of actual shoot N concentration to the critical N concentration for the maximum growth at any growth stage and the specific leaf nitrogen $(SLN;\;g/m^2\;leaf\;area)$ increased. This relationship between RUE (g/MJ of PAR) and N nutritive status was expressed well by the following exponential functions: $$RUE=3.13\{1-exp(-4.33NNNI+1.26)\}$$ $$RUE=3.17\{1-exp(-1.33SLN+0.04)\}$$ The above equations explained, respectively, about 80% and 75% of the average RUE variation due to varying nitrogen nutritive status of rice plants. However, these equations would have some limitations if incorporated as a component model to simulate the rice growth as they are based on relationships averaged over the entire growth period before heading.

• Korean Journal of Environment and Ecology
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• v.26 no.4
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• pp.528-536
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• 2012

This study has compared the different types of forest fires(unburned, crown fire, ground fire) and the degree of vegetation recovery at Samcheuk-si, Gangwon-do by assessing the biomass and net primary production from July 2007 through July 2010. The research showed that the average biomass of unburned site(Un), crown fire site(C-1), crown fire site(C-3), ground fire site(G-2) were $181.20{\pm}5.39$, $62.04{\pm}4.38$, $131.09{\pm}14.38$, $63.39{\pm}2.72ton{\cdot}ha^{-1}$, respectively. And the research showed that the average net primary production of unburned site(Un), crown fire site(C-1), crown fire site(C-3), ground fire site(G-2) were $4.17{\pm}0.56$, $3.27{\pm}1.56$, $11.51{\pm}0.53$, $2.10{\pm}0.31ton{\cdot}ha^{-1}{\cdot}yr^{-1}$, respectively. Quercus mongolica $DH_{10}$(Diameter at the 10cm tree height) growth rate at each plot was compared to the crown fire site(C-1) in the annual average $1.21{\pm}0.55mm{\cdot}yr^{-1}$ at the speed of the fastest growth follows; showed crown fire site(C-3), ground fire site(G-2), unburned site(Un) appeared in the order. And that showed the growth rate of height was highest in the $15.43{\pm}4.57cm{\cdot}yr^{-1}$ at crown fire site(C-3), then the crown fire site(C-1), and ground fire site(G-2), and lowest in the unburned site(Un).

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.28 no.3
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• pp.114-121
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• 2010

Traditional temples in Korea are the important cultural heritage because of artistic traditonal buildings and structures, paintings, sculptures, and big forest areas which are most ecological and beautiful in Korea. Since traditional temples still function as religious places for very long time, the sense of places intrinsic to the temples are very strong and vivid. The sense of place is very closely related to the conservation of the original landscape type. Recently however, there is a strong tendency to use solar energy in traditional temples because of the low energy efficiency of the old traditional architecture which may have negative impact on landscape which again in turn may lead to the destruction of the sense of place. The purpose of this study was to suggest some landscape design guidelines to protect the sense of place of traditional temple by investigating the impact of solar energy facility on the landscape experience of traditional temple. In order to do perform this purpose, Tongdosa was selected as a study site and four kinds of measurement tools(landscape image, temple identity, landscape satisfaction, degree of landscape improvement) were used as questionnaire items. 180 college students participated in the questionnaire survey. The analysis showed that the solar energy facility had very negative impact on landscape experience such as three landscape image factors(scenic beauty, openness, complexity), landscape satisfaction, temple identity, and landscape improvement. Based on the results, three landscape improvement plans were suggested. First, solar energy facility should be built in the forest in order not to be exposed to visitors, if possible. Second, the landscape management of traditional temple should emphasize on sustaining scenic beauty and temple identity along with the provision of openness. Lastly, detailed landscape guideline should be prepared to regulate the scale, ratio, and the form of the artificial buildings and structures to protect the sense of place of traditional temple.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.28 no.2
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• pp.67-74
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• 2010

Law-protected trees are our precious asset as natural resources with history and tradition and natural heritage which should be protected and maintained well to bequeath next generation. Law-protected trees have not only thremmatologic and genetic meaning but also environmental and emotional meaning for their value to be high. This study investigated location, vitality, wrapping condition of root area and status of maintenance of the trees to figure out their growth environment and status of maintenance in a small-middle city through survey on those of law-protected trees in Je-cheon. There showed 300 more year old trees in Je-cheon mostly and the number of trees located in flat fields was the highest. For location type, village, hill and road types were presented in the order and for degree of development, land for building was found most frequently. The average electric resistance of the formative layer was measured to be $8.4k{\Omega}$ and four trees showed bark separation. Most law-protected trees underwent tree surgery, and complete bareness of root area was observed in a tree. The root area of two trees was covered with concrete. pH of soil was recorded to be 5.0~8.4 with its average of 7.1 and electric conductivity(EC) was less than 0.5 dS/m. For status of maintenance rearing facilities were placed for 16 trees out of totally 48 ones and stone fence was done for three ones. Tree surgery was conducted for 33 trees to prevent and to treat decomposed parts of holes. Direction boards were installed for 23 trees. Based on these results, measures to manage systematically law-protected trees in Jecheon could be suggested as follows. First, a sufficient space for growth of low part of trees should be secured. Second, a voluntary management should be induced by advertising them to residents in a community. Third, rearing facilities and direction boards of law-protected trees should be placed and related education should be conducted. Fourth, through operation of the department for law-protected trees consisting of related professions and cooperation among related departments the trees should be maintained continuously.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.1
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• pp.48-59
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• 2023

