UAV(Unmanned Aerial vehicle) could be effectively applied in a field of land monitoring for analyzing disaster area and mapping, because it can quickly acquire image data at low costs. For this reason, we reviewed the legal system related to mapping, and proposed suggestions for improving in legal system, due to introducing the UAV to Korean land-monitoring through this paper. Also, we evaluated spatial and time accuracy of the digital map, which are generated from UAV images that were taken for occasional map updates and disaster detections. As a result, the mean error is about 10m if only GPS/INS data used, while using GCP(Ground Control Points) it is about 10cm. Therefore, we conclude that the UAV could be effective method in korea land-monitoring field This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http:// creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Road signs are important infrastructures for safe and smooth traffic by providing useful information to drivers. It is necessary to establish road sign DB for managing road signs systematically. To provide such DB, manually detection and recognition from imagery can be done. However, it is time and cost consuming. In this study, we proposed algorithms for automatic recognition of direction information in road sign image. Also we developed algorithm code using OpenCV library, and applied it to road sign image. To automatically detect and recognize direction information, we developed program which is composed of various modules such as image enhancement, image binarization, arrow region extraction, interesting point extraction, and template image matching. As a result, we can confirm the possibility of automatic recognition of direction information in road sign image.
In this study, we investigated the landslides area which occurred in Umyeonsan in 2011 and collected landslide location data. Using this field data with aerial photos and LiDAR data which is obtained before and after disaster event, we analyzed the landslide occurrence frequency per unit area about various topographic characteristics. In case of slope, we compared two kind of slopes which are calculated with Neighborhood algorithm and maximum slope algorithm. Also we used aspect, elevation, profile curvature and planform curvature in topographic analysis of landslide occurrence locations. As a result, the region of which maximum slope is 40°-45° is relatively hazardous in landslide. If the perpendicular surface to the direction of the maximum slope is concave, it is more hazardous than other case. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http:// creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Debris flows are rapidly flowing masses of water mixed with soil and gravel from landslides which are caused by typhoons or rainstorms. The combination of Korea's mountain dominated topography (70%) and seasonal heavy rains and typhoons causes landslides and large-scale debris flows from June to August. These phenomena often cause property damage and casualties that amount up to 20% of total annual disaster fatalities. The key point to predicting debris flow is to understand its movement mechanism, erosion, and deposition. In order to achieve a more accurate estimation of debris flow path and damage, this study incorporates quantitative analysis of high resolution LiDAR DEM (GSD 10cm) to delineate geomorphic and topographic changes induced by Jinbu real scale debris flow test. 2) Department of Civil Engineering, Gangneung-Wonju National University (E-mail: swl@gwnu.ac.kr) 3) Department of Civil Engineering, Gangneung-Wonju National University (E-mail: paik@gwnu.ac.kr) 4) Department of Civil Engineering, Gangneung-Wonju National University (E-mail: yune@gwnu.ac.kr) 5) Corresponding Author, Member, Department of Civil Engineering, Gangneung-Wonju National University (E-mail: ghkim@gwnu.ac.kr) This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http:// creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Korea has been continuously affected by landslides, as 70% of the land is covered by mountains and most of annual rainfall concentrates between June and September. Recently, abrupt climate change affects the increase of landslide occurrence. Gangwon region is especially suffered by landslide damages, because the most of the part is mountainous, steep, and having shallow soil. In this study, a landslide risk assessment model was developed by applying logistic regression to the various data of Duksan-ri, Inje-eup, Inje-gun, Gangwon-do, which has suffered massive landslide triggered by heavy rain in July 2006. The information collected from field investigation and aerial photos right after the landslide of study area were stored in GIS DB for analysis. Slope gradient entered in two ways-as categorical variable and as linear variable. Error matrix for each case was made, and developed model showed the classification accuracy of 81.4% and 81.9%, respectively.
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