• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.2 no.1
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• pp.1-14
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• 2021

The study has been carried out with an objective to prepare Siberian roe deer habitat potential maps in South Korea based on three geographic information system-based models including frequency ratio (FR) as a bivariate statistical approach as well as convolutional neural network (CNN) and long short-term memory (LSTM) as machine learning algorithms. According to field observations, 741 locations were reported as roe deer's habitat preferences. The dataset were divided with a proportion of 70:30 for constructing models and validation purposes. Through FR model, a total of 10 influential factors were opted for the modelling process, namely altitude, valley depth, slope height, topographic position index (TPI), topographic wetness index (TWI), normalized difference water index, drainage density, road density, radar intensity, and morphological feature. The results of variable importance analysis determined that TPI, TWI, altitude and valley depth have higher impact on predicting. Furthermore, the area under the receiver operating characteristic (ROC) curve was applied to assess the prediction accuracies of three models. The results showed that all the models almost have similar performances, but LSTM model had relatively higher prediction ability in comparison to FR and CNN models with the accuracy of 76% and 73% during the training and validation process. The obtained map of LSTM model was categorized into five classes of potentiality including very low, low, moderate, high and very high with proportions of 19.70%, 19.81%, 19.31%, 19.86%, and 21.31%, respectively. The resultant potential maps may be valuable to monitor and preserve the Siberian roe deer habitats.

• Structural Monitoring and Maintenance
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• v.8 no.4
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• pp.309-328
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• 2021

The objective of this work was to develop a methodology for geodetic monitoring on onshore wind towers, to ascertain the existence of displacements from object points located in the tower and at the foundation's base. The geodesic auscultation was carried out in the Gravatá 01 and 02 wind towers of the Eólica Gravatá wind farm, located in the Brazilian municipality of Gravatá-PE, using a stable Measurement Reference System. To verify the existence of displacements, pins were implanted, with semi-spherical surfaces, at the bases of the towers being monitored, measured by means of high-precision geometric leveling and around the Gravatá 02 tower, concrete landmarks, iron rods and reflective sheets were implanted, observed using geodetic/topographic methods: GNSS survey, transverse with forced centering, three-dimensional irradiation, edge measurement method and trigonometric leveling of unilateral views. It was found that in the Gravatá 02 tower the average rays of the circular sections of the transverse welds (ST) were 1.8431 m ± 0.0005 m (ST01) and 1.6994 m ± 0.0268 m of ST22, where, 01 and 22 represent the serial number of the transverse welds along the tower. The average calculation of the deflection between the coordinates of the center of the circular section of the ST22 and the vertical reference alignment of the ST1 was 0°2'39.22" ± 2.83" in the Northwest direction and an average linear difference of 0.0878 m ± 0.0078 m. The top deflection angle was 0°8'44.88" and a linear difference of ± 0.2590 m, defined from a non-linear function adjusted by Least Squares Method (LSM).

• Ocean and Polar Research
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• v.29 no.4
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• pp.303-310
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• 2007

2-D wavelet analysis is applied to bathymetric data from the KR1 area of Korea Deepsea Mining Area. The wavelet analysis is one of the quantitative methods to analyze the topography. The wavelet allows us to create filters to select for topography in a continuous variety of shapes, sizes, and orientation. The 2-D Linear B-spline filter, 100 BS and 100 NF, is convolved with bathymetric data to identify the location of abyssal hills and abyssal troughs in bathymetry. In addition, the 2-D derivative of Cubic B-spline filter, 60 BS and 60 NF, is applied to bathymetric data to find the slope of abyssal hill in bathymetry. These filters were rotated $5^{\circ}$ counterclockwise from NS to match the dominant orientation of seafloor lineament. Both filters result in good match with abyssal hills, troughs, and slopes. This method can apply to fault, fold, and other lineament structures description with variable size. The result of application shows that wavelet analysis of bathymetric data could be used with fundamental data of geophysical analysis.

• Journal of Korean Society of Forest Science
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• v.86 no.2
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• pp.241-250
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• 1997

The study was conducted to make a map for selecting righteous tree species for each site by digital terrain analysis. We set an algorithmic value for each tree species' characteristics with distribution pattern analysis, and the soil types were digitized from data indicated on soil map. Mean altitude, slope, aspect and micro-topography were estimated from the digital map for each block which had been calculated by regression equations with altitude. The results obtained from the study could be summarized as follows 1. We could develope a method to select righteous tree species for a given site with concern of soil, forest condition and topographic factors on Muju-Gun in Chonbuk province(2,500ha) by the terrain analysis and multi-variate digital map with a personal computer. 2. The brown forest soils were major soil types for the study area, and 29 tree species were occurred with Pinus densiflora as a dominant species. The differences in site condition and soil properties resulted in site quality differences for each tree species. 3. We tried to figure out the accuracy of a basic program(DTM.BAS) enterprised for this study with comparing the mean altitude and aspect calculated from the topographic terrain analysis map and those from surveyed data. The differences between the values were less than 5% which could be accepted as a statistically allowable value for altitude, as well as the values for aspect showed no differences between both the mean altitude and aspect. The result may indicate that the program can be used further in efficiency. 4. From the righteous-site selection map, the 2nd group(R, $B_1$) took the largest area with 46% followed by non-forest area (L) with 23%, the 5th group with 7% and the 4th group with 5%, respectively. The other groups occupied less than 6%. 5. We suggested four types of management tools by silvicultural tree species with considering soil type and topographic conditions.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.2
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• pp.238-243
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• 2007

