• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.302-305
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• 2004

The aim of this study is to apply and crossvalidate a spatial logistic multiple-regression model at Boun, Korea, using a Geographic Information System (GIS). Landslide locations in the Boun area were identified by interpretation of aerial photographs and field surveys. Maps of the topography, soil type, forest cover, geology, and land-use were constructed from a spatial database. The factors that influence landslide occurrence, such as slope, aspect, and curvature of topography, were calculated from the topographic database. Texture, material, drainage, and effective soil thickness were extracted from the soil database, and type, diameter, and density of forest were extracted from the forest database. Lithology was extracted from the geological database and land-use was classified from the Landsat TM image satellite image. Landslide susceptibility was analyzed using landslide-occurrence factors by logistic multiple-regression methods. For validation and cross-validation, the result of the analysis was applied both to the study area, Boun, and another area, Youngin, Korea. The validation and cross-validation results showed satisfactory agreement between the susceptibility map and the existing data with respect to landslide locations. The GIS was used to analyze the vast amount of data efficiently, and statistical programs were used to maintain specificity and accuracy.

• Journal of Forest and Environmental Science
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• v.32 no.4
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• pp.377-383
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• 2016

We obtained a total of 36 GPS coordinates of the seven bat species of Rhinolophus ferrumequinum, Myotis ikonnikovi, M. nattereri, M. petax, Murina ussuriensis, Plecotus auritus, and Pipistrellus abramus. Characteristics of forests (forest type, age class, DBH class and crown density), terrain (aspect, slope and distance from mountain stream) and disturbance factors (distance from human residential areas and distance from cultivated areas) that bats have used as their habitats were revealed from the GIS analysis based on GPS coordinates of the 36 positions that bats were found. The bats-preferred forest type is broad-leaf forests (43%) with the trees of the 2th (31%) and 5th (31%) age class, the trees of sapling (36%) and large DBH class (31%), and sparse crown density (67%). Bats prefer the slop direction of the east (39%), the gradient below $15^{\circ}$ (61%), the ranges within 200 m from the mountain streams (92%), the ranges within 200 m near roads (89%), the ranges of 200-400 m from human residential areas (28%), and the ranges within 200 m from cultivated areas (36%).

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.298-301
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• 2004

The aim of this study is to cross-validate of spatial probability model, artificial neural network at Boun, Korea, using a Geographic Information System (GIS). Landslide locations were identified in the Boun, Janghung and Youngin areas from interpretation of aerial photographs, field surveys, and maps of the topography, soil type, forest cover and land use were constructed to spatial data-sets. The factors that influence landslide occurrence, such as slope, aspect and curvature of topography, were calculated from the topographic database. Topographic type, texture, material, drainage and effective soil thickness were extracted from the soil database, and type, diameter, age and density of forest were extracted from the forest database. Lithology was extracted from the geological database, and land use was classified from the Landsat TM image satellite image. Landslide susceptibility was analyzed using the landslide­occurrence factors by artificial neural network model. For the validation and cross-validation, the result of the analysis was applied to each study areas. The validation and cross-validate results showed satisfactory agreement between the susceptibility map and the existing data on landslide locations.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.256-272
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• 2002

The purpose of this study is to develop landslide susceptibility analysis techniques using artificial neural network and to apply the newly developed techniques to the study area of Boun in Korea. Landslide locations were identified in the study area from interpretation of aerial photographs, field survey data, and a spatial database of the topography, soil type, timber cover, geology and land use. The landslide-related factors (slope, aspect, curvature, topographic type, soil texture, soil material, soil drainage, soil effective thickness, timber type, timber age, and timber diameter, timber density, geology and land use) were extracted from the spatial database. Using those factors, landslide susceptibility was analyzed by artificial neural network methods. For this, the weights of each factor were determinated in 3 cases by the backpropagation method, which is a type of artificial neural network method. Then the landslide susceptibility indexes were calculated and the susceptibility maps were made with a GIS program. The results of the landslide susceptibility maps were verified and compared using landslide location data. A GIS was used to efficiently analyze the vast amount of data, and an artificial neural network was turned out be an effective tool to maintain precision and accuracy.

• Spatial Information Research
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• v.11 no.1
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• pp.23-32
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• 2003

TIN is applied in pondage calculation and topography analysis. And much processing time and storage capacity are needed because TIN contains information as elevation, slope and aspect. In the construction of TIN using contour, weed tolerance that is used for the simplification of line is influenced on the sampling distance of contour. The processing time and storage capacity of TIN are calculated in according to the weed tolerance of various size in this research. And we estimated OEMs standard error that is created from TIN to present reasonable weed tolerance and decided the size of weed tolerance that satisfy DEM standard error. We got TINs weed tolerance that satisfy DEM standard error(5m) was 70m and DEMs resolution is 20m as estimation result.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.15 no.2
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• pp.287-298
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• 1997

The main object of this study was to prove the effectiveness of satellite image data for extraction of the Matsucoccus Thenbergianae Miller ビt Park damaged area. The effectiveness of extraction of damaged area was improved by using the BRCT(Backwards radiance correction transformation) with DEM for normalization of topographic effects. The surface analysis of the extracted damaged area was revealed that the damage was started at south-west slope with the aspect of 7 to 18 degrees, and 50% to 70% of the highest altitude mountains. The direction of damage attached by the Matsucoccus Thunbergianae Miller et Park was able to predict through the analysis of periodical of years' images

