• Journal of the Korean Geosynthetics Society
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• v.12 no.2
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• pp.67-74
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• 2013

In this study, the prediction of slope hazard probability was performed to the study area located in Hadae-ri, Woochun-myeon, Hoengsung-gun, Gangwon Province around Youngdong express way using the computer program SHAPP ver 1.0 developed by a decision tree model. The soil samples were collected at total 10 points, and soil tests were performed to measure soil properties. The thematic maps of soil properties such as coefficient of permeability and void ratio were made on the basis of soil test results. The slope angle analysis of topography was performed using a digital map. As the prediction result of slope hazard probability, 2,120 cells among total 27,776 cells were predicted to be in the event of slope hazards. Therefore, the predicted area of occurring slope hazards may be $53,000m^2$ because the analyzed cell size was $5m{\times}5m$.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.2
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• pp.128-137
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• 2011

The purpose of the FAPIS(Forest Aerial Photograph Interpretation System) development is to increase accuracy and efficiency of the digital forest cover type mapping for improving conventional analog-based mapping procedures by optimizing work-flow and mapping technology. The database models including digital forest cover type map, aerial photograph, and topographic map were designed for use in this system construction. The interface configured concisely to connect with functions such as search engine, display control, conversion to stereo interpretation mode, modification tools, automation of print layout and database models. It is expected that the standardization methodology based on this system can be applied and extended in making all kinds of digital thematic maps, providing decision-making and information of forest resources.

• The Journal of the Korea Contents Association
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• v.9 no.6
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• pp.436-443
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• 2009

There have been rapid increases to the demands for modeling diverse and complex spatial phenomena and utilizing spatial data through the computer across all the aspects of society. As a result, the importance and utilization of remote sensing and GIS's(geographic information systems) have also increased. It can produce digital data of enormous accuracy and value by incorporating remote sensing images into GIS analysis technology and make various thematic maps by classifying and analyzing land cover. Once such a map is made for the target area, it can easily do modeling and constant monitoring based on the map, revise the database with ease, and thus efficiently update geo-spatial information. Under the goal of analyzing changes to land cover along the road by combining the remote sensing and GIS technology, this study classified land cover from the images of two periods, detected changes to the six classes over ten years, and obtained statistics about the study area's quantitative area changes in order to provide basic decision making data for urban planning and development. By analyzing land use along the road, one can set up plans for the area along the road and the downtown to supplement each other.

• Korean Journal of Remote Sensing
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• v.20 no.6
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• pp.369-382
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• 2004

The purpose of this study is the investigation of applicability of LSMA(Linear Spectral Mixture Analysis) on the geological uses with different radiometric and spatial types of sensor images such as Terra ASTER and LANDSAT 7 ETM+. As for the actual application case, geologic mapping for mineral exploration using ASTER and ETM+ at the Mongolian plateau region was carried out. After the pre-processing such as the geometric corrections and calibration of radiance, 7 endmembers, as spectral classes for geologic rock types, related to spectral signature deviation for the given application was determined by the pre-surveyed geological mapping information and the correlation matrix analysis, and total 20 images of ASTER and ETM+ were used to LSMA processing. As the results, fraction maps showing individual mineral types in the study area are presented. It concluded that this approach based on LSMA using ETM+ and ASTER is regarded as one of the effective schemes for geologic remote sensing.

• 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.

• Korean Journal of Remote Sensing
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• v.24 no.2
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• pp.205-211
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• 2008

The river management in Korea had been focused on line based 2D spatial data for the developing river management application system. In this study, the polygon based 3D spatial data such as aerial photos and satellite images were selected and used through comparing their resolution levels for the river environment management. In addition, 1m detailed DEM (Digital Elevation Model) was constructed to implement the real topography information around river so that the damage area scale could be extracted for flood disaster. Also, the social environment thematic maps such as a cadastral map or land cover map could be used to verify the real damage area scale by overlay analysis on aerial photos or satellite images. The construction of these spatial data makes possible to present the real surface information and extract quantitative analysis to support the scientific decision making for establishing the river management policy. For the further study, the lidar surveying data will be considered as the very useful data by offering the real height information of riverbed as the depth of river so that flood simulation can give more reality.

