• Korean Journal of Environment and Ecology
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• v.29 no.1
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• pp.14-20
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• 2015

We created species richness maps of mammals, birds and plants using "Nnational Ecosystem Survey" data and identified correlations between species richness maps of each taxa. We examine the distribution of species richness of each taxa and calculated conservation priority rank through plotting species-area curves using an additive benefit function in Zonation. The conclusions of this study are as follows. First, plant showed high species richness in Gangwon province and Baekdudaegan, and mammals showed high species richness at eastern slope of Baekdudaegan in Gangwon province unusually and the species richness of mammals distributed equally except Gyeonggi and Chungnam province. However, birds showed high species richness in the west costal because the area is the major route of winter migratory birds. Second, correlation of each taxa's distribution is not significant. Correlation between mammals and birds is positive but correlations between birds and others are negative. Because mammals inhabit in forest but birds mostly live in coastal wetlands and rivers. Therefore, bird's habitats are not shared with other habitats. Third, the probability of mammals occurrence is very low under 25% in species-area curve, others increase proportionally to area. Birds increase dramatically richness at 10% because bird's habitat is concentrated in coastal wetlands and rivers. Plants increased gently species richness due to large forest in Gangwon province. We can calculate the predicted number of species in curves and plan various conservation strategies using the marginal number of species. Finally, high priority ranks for conservation distributed mainly in Gangwon province and Baekdudaegan. When we compared with priority map and terrestrial national parks, the parks were evaluated as high priority ranks. However, the rank of parks away from Baekdudaegan was low. This study has the meaning of selecting conservation priority area using National Ecosystem Survey. In spite of the omission of survey data in national parks and Baekdudaegan, the results were good. Therefore, the priority rank method using species distribution models is useful to selecting protected areas and improving conservation plans. However, it is needed to select protected areas considering various evaluation factors, such as rarity, connectivity, representativeness, focal species and so on because there is a limit to select protected area only using species richness.

• Korean Journal of Soil Science and Fertilizer
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• v.50 no.5
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• pp.422-433
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• 2017

Unmanned Aerial Vehicle (UAV) has several advantages over conventional remote sensing techniques. They can acquire high-resolution images quickly and repeatedly. And with a comparatively lower flight altitude, they can obtain good quality images even in cloudy weather. In this paper, we developed for estimating garlic growth at field scale model in major cultivation regions. We used the $NDVI_{UAV}$ that reflects the crop conditions, and seven meteorological elements for 3 major cultivation regions from 2015 to 2017. For this study, UAV imagery was taken at Taean, Changnyeong, and Hapcheon regions nine times from early February to late June during the garlic growing season. Four plant growth parameters, plant height (P.H.), leaf number (L.N.), plant diameter (P.D.), and fresh weight (F.W.) were measured for twenty plants per plot for each field campaign. The multiple linear regression models were suggested by using backward elimination and stepwise selection in the extraction of independent variables. As a result, model of cold type explain 82.1%, 65.9%, 64.5%, and 61.7% of the P.H., F.W., L.N., P.D. with a root mean square error (RMSE) of 7.98 cm, 5.91 g, 1.05, and 3.43 cm. Especially, model of warm type explain 92.9%, 88.6%, 62.8%, 54.6% of the P.H., P.D., L.N., F.W. with a root mean square error (RMSE) of 16.41 cm, 9.08 cm, 1.12, 19.51 g. The spatial distribution map of garlic growth was in strong agreement with the field measurements in terms of field variation and relative numerical values when $NDVI_{UAV}$ was applied to multiple linear regression models. These results will also be useful for determining the UAV multi-spectral imagery necessary to estimate growth parameters of garlic.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.6
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• pp.741-747
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• 2009

For construction of 3D virtual city models, airborne digital cameras, laser scanners, multi-oblique photograph systems and other devices are currently being used. With such advanced techniques, precise 3D spatial information can be collected and high quality 3D city models can be built in a considerably large area. The 3D spatial information to be built has to provide the latest information that quickly reflects the causes of any change due to urban development. In this study, a UAV photogrammetric method using low cost UAV and digital camera was proposed to acquire and update 3D spatial information effectively on small areas where information continuously change. In the proposed UAV photogrammetric method, the elements of interior orientation were acquired through camera calibration and the vertical and oblique photographs were taken at 9 points and the 3D drawing of ground control points and buildings was performed using 20 images among the pictured images. This study also analyzed the accuracy of the proposed method comparing with ground survey data and digital map in order to examine whether the method can be used in on-demand 3D spatial information update on relatively small areas.