• Journal of the Korean Society of Environmental Restoration Technology
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• v.11 no.4
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• pp.91-102
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• 2008

This study was conducted to obtain the basic information about Siberia Musk Deer (Moschus moschiferus), and to establish a conservation area for the replacement of Siberia Musk Deer into Mt. Odea National Park, South Korea. We analyzed the main habitat for Siberia Musk Deer restoration in Mt. Odae National Park, Korea. We recorded Siberia Musk Deers' field signs (i.e., bedding sites, feeding areas, feces and tracks), and habitat variables such as nearest distance to the watercourse, trails, slope, aspect, forest type and land cover etc. from Dec. 2004 to Aug. 2007 in Mt. Jiri, Mt. Seorak, and Demilitarized Zone (DMZ). Rocky areas, ridges, mixed coniferous forest (Red pine and Mongolian oak), southern and southeastern slope, elevation of above 800m, and distance from watercourse shorter than 300m etc. were dominant habitat types of Siberia Musk Deer. Based on the significant habitat types, a proper conservation plan should be prepared for the restoration of habitats in order to reintroduce, and to increase the population of Siberia Musk Deer in Mt. Odea National Park, South Korea. Small population size, and limited ecological data are the major constraints for the establishment of conservation areas. Furthermore, other anthropogenic factors including human activities, poaching, and residential area around the park caused the difficulties to qualify as a conservation area. For the successful establishment of conservation area in the future, it is recommended to conduct a comprehensive ecological research, and to survey human disturbances including their impacts on the habitats of Siberia Musk Deer in the Mt. Odea National Park.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.2
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• pp.97-106
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• 2006

Site index is an essential tool to estimate forest productivity. Generally, a site index equation is developed and used from the relationship between stand age and dominant tree heights. However, there is a limit to the use of the site index equation in the application of variable ages, environmental influence, and estimation of site index for the unstocked forest. Therefore, it has been attempted to develop a new site index equation based on various environmental factors including site, climate, and topographical variables. This study was conducted to develop a site index equation based on the relationship between site index and environmental factors for the species of Pinus koraiensis in Yangpyung-Gun, Gyunggi Province. The influence of climatic factors (temperature and solar irradiation ratio), topographical factors (elevation, slope, ratio of slope to valley and aspect) and soil profiles (soil depth by layer and soil consistency) on site index were evaluated by multiple regression analysis. Five environmental factors were selected in the final site index equation for Pinus koraiensis. The site index equation developed in this study was also verified by three evaluation statistics: model's estimation bias, model's precision, and mean square error of measurement. Based on the site index equation, the number of productive areas for Pinus koraiensis were estimated by applying GIS technique to digitized forest maps. In addition, the distribution of productive areas was compared with the areas of current distribution of Pinus koraiensis. It is expected that the results obtained in this study could provide valuable information about the amount and distribution of productive areas for Pinus koraiensis reforestation.

• Geomechanics and Engineering
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• v.24 no.5
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• pp.407-418
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• 2021

Due to the complexity of the causes of the sliding mass instabilities, landslide susceptibility and hazard evaluation are difficult, but they can be more carefully considered and regionally evaluated by using new programming technologies to minimize the hazard. This study aims to evaluate the landslide hazard zonation in the Tabriz region, Iran. A fuzzy logic-based multi-criteria decision-making method was proposed for susceptibility analysis and preparing the hazard zonation maps implemented in MATLAB programming language and Geographic Information System (GIS) environment. In this study, five main factors have been identified as triggering including climate (i.e., precipitation, temperature), geomorphology (i.e., slope gradient, slope aspect, land cover), tectonic and seismic parameters (i.e., tectonic lineament congestion, distribution of earthquakes, the unsafe radius of main faults, seismicity), geological and hydrological conditions (i.e., drainage patterns, hydraulic gradient, groundwater table depth, weathered geo-materials), and human activities (i.e., distance to roads, distance to the municipal areas) in the study area. The results of analyses are presented as a landslide hazard map which is classified into 5 different sensitive categories (i.e., insignificant to very high potential). Then, landslide susceptibility maps were prepared for the Tabriz region, which is categorized in a high-sensitive area located in the northern parts of the area. Based on these maps, the Bozgoosh-Sahand mountainous belt, Misho-Miro Mountains and western highlands of Jolfa have been delineated as risk-able zones.

• Journal of agriculture & life science
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• v.44 no.4
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• pp.9-20
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• 2010

This study was carried out to analyze the landslide characteristics and forest environment factors on the landslide area of Jeonlabuk-do province in korea. The results obtained from this study were summarized as follows; The total number of landslide occurrence was 182 areas. The average area of landslide scar was $1,859m^2$, average length of the landslides was 139m, average width was 13m. The landslides were highly occurred in igneous rock and coniferous. And also, slope gradient was $21{\sim}30^{\circ}$, aspect was NE, altitude was 401~500m, vertical and cross slope was concave (凹),stream order was 1 order, soil depth was 15m below, landslide type was linear, forest type was artificial. The relationship between landslide area and environmental factors was a positive correlation with cross slope (convex), position (upper), altitude (501m), forest type (coniferous), parent rock (sedimentary rock), D.B.H. (over 17cm), but was negative correlation with slope gradient ($31{\sim}40^{\circ}$), parent rock (igneous rock), D.B.H. (6~16cm).