Ground-level ozone affects human health and plant growth. Ozone is produced by chemical reactions between oxides of nitrogen (NOx) and volatile organic compounds (VOCs) from anthropogenic and biogenic sources. In this study, two different land cover and emission factor datasets were input to the MEGAN v2.1 emission model to examine how these parameters contribute to the biogenic emissions and ozone production. Four input sensitivity scenarios (A, B, C and D) were generated from land cover and vegetation emission factors combination. The effects of BVOCs emissions by scenario were also investigated. From air quality modeling result using CAMx, maximum 1 hour ozone concentrations were estimated 62 ppb, 60 ppb, 68 ppb, 65 ppb, 55 ppb for scenarios A, B, C, D and E, respectively. For maximum 8 hour ozone concentration, 57 ppb, 56 ppb, 63 ppb, 60 ppb, and 53 ppb were estimated by scenario. The minimum difference by land cover was up to 25 ppb and by emission factor that was up to 35 ppb. From the modeling performance evaluation using ground ozone measurement over the six regions (East Seoul, West Seoul, Incheon, Namyangju, Wonju, and Daegu), the model performed well in terms of the correlation coefficient (0.6 to 0.82). For the 4 urban regions (East Seoul, West Seoul, Incheon, and Namyangju), ozone simulations were not quite sensitive to the change of BVOC emissions. For rural regions (Wonju and Daegu) , however, BVOC emission affected ozone concentration much more than previously mentioned regions, especially in case of scenario C. This implies the importance of biogenic emissions on ozone production over the sub-urban to rural regions.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.337-345
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• 2023

Estimating the rice heading date is one of the most crucial agricultural tasks related to productivity. However, due to abnormal climates around the world, it is becoming increasingly challenging to estimate the rice heading date. Therefore, a more objective classification method for estimating the rice heading date is needed than the existing methods. This study, we aimed to classify the rice heading stage from various images using a CNN classification model. We collected top-view images taken from a drone and a phenotyping tower, as well as slanted-view images captured with a RGB camera. The collected images underwent preprocessing to prepare them as input data for the CNN model. The CNN architectures employed were ResNet50, InceptionV3, and VGG19, which are commonly used in image classification models. The accuracy of the models all showed an accuracy of 0.98 or higher regardless of each architecture and type of image. We also used Grad-CAM to visually check which features of the image the model looked at and classified. Then verified our model accurately measure the rice heading date in paddy fields. The rice heading date was estimated to be approximately one day apart on average in the four paddy fields. This method suggests that the water head can be estimated automatically and quantitatively when estimating the rice heading date from various paddy field monitoring images.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.3
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• pp.129-141
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• 2023

Crop models have been used to predict yield under diverse environmental and cultivation conditions, which can be used to support decisions on the management of forage crop. Cultivar parameters are one of required inputs to crop models in order to represent genetic properties for a given forage cultivar. The objectives of this study were to compare calibration and ensemble approaches in order to minimize the uncertainty of crop yield estimates using the SIMPLE crop model. Cultivar parameters were calibrated using Log-likelihood (LL) and Generic Composite Similarity Measure (GCSM) as an objective function for Metropolis-Hastings (MH) algorithm. In total, 20 sets of cultivar parameters were generated for each method. Two types of ensemble approach. First type of ensemble approach was the average of model outputs (E_em), using individual parameters. The second ensemble approach was model output (E_pm) of cultivar parameter obtained by averaging given 20 sets of parameters. Comparison was done for each cultivar and for each error calculation methods. 'Jowoo' and 'Yeongwoo', which are forage rice cultivars used in Korea, were subject to the parameter calibration. Yield data were obtained from experiment fields at Suwon, Jeonju, Naju and I ksan. Data for 2013, 2014 and 2016 were used for parameter calibration. For validation, yield data reported from 2016 to 2018 at Suwon was used. Initial calibration indicated that genetic coefficients obtained by LL were distributed in a narrower range than coefficients obtained by GCSM. A two-sample t-test was performed to compare between different methods of ensemble approaches and no significant difference was found between them. Uncertainty of GCSM can be neutralized by adjusting the acceptance probability. The other ensemble method (E_pm) indicates that the uncertainty can be reduced with less computation using ensemble approach.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.70-82
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• 2023

