• Proceedings of the Korean Geotechical Society Conference
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• 2002.10a
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• pp.499-506
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• 2002

The purpose of this study is to develop landslide susceptibility analysis techniques using artificial neural networks and to apply the newly developed techniques for assessment of landslide susceptibility to the study area of Yongin in Korea. Landslide locations were identified in the study area from interpretation of aerial Photographs and field survey data, and a spatial database of the topography, soil type and timber cover were constructed. The landslide-related factors such as topographic slope, topographic curvature, soil texture, soil drainage, soil effective thickness, timber age, and timber diameter were extracted from the spatial database. Using those factors, landslide susceptibility and weights of each factor were analyzed by two artificial neural network methods. In the first method, the landslide susceptibility index was calculated by the back propagation method, which is a type of artificial neural network method. Then, the susceptibility map was made with a GIS program. The results of the landslide susceptibility analysis were verified using landslide location data. The verification results show satisfactory agreement between the susceptibility index and existing landslide location data. In the second method, weights of each factor were determinated. The weights, relative importance of each factor, were calculated using importance-free characteristics method of artificial neural networks.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.1
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• pp.37-43
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• 2001

Crop status monitoring and yield prediction at higher spatial resolution is a valuable tool in various decision making processes including agricultural policy making by the national and local governments. A prototype crop forecasting system was developed to project the size of rice crop across geographic areas nationwide, based on daily weather pattern. The system consists of crop models and the input data for 1,455 cultivation zone units (the smallest administrative unit of local government in South Korea called "Myun") making up the coterminous South Korea. CERES-rice, a rice crop growth simulation model, was tuned to have genetic characteristics pertinent to domestic cultivars. Daily maximum/minimum temperature, solar radiation, and precipitation surface on 1km by 1km grid spacing were prepared by a spatial interpolation of 63 point observations from the Korea Meteorological Administration network. Spatial mean weather data were derived for each Myun and transformed to the model input format. Soil characteristics and management information at each Myun were available from the Rural Development Administration. The system was applied to the forecasting of national rice production for the recent 3 years (1997 to 1999). The model was run with the past weather data as of September 15 each year, which is about a month earlier than the actual harvest date. Simulated yields of 1,455 Myuns were grouped into 162 counties by acreage-weighted summation to enable the validation, since the official production statistics from the Ministry of Agriculture and Forestry is on the county basis. Forecast yields were less sensitive to the changes in annual climate than the reported yields and there was a relatively weak correlation between the forecast and the reported yields. However, the projected size of rice crop at each county, which was obtained by multiplication of the mean yield with the acreage, was close to the reported production with the $r^2$ values higher than 0.97 in all three years.

• Korean Journal of Remote Sensing
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• v.26 no.3
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• pp.317-324
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• 2010

In recent years, many automatic classification approaches have been employed. An automatic classification method can be effective, time-saving and can produce objective results due to the exclusion of operator intervention. This paper proposes a classification method based on automated training for high resolution multispectral images using ancillary data. Generally, it is problematic to automatically classify high resolution images using ancillary data, because of the scale difference between the high resolution image and the ancillary data. In order to overcome this problem, the proposed method utilizes the classification results of a Landsat image as a medium for automatic classification. For the classification of a Landsat image, a maximum likelihood classification is applied to the image, and the attributes of ancillary data are entered as the training data. In the case of a high resolution image, a K-means clustering algorithm, an unsupervised classification, was conducted and the result was compared to the classification results of the Landsat image. Subsequently, the training data of the high resolution image was automatically extracted using regular rules based on a RELATIONAL matrix that shows the relation between the two results. Finally, a high resolution image was classified and updated using the extracted training data. The proposed method was applied to QuickBird and SPOT-5 images of non-accessible areas. The result showed good performance in accuracy assessments. Therefore, we expect that the method can be effectively used to automatically construct thematic maps for non-accessible areas and update areas that do not have any attributes in geographic information system.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.1
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• pp.12-25
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• 2011

It is needed to preserve good effects and to prevent bad influences on local climate in urban and environmental planning. This study seeks to develop climate analysis maps to provide realistic information considering local air temperature and wind flows. Quantitative analyses are conducted by CAS for the production, transportation, and stagnation of cold air, wind flow and thermal conditions by incorporating GIS analysis on land cover and elevation and meteorological analysis from MetPhoMod - a mesoscale weather model. The CAS helps The easier analysis and assessment of urban development on local climate. It will contribute to the better life of the people in cities by providing better understanding of the local climate to the urban space planners.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.4
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• pp.169-185
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• 2016

Recently mean stand height has been added as new attribute to forest type maps, but it is often too costly and time consuming to manually measure 9,100,000 points from countrywide stereo aerial photos. In addition, tree heights are frequently measured around tombs and forest edges, which are poor representations of the interior tree stand. This work proposes an estimation of mean stand height using an image-based point cloud, which was extracted from stereo aerial photo with FUSION S/W. Then, a digital terrain model was created by filtering the DSM point cloud and subtracting the DTM from DSM, resulting in nDSM, which represents object heights (buildings, trees, etc.). The RMSE was calculated to compare differences in tree heights between those observed and extracted from the nDSM. The resulting RMSE of average total plot height was 0.96 m. Individual tree heights of the whole study site area were extracted using the USDA Forest Service's FUSION S/W. Finally, mean stand height was produced by averaging individual tree heights in a stand polygon of the forest type map. In order to automate the mean stand height extraction using photogrammetric methods, a module was developed as an ArcGIS add-in toolbox.