• Ecology and Resilient Infrastructure
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• v.8 no.4
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• pp.253-265
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• 2021

In this study, crop cultivation filed was extracted by using Unmanned Aerial Vehicle (UAV) imagery and deep learning models to overcome the limitations of satellite imagery and to contribute to the technological development of understanding the status of crop cultivation field. The study area was set around Chungbuk Goesan-gun Gammul-myeon Yidam-li and orthogonal images of the area were acquired by using UAV images. In addition, study data for deep learning models was collected by using Farm Map that modified by fieldwork. The Attention U-Net was used as a deep learning model to extract feature of UAV in this study. After the model learning process, the performance evaluation of the model for corn cultivation extraction was performed using non-learning data. We present the model's performance using precision, recall, and F1-score; the metrics show 0.94, 0.96, and 0.92, respectively. This study proved that the method is an effective methodology of extracting corn cultivation field, also presented the potential applicability for other crops.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.2
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• pp.65-81
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• 2019

This study analyzed the relationship of land cover type, urban temperature in Gimhae city, Gyeongsangnam-do, South Korea. Date were used for land cover map, MODIS LST, and detailed temperature data on the Korean Peninsula based on RCP between 2000 and 2010. The correlation between urban area and surface temperature was 0.417, 0.512 for agricultural area and -0.607 for forest area. The correlation between surface temperature and air temperature was 0.301. The relationship with air temperature was analyzed as 0.275 for urban area, agriculture area 0.226, forest area 0.350. Urban and agricultural areas showed increased surface and air temperature as the area increased, while forest areas showed opposite improvements. In structural equation models, urban and agricultural areas had direct effects on the rise of surface temperature, whle forest areas had direct effects on the reduction of air temperature. In the future, it is necessary to use measured temperature data near the surface to understand the relationship between surface temperature and temperature according to the changes in spatial characteristics, which will prepare measures for urban heat island mitigation at the level of urban and environmental planning.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1D
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• pp.145-151
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• 2009

Recently, the rapid development of GIS technology has made it possible to handle a various data associated with spatially hydrological parameters with their attribute information. Therefore, there has been a shift in focus from lumped runoff models to distributed runoff models, as the latter can consider temporal and spatial variations of discharge. This research is to evaluate the feasibility of GIS based distributed model using radar rainfall which can express temporal and spatial distribution in actual dam watershed during flood runoff period. K-DRUM (K-water hydrologic & hydaulic Distributed flood RUnoff Model) which was developed to calculate flood discharge connected to radar rainfall based on long-term runoff model developed by Kyoto- University DPRI (Disaster Prevention Research Institute), and Yondam-Dam watershed ($930km^2$) was applied as study site. Distributed rainfall according to grid resolution was generated by using preprocess program of radar rainfall, from JIN radar. Also, GIS hydrological parameters were extracted from basic GIS data such as DEM, land cover and soil map, and used as input data of distributed model (K-DRUM). Results of this research can provide a base for building of real-time short-term rainfall runoff forecast system according to flash flood in near future.

