• Proceedings of the Plant Resources Society of Korea Conference
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• 2018.10a
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• pp.24-24
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• 2018

Degraded plantation forests are increasing because of unfavorable forestry conditions prevailing in Japan, including falling timber prices, increasing operational costs, and aging and declining forestry workforce. To remedy this situation, appropriate management strategy is required. This study introduces the challenges of Odai Town, Mie Prefecture that employed a new management strategy by evaluating site suitability for conifer forests and that proposes a new forest management regime of planting deciduous trees in unsuitable sites. The site suitability for conifer forests was evaluated from two aspects: the natural site conditions and the relationship among site conditions, growth, and damage by Anaglyptus subfasciatus Pic. in Cryptomeria japonica D. Don and Chamaecyparis obtusa Sieb. Et Zucc. forests. By analyzing the relationship among site conditions, growth, and insect damage based on field data obtained in plantation forests, growth evaluation and insect damage evaluation maps were developed. Based on the natural forest investigation, natural site condition maps for C. japonica and C. obtusa were established. Furthermore, by integrating these evaluation maps with the forest road maps showing the accessibility to the forest, the forest management regime for the whole plantation area of Odai Town was established. The forest management regime map indicates the sites suitable for forestry: suitable for long-rotation, short-rotation, and potential sites for short-rotation. The sites unsuitable for forestry were considered to be more suitable for broadleaved forests. Clear-cutting was conducted in a small area and different seral stage saplings (approximately 20 deciduous tree species) suitable to the site conditions were planted in an area of $80-120m^2$ protected by deer-fences. This might establish a forest composed of many species with a multilayer vertical forest structure in a short period. The planted saplings were distributed neither randomly nor uniformly to reflect the natural distribution of trees in the forest. A challenge to develop new products using the deciduous trees has started, such as wood chips for preparing smoked food, essential oil, and deodorizer. As these challenges have just begun, their effects on enhancing sustainable resource management are still being monitored. Even with the challenges, this regime can be of high value as a management strategy to remedy the situation of expansion of degraded forests in Japan.

• 지반과기술
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• v.3 no.3
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• pp.15-22
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• 2006

The optimum blasting pattern to excavate a quarry efficiently and economically can be determined based on the minimum production cost, which is generally estimated according to rock fragmentation. Therefore, it is a critical problem to predict fragment size distribution of blasted rocks over an entire quarry. By comparing various prediction models, it can be ascertained that the result obtained from Kuz-Ram model relatively coincides with that of field measurements. Kuz-Ram model uses the concept of rock factor to signify conditions of rock mass such as block size, rock jointing, strength and others. For the evaluation of total production cost, it is imperative to estimate 3-D spatial distribution of rock factor for the entire quarry. In this study, a sequential indicator simulation technique is adopted for estimation of spatial distribution of rock factor due to its higher reproducibility of spatial variability and distribution models than Kriging methods. Further, this can reduce the uncertainty of predictor using distribution information of sample data. The entire quarry is classified into three types of rock mass and optimum blasting pattern is proposed for each type based on 3-D spatial distribution of rock factor. In addition, plane maps of rock factor distribution for each ground level are provided to estimate production costs for each process and to make a plan for an optimum blasting pattern.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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• pp.5507-5528
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• 2016

In computer vision, salient object is important to extract the useful information of foreground. With active contour analysis acting as the core in this paper, we propose a bottom-up saliency detection algorithm combining with the Bayesian model and the global color distribution. Under the supports of active contour model, a more accurate foreground can be obtained as a foundation for the Bayesian model and the global color distribution. Furthermore, we establish a contour-based selection mechanism to optimize the global-color distribution, which is an effective revising approach for the Bayesian model as well. To obtain an excellent object contour, we firstly intensify the object region in the source gray-scale image by a seed-based method. The final saliency map can be detected after weighting the color distribution to the Bayesian saliency map, after both of the two components are available. The contribution of this paper is that, comparing the Harris-based convex hull algorithm, the active contour can extract a more accurate and non-convex foreground. Moreover, the global color distribution can solve the saliency-scattered drawback of Bayesian model, by the mutual complementation. According to the detected results, the final saliency maps generated with considering the global color distribution and active contour are much-improved.

• Journal of The Korean Astronomical Society
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• v.24 no.1
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• pp.55-70
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• 1991

Infrared emission maps are constructed at 12.5, 25, 60, and $100{\mu}m$ for dark globules B5, B34, B133, B134, B361, L134 and L1523 by using Infrared Astronomical Satellite data base. These clouds are selected on the basis of their appearance in Palomar print as dark obscuring objects with angular sizes in the range of 3 to 30 arcminutes. The short wavelength(12.5 and $25{\mu}m$) maps show the embedded infrared sources. We found many such sources only in B5, B361 and B34 regions, Diffuse component at 12.5 and $25{\mu}m$, possibly arising from the stochastically heated very small dust grains(a < $0.01{\mu}m$) by interstellar radiation field, is found in B361 and L1523 regions. Such emission is characterized by the limb brightening, and it is confirmed in L1523 and in B361. Infrared emissions at the long wavelengths(60 and $100{\mu}m$) are due to colder dusts with temperature less than 20 K. The distribution of color index determined by the ratio 60 to $100{\mu}m$ intensities shows monotonic decrease of dust temperature toward the center. The black body temperature determined from these ratios is found to lie between 16 and 23 K. Such temperature is possible for small(i.e., $a\;{\lesssim}\;0.01{\mu}m$) graphite grains if the grains are mainly heated by interstellar radiation field. Thus IRAS 100 and $60{\mu}m$ emissions are arising mainly from small grains in the colud. The distribution of such dust grains implied from the emissivity distributions at 100 and $60{\mu}m$ resembles that of isothermal sphere. This contrasts to earlier findings of much steeper distribution of dusts contributing visible extinction. These dust grains are mainly larger ones(i.e., $a{\simeq}0.1{\mu}m$). Therefore we conclude that the average grain size increase, toward the cloud center.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.4 no.4
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• pp.159-176
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• 2023