The TAM(Topographic Attentive Mapping) network neural network model is an especially effective one for pattern analysis. It is composed of of Input layer, category layer, and output layer. Fuzzy rule, lot input and output data are acquired from it. The TAM network with three pruning rules for reducing links and nodes at the layer is called fuzzy TAM network. In this paper, we apply fuzzy TAM network to pattern analysis of leadership type for organizational leader and show its usefulness. Here, criteria of input layer and target value of output layer are the value and leadership related personality type variables of the Egogram and Enneagram, respectively.

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.3
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• pp.63-68
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• 2007

The LRA(Logistic Regression Analysis) conducts a quantitative analysis by collecting a lot of samples and the AHP(Analytic Hierarchy Program) makes use of expert decision influenced by subjective judgment to a certain degree. This study is to suggest a combination method in mapping landslide hazard by giving equal weight for the result of LRA and AHP. Topographic factors(slope, aspect, elevation), soil dram, soil depth and land use were adopted to classify landslide hazard areas. The three methods(LRA, AHP, the combined approach) was applied to a $520km^2$ region located in the middle of South Korea which have occurred 39 landslides during 1999 and 2003. The suggested method showed 58.9% matching rate for the real landslide sites comparing with the classified areas of high-risk landslide While LRA and AHP Showed 46.1% and 48.7% matching rates respectively. Further studies are recommended to find the optimal combining weight of LRA and AHP with more landslide data.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.1
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• pp.86-93
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• 2006

The TAM(Topographic Attentive Mapping) network based on a biologically-motivated neural network model is an especially effective one for pattern analysis. It is composed of of input layer, category layer, and output layer. Fuzzy rule, for input and output data are acquired from it. The TAM network with three pruning rules for reducing links and nodes at the layer is called fuzzy TAM network. In this paper, we apply fuzzy TAM network to pattern analysis of core competency model for subcontractors of construction companies and show its usefulness.

• Journal of Soil and Groundwater Environment
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• v.18 no.4
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• pp.40-49
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• 2013

In the beginning of $20^{th}$ century, the coal mining industry had an important role in Japan at which two-thirds of the coal product came from the Kitakyushu-Chikuho District (KCD). As a consequence of mining activities, land-use condition in this district showed notable changes. This paper presented a study of land-use changes in coal mining area by characterizing land-use pattern transition over the last 100 years. In order to carry out the rigorous analysis of land-use, a series of land-use maps over the last 100 years was developed using geographic information systems (GIS). The historic topographic map and another available old data were used to investigate the long-term changes of land-use associated with past mining within the GIS platform. The results showed that the utilization of a series of developed land-use maps successfully indicated the difference of land-use pattern in the KCD before and after the peak of mining activities. The general findings from land-use analysis described that forest and farm lands were lost and turned into abandoned sites in the last 100 years.

• Journal of the Korean Society of Safety
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• v.31 no.1
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• pp.105-110
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• 2016

Mountainous disasters such as landslides and debris flow are difficult to forecast. Debris flow in particular often flows along the valley until it reaches the road or residential area, causing casualties and huge damages. In this study, the researchers selected Seoraksan National Park area located at Inje County (Inje-gun), Gangwon Province-where many mountainous disasters occur due to localized torrential downpours-for the damage reduction and cause analysis of the area experiencing frequent mountainous disasters every year. Then, the researchers conducted the field study and constructed geospatial information data by GIS method to analyze the characteristics of the disaster-occurring area. Also, to extract more precise geographic parameters, the researchers scanned debris flow triggering area through terrestrial LiDAR and constructed 3D geographical data. LiDAR geographical data was then compared with the existing numerical map to evaluate its precision and made the comparative analysis with the geographic data before and after the disaster occurrence. In the future, it will be utilized as basic data for risk analysis of mountainous disaster or disaster reduction measures through a fine-grid topographical map.

• Ocean Systems Engineering
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• v.8 no.3
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• pp.329-343
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• 2018

The inclination of seabed profile (sloped seabed) is one of the known topographic features which can be observed at different seabed level in the large offshore basin. A mooring system connected between the platform and global seabed is an integral part of the floating structure which tries to keep the floating platform settled in its own position against hostile sea environment. This paper deals with an investigation of the motion responses of an FPSO platform moored on the sloped seabed under the combined action of wave, wind and current loads. A three-dimensional panel discretization method has been used to model the floating body. To introduce the connection of multi-segmented non-linear elastic catenary mooring cables with the sloped seabed, a quasi-static composite catenary model is employed. The model and analysis have been completed by using hydrodynamic diffraction code AQWA. Validation of the numerical model has been successfully carried out with an experimental work published in the latest literature. The analysis procedure in this study has been followed time domain analysis. The study involves an objective oriented investigation on platform motions, in order to identify the effects of the slopped seabed, the action of the wave, wind and current loads and the presence of riser system. In the end, an effective analysis has been performed to identify a stable mooring model in demand of reducing structural responses of the FPSO.