• Proceedings of the KOSOMBE Conference
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• v.1991 no.05
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• pp.65-70
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• 1991

A hybrid model which uses a probabilistic model and a MLP(multi layer perceptron) model for pattern recognition of EMG(electromyogram) signals is proposed in this paper. MLP model has problems which do not guarantee global minima of error due to learning method and have different approximation grade to bayesian probabilities due to different amounts and quality of training data, the number of hidden layers and hidden nodes, etc. Especially in the case of new test data which exclude design samples, the latter problem produces quite different results. The error probability of probabilistic model is closely related to the estimation error of the parameters used in the model and fidelity of assumtion. Generally, it is impossible to introduce the bayesian classifier to the probabilistic model of EMG signals because of unknown priori probabilities and is estimated by MLE(maximum likelihood estimate). In this paper we propose the method which get the MAP(maximum a posteriori probability) in the probabilistic model by estimating the priori probability distribution which minimize the error probability using the MLP. This method minimize the error probability of the probabilistic model as long as the realization of the MLP is optimal and approximate the minimum of error probability of each class of both models selectively. Alocating the reference coordinate of EMG signal to the outside of the body make it easy to suit to the applications which it is difficult to define and seperate using internal body coordinate. Simulation results show the benefit of the proposed model compared to use the MLP and the probabilistic model seperately.

• Journal of the Korean Society of Systems Engineering
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• v.15 no.2
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• pp.79-86
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• 2019

Among the government-sponsored projects supported by Ministry of SMEs and Startups(MSS), the financial support of the Consulting Research Institutes of our university is scheduled to be ended this year. In this regard, this study is to develop a profit model for R&D center of Consulting Research Institute that can cultivate the financial independence of R&D center of Consulting Research Institutes and foster technology convergence consulting manpower to strengthen the competitiveness of SMEs in preparation for the Fourth Industrial Revolution. The profit model were derived from the current status of consulting industry and similar organizations, the current status of consulting graduate R&D centers, case studies of other universities, and focus group interviews. In order to select three high profit models and commercialize them, BMC (Biz Model Canvas) was used and business feasibility was examined. Therefore, three profit model of R&D center of Consulting Research Institute are: First, SCB (SME's Consulting Business: Total Solution Provider for SMEs through Technology Convergence Consulting), Second, SNB (SME's Network Business: Experts connection in Consulting Graduate School for Solving Problems and Problems of SMEs / Industry Consolidation) And third, SM (Sustainable Management: Financial independence through structural improvement of Consulting Research Institute), and the road-map was established. As an implementation plan, the company intends to seek financial independence by developing a profit model for R&D center of Consulting Research Institutes and by establishing business goals and strategies, manpower operation plan, organization, and investment plan for three years.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.174-179
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• 2017

Soil parameters are required inputs to crop models, which estimate crop yield under a given environment condition. The Korean Soil Information System (KSIS), which provides detailed soil profile record of 390 soil series in the HTML (HyperText Markup Language) format, would be useful to prepare soil input files. Korean Soil Information System Processing Tool (KSISPT) was developed to aid generation of soil input data based on the KSIS database. Java was used to implement the tool that consists of a set of modules for parsing the HTML document of the KSIS, storing data required for preparing soil input file, calculating additional soil parameter, and writing soil input file to a local disk. Using the automated soil data preparation tool, about 940 soil input data were created for the DSSAT model and the ORYZA 2000 model, respectively. In combination with soil series distribution map at 30m resolution, spatial analysis of crop yield could be projected under climate change, which would help the development of adaptation strategies.

• Journal of Korean Society of Transportation
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• v.33 no.3
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• pp.294-303
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• 2015

This paper describes a method that can be used for estimating future carbon emissions and environmental effects. To forecast future land use and transportation changes under various low carbon policies, a DELTA and OmniTRANS combination (a land use-transport integrated model) was applied. Appropriate emission estimation methods and dispersion models were selected and applied in the method. It was designed that the estimated emissions from land use and transportation activity as well as the estimated concentrations of air pollutants and comprehensive air quality index (CAI) are presented on a GIS-based map. The prototype was developed for the city of Suwon and the outcome examples were presented in this paper; it demonstrates what kinds of analysis results are presented in this method. It is expected that the developed method will be very useful for decision makers who want to know the effect of environmental policies in cities.