• Journal of Korean Society of Forest Science
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• v.81 no.4
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• pp.372-382
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• 1992

Recreation planning is essential activity to meet changing demands and to protect the resources. The recreation opportunity specturm(ROS) system is a principal part of a recreational management planning. In this study, the basic concepts and tenets of the ROS system described and reviewed the feasibility of applying to forest recreation planning to the Korean national forest. In Korea, the forest land as a major recreation place has used without the rational planning process. The control for the laissez-faire use on the forest area, the classification of recreational opportunity settings is the most important process and then it make a useful tool for providing proper recreational opportunity and site development guidance. Opportunity settings classification can help maintain diversity and enhance protection of forest resources. It can also improve the quality of recreational experiences and the management action guidances. GIS technology using the ARC/INFO could be useful in current attempts to identify analysis areas for predictive modeling of forest recreation site planning.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.4
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• pp.3-10
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• 2008

Cadastral map is a public book that has been composed by continuous parcel having location, number, classification, boundary and an area based on Cadastral Law. A few years ago, cadastral map had been managed by form drawn on 2 dimension plane paper with 7 regular scales. Recently as computer systems are upgrading, cadastral map was able to have a chance to develope one step. Its type has been remade from raster to vector. In result, the cadastral map of vector type becomes to apply variously. Therefore, digital cadastral map has been ready a system to be use with multi-propose by KLIS(Korean Land Information System). In this research, it concretely want presentation of status using land more than original parcel on basic coordination cadastral map and KLIS(Korean Land Information System). The cadastral map is composed as parcel unit was applied by new presentation technique to "Model Research on One Parcel Presentation Technique for Land Status of Cadastral Map". The function of cadastral map on One Parcel Presentation Technique which is not only location relation of possession right and expression of states using land in 28 classifications demonstrated on the cadastral law but also used as foundation data of GIS construct business is developed by lines and classification of parcel to center around public sites of roads, rails, drains and rivers. especially, this research is composed of technique elevation and development of One Parcel Projection Technique of cadastral map in using object of roads among public sites.

• Journal of Korean Society of Forest Science
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• v.88 no.2
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• pp.157-168
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• 1999

This paper analyzed vegetation and land use classification, slope and permanent preservation and legal reserves on the farm Jangada and Jamaica-Mato Grosso do Sul, Brazil, using satellite image for assisting the planning of planting Eucalyptus spp. This part of the State of Mato Grosso do Sul represents an important geopolitcal area, since it is located on the borders of Bolivia and Paraguay. Also exportation of goods can be achieved through hydrovias extending to Buenos Aires, Argentina-through the Paraguay River. Also there are road and railroad connection which link the soutreastern part of Brazil to the Andean countries. The vegetation map from sheet SF 21-Campo Grande of the RADAMBRASIL Project was used as the basis for the preliminary interpretation of coverage, and complemented by a visit of the field. After the initial interpretation of the image, definition of classes of use and land occupation were made, and files of spectral signatures were created. On the farms Jamaica and Jangada Open Arboreal Savanna and Grass Savanna are the predominant physiognomies occupying 68% of total area. In spite of the results being satisfactory at the present moment, the development of this project should be revised and adjusted based on the evaluations already made, including a greater detailing of environmental components, principally with respect to soil and topography.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.4
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• pp.182-192
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• 2008

In oder to develop a decision supporting system for oil spill response, the prototype of pollution response support system which has integrated oil spill prediction system and pollution risk prediction system has developed for Incheon-Daesan area. Spill prediction system calculates oil spill aspects based on real-time wind data and real-time water flow and the residual volume of spilt oil and spread pattern are calculated considering the characteristic of spilt oil. In this study, real-time data is created from results of real-time meteorological forecasting model(National Institute of Environmental Research) using ftp, real-time tidal currents datasets are built using CHARRY(Current by Harmonic Response to the Reference Yardstick) model and real-time wind-driven currents are calculated applying the correlation function between wind and wind-driven currents. In order to model the feature which is spilt oil spreading according to real-time water flow is weathered, the decrease ratio by oil kinds was used. These real-time data and real-time prediction information have been integrated with ESI(Environmental Sensitivity Index) and response resources and then these are provided using GIS as a whole system to make the response strategy.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.2
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• pp.151-159
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• 2004

The diversity, expansion of human activity and rapid urbanization make modem society to faced with problems like damage of nature and drain of natural resources. Under these circumstances rapid and accurate change detection techniques, which can detect wide range utilization changes, are needed for efficient management and utilization plan of national territory. In this study to perform change detection from remote sensing images, space analysis technique contained in Geographic Information System is applied. And from this technique, the software. that can execute new change detection algorithm, query, inquiry and analysis, is produced. This software is on the basis of graphic user interface and has many functions such as format conversion, grid calculation, statistical processing, display and reference. In this study, simultaneously change detection for multi-temporal satellite images can be performed and integrated one change image about four different periods was produced. Further more software user can acquire land cover change information for an specific area through querying and questioning about yearly changes. Finally making of every application module for change detection into one window based visual basic program, can be produced user convenience and automatic performances.