• Journal of The Geomorphological Association of Korea
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• v.21 no.4
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• pp.133-147
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• 2014

Reducing the range of target landform, is required to save the time and cost before real field survey in the case of inaccessible landform such as talus. In this study, Weight of Evidence modeling, which is a Target-driven spatial analysis statistics methods, has been applied to reduce the field survey range of target landform. In order to apply the Weight of Evidence analysis, a likelihood ratio was calculated on the basis of the result of correlation analysis between geomorphic factors and GIS information after selection of geomorphic factors regarding talus. A best combination, which has the biggest possibility for Talus Potential Index, was found by using SRC and AUC methods after calculating the number of cases for each thematic maps. This combination which includes aspect, geology, slope, land-cover, soil depth and soil drainage factors, showed quite high accuracy by 74.47% indicating the ratio of real existent talus to potential talus distribution.

• Journal of The Geomorphological Association of Korea
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• v.25 no.2
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• pp.1-14
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• 2018

The main objective of this paper is to classify properties of the locational environment for each debris type by calculating likelihood ratio based on the correlation between the distributions for each type of debris landform. A total of 8 thematic maps, like as elevation, slope, aspect, curvature, topographic wetness index (TWI), soil drainage, geology, and landcover including with GIS spatial information generally used in this type of debris landform analysis. The results of this study showed that the block stream had a high likelihood ratio compared to talus in areas with relatively high elevation; and concerning slope, the block stream had a high likelihood ratio in a relatively low region than talus. Concerning aspect, a clear correlation could not be analyzed for each debristype, and concerning curvature, the block stream displayed a developed slope on the more concave valley than the talus. Analysis concerning TWI, the block stream displayed a higher likelihood ratio in wider sections than talus, and concerning soil drainage, the talus and block stream both displayed a high likelihood ratio in regions with well-drained soil. The talus displayed a high likelihood ratio in the order of metamorphic rocks, sedimentary rocks, and granite, while the block stream displayed a high likelihood ratio in the order of volcanic rocks, granite, and sedimentary rocks. In addition, concerning landcover, the likelihood ratio had the most concentrated distributed compared to natural bare land only concerning talus. Based on the likelihood ratio result, it can be used as basic data for extracting the possible areas of distribution for each debris type through the GIS spatial integration method.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.3
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• pp.157-165
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• 2021

Recently, as the spatial resolution of satellite and aerial images has improved, various studies using remotely sensed data with high spatial resolution have been conducted. In particular, since the building extraction is essential for creating digital thematic maps, high accuracy of building extraction result is required. In this manuscript, building extraction models were generated using SegNet, U-Net, FC-DenseNet, and HRNetV2, which are representative semantic segmentation models in deep learning techniques, and then the evaluation of building extraction results was performed. Training dataset for building extraction were generated by using aerial orthophotos including various buildings, and evaluation was conducted in three areas. First, the model performance was evaluated through the region adjacent to the training dataset. In addition, the applicability of the model was evaluated through the region different from the training dataset. As a result, the f1-score of HRNetV2 represented the best values in terms of model performance and applicability. Through this study, the possibility of creating and modifying the building layer in the digital map was confirmed.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1485-1492
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• 2020

It has been more than 20 years since the launch of KOMPSAT-1, and so far, a total of 5 satellites have been successfully launched. Until now, KOMPSAT has been used in various fields, including the production of various thematic maps, land change, environmental analysis, and marine monitoring. Many researchers have conducted research to process, analyze, and utilize KOMPSAT images. According to the national space development plan, the KOMPSAT series will be continuously developed to meet the demand for satellite images at the national level. If the ultimate purpose of satellite development is to utilize acquired images, systematic research to effectively utilize the developed satellites should be followed. This special issue introduces the recently conducted research on the use of KOMPSAT images.