The conservation of the raccoon dog (Nyctereutes procyonoides) in South Korea requires the protection and preservation of natural habitats while additionally ensuring coexistence with human activities. Applying habitat map modeling techniques provides information regarding the distributional patterns of raccoon dogs and assists in the development of future conservation strategies. The purpose of this study is to generate potential habitat distribution maps for the raccoon dog in South Korea using geospatial technology-based models. These models include the frequency ratio (FR) as a bivariate statistical approach, the group method of data handling (GMDH) as a machine learning algorithm, and convolutional neural network (CNN) and long short-term memory (LSTM) as deep learning algorithms. Moreover, the imperialist competitive algorithm (ICA) is used to fine-tune the hyperparameters of the machine learning and deep learning models. Moreover, there are 14 habitat characteristics used for developing the models: elevation, slope, valley depth, topographic wetness index, terrain roughness index, slope height, surface area, slope length and steepness factor (LS factor), normalized difference vegetation index, normalized difference water index, distance to drainage, distance to roads, drainage density, and morphometric features. The accuracy of prediction is evaluated using the area under the receiver operating characteristic curve. The results indicate comparable performances of all models. However, the CNN demonstrates superior capacity for prediction, achieving accuracies of 76.3% and 75.7% for the training and validation processes, respectively. The maps of potential habitat distribution are generated for five different levels of potentiality: very low, low, moderate, high, and very high.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.374-377
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• 2005

The distribution and changes of tropospheric nitrogen dioxide ($NO_2$) are analyzed using the satellite measurements data from GOME (Global Ozone Monitoring Experiment) and SCIMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY). We produced global maps of tropospheric $NO_2$ for 4 seasons using GOME measurements from January 1997 to June 2003. The global distribution shows high values in regions with dense population and high industrialization. Tropospheric $NO_2$ shows obvious seasonal changes depending on its emission and lifetime. Based on the good agreement between two instruments in the time period of overlapping measurements (January 2003-June2003), we linked SClAMACHY data to the GOME time series. The combined time series over the past decade indicate that $NO_2$ 1evels over China are rapidly increasing while those over Europe are decreasing. We also discussed potential application of spaceborne instruments in detecting and characterizing long-distance transport of $NO_2$.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2003.10a
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• pp.443-446
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• 2003

This study was conducted to draw design rainfall for the regional design rainfall derived by the optimal distribution and method of frequency analysis. The design rainfalls were calculated by the regional and at-site analysis for Log-Pearson type III and GEV distributions and were compared with Relative efficiency(RE) which is ratio of Relative root-mean-square error(RRMSE) by the regional and at-site analysis for Log-Pearson type III and GEV distributions. Consequently, optimal design rainfalls following the regions and consecutive durations were derived by the regional frequency analysis for GEV distribution and design rainfall maps were drawn by GIS techniques.

• Journal of the Earthquake Engineering Society of Korea
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• v.19 no.3
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• pp.93-102
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• 2015

This study evaluates collapse probabilities of structures which are designed according to a domestic seismic design code, KBC2009. In evaluating their collapse probabilities, to do this, probabilistic distribution models for seismic hazard and structural capacity are required. In this paper, eight major cities in Korea are selected and the demand probabilistic distribution of each city is obtained from the uniform seismic hazard. The probabilistic distribution for the structural capacity is assumed to follow a underlying design philosophy implicitly defined in ASCE 7-10. With the assumptions, the structural collapse probability in 50 years is evaluated based on the concept of a risk integral. This paper then defines an mean value of the collapse probabilities in 50 years of the selected major cities as the target risk. Risk-targeted spectral accelerations are finally suggested by modifying a current mapped spectral acceleration to meet the target risk.

• Tunnel and Underground Space
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• v.12 no.3
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• pp.198-209
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• 2002

To assess deep geological environment for the research and development of hish-level radioactive waste disposal, six boreholes of 3" in diameter were installed in two granitic areas. An areal extent of the rock block scale in the study sites was estimated by the lineament analysis from satellite images and shaded relief maps. The characterization of fracture system developed in rock block scale was carried out based on the acoustic televiewer logging in deep boreholes. In the Yuseong site, the granite rock mass was divided into the upper and lower zones at around -160m based on the probabilistic distribution characteristics of the geometric parameters such as orientation, fracture frequency, spacing and aperture size. Since the groundwater flow is dependent on the fracture system in a fractured rock mass, the correlation of the fracture frequency and cumulative aperture size to the hydraulic conductivity was also discussed.

• Journal of Ecology and Environment
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• v.37 no.2
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• pp.53-60
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• 2014

The arctic tundra is an important ecosystem in terms of the organic carbon cycle and climate change, and therefore, detailed analysis of vegetation distribution patterns is required to determine their association. We used grid-sampling method and applied geostatistics to analyze spatial variability and patterns of vegetation within a two-dimensional space, and calculated the Moran's I statistics and semivariance to assess the spatial autocorrelation of vegetation. Spatially autocorrelated vegetation consisted of moss, Eriophorum vaginatum, Betula nana, and Rubus chamaemorus. Interpolation maps and cross-correlograms revealed spatial specificity of Carex aquatilis and a strong negative spatial correlation between E. vaginatum and C. aquatilis. These results suggest differences between the species in water requirements for survival in the arctic tundra. Geostatistical methods could offer valuable information for identifying the vegetation spatial distribution.