The recent surge of IT and data acquisition is shifting the paradigm in all aspects of life, and these advances are also affecting academic fields. Research topics and methods are being improved through academic exchange and connections. In particular, data-based research methods are employed in various academic fields, including landscape architecture, where continuous research is needed. Therefore, this study aims to investigate the possibility of developing a landscape preference evaluation and prediction model using machine learning, a branch of Artificial Intelligence, reflecting the current situation. To achieve the goal of this study, machine learning techniques were applied to the landscaping field to build a landscape preference evaluation and prediction model to verify the simulation accuracy of the model. For this, wind power facility landscape images, recently attracting attention as a renewable energy source, were selected as the research objects. For analysis, images of the wind power facility landscapes were collected using web crawling techniques, and an analysis dataset was built. Orange version 3.33, a program from the University of Ljubljana was used for machine learning analysis to derive a prediction model with excellent performance. IA model that integrates the evaluation criteria of machine learning and a separate model structure for the evaluation criteria were used to generate a model using kNN, SVM, Random Forest, Logistic Regression, and Neural Network algorithms suitable for machine learning classification models. The performance evaluation of the generated models was conducted to derive the most suitable prediction model. The prediction model derived in this study separately evaluates three evaluation criteria, including classification by type of landscape, classification by distance between landscape and target, and classification by preference, and then synthesizes and predicts results. As a result of the study, a prediction model with a high accuracy of 0.986 for the evaluation criterion according to the type of landscape, 0.973 for the evaluation criterion according to the distance, and 0.952 for the evaluation criterion according to the preference was developed, and it can be seen that the verification process through the evaluation of data prediction results exceeds the required performance value of the model. As an experimental attempt to investigate the possibility of developing a prediction model using machine learning in landscape-related research, this study was able to confirm the possibility of creating a high-performance prediction model by building a data set through the collection and refinement of image data and subsequently utilizing it in landscape-related research fields. Based on the results, implications, and limitations of this study, it is believed that it is possible to develop various types of landscape prediction models, including wind power facility natural, and cultural landscapes. Machine learning techniques can be more useful and valuable in the field of landscape architecture by exploring and applying research methods appropriate to the topic, reducing the time of data classification through the study of a model that classifies images according to landscape types or analyzing the importance of landscape planning factors through the analysis of landscape prediction factors using machine learning.

• Management & Information Systems Review
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• v.29 no.4
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• pp.305-332
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• 2010

This study was searching for elements affecting satisfaction of customers by comparing health management service businesses such as wellbeing care, yoga, and fitness. The discovered elements were analyzed and verified to find which elements are affecting what businesses through case studies. Multidirectional analysis was implemented for each service type using program, physical environment, and provided service drawn from the previous researches with SERVQUAL criteria and measured values on customer satisfactions. According to the analysis, physical environment in forest wellbeing care, program in yoga, and provided service in fitness were the most affecting elements. Thus, each health management service business must consider the lifestyle and trend of customers, and the specialized service corresponding to its uniqueness must be provided to customers. Surely, modernized exercise equipment, personalized program, and comfortable-luxurious settings are must have in order to be competitive. In addition, the business owners have to realize that customers are moving to quality from quantity. This means exercise must be brought up to the level of social value for relationship and links rather than left at the level of simple physical and mental trainings. To achieve these, other programs to support relationship among customers and circulating system with friendly environment must be considered at the same time.

• Journal of Environmental Impact Assessment
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• v.24 no.3
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• pp.287-299
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• 2015

If the Nakdong River estuary is to be sustainable, land use management practices need to consider bird habitat requirements, especially given that the area serves as an important migratory bird sanctuary. In this study, bird habitats found in the Nakdong River estuary were classified into 11 different types including Phragmites australiss, mud flat, farmland, open surface in freshwater, sand bar, riparian forest, Scirpus planiculmis, waterway, construction, grasslands, and open surface in sea or brackish water. Taking into consideration the regional characteristics, habitat properties, and landscape indices, a total of 12 study sites were analyzed. Mud flat, construction, farmland, and P. australis account for 80% of the total land area. The high area ratio of construction and farmland to other types of habitat revealed a high amount of historical human activity and intervention in the area. Both patch numbers as well as patch density were high in West Nakdong River, Samrak Waterfront, Maekdo River, and Daejeo Floodgate, with these areas showing the greatest fragmentation as well. Total numbers of species and individuals had a positive correlation with the area and the number of habitat types. Findings suggest that protecting the habitat area, especially in S. planiculmis, is the most important factor for bird habitat management and that future development could result in habitat loss, having a profoundly adverse impact on bird populations. Therefore, it is important that the total area should be carefully protected by land use regulations in order to ensure that the Nakdong River estuary maintains its functional integrity as a migratory bird sanctuary.