• Proceedings of the KSRS Conference
• /
• 2002.10a
• /
• pp.34-39
• /
• 2002

Road information is very important for topographic mapping, transportation application, urban planning and other related application fields. Therefore, automatic detection of road networks from spatial imagery, such as aerial photos and satellite imagery can play a central role in road information acquisition. In this paper, we use least squares correlation matching alone for road center tracking and show that it works. We assumed that (bright) road centerlines would be visible in the image. We further assumed that within a same road segment, there would be only small differences in brightness values. This algorithm works by defining a template around a user-given input point, which shall lie on a road centerline, and then by matching the template against the image along the orientation of the road under consideration. Once matching succeeds, new match proceeds by shifting a matched target window further along road orientation at the target window. By repeating the process above, we obtain a series of points, which lie on a road centerline successively. A 1m resolution IKONOS images over Seoul and Daejeon were used for tests. The results showed that this algorithm could extract road centerlines in any orientation and help in fast and exact he ad-up digitization/vectorization of cartographic images.

• International Journal of Highway Engineering
• /
• v.8 no.1 s.27
• /
• pp.65-75
• /
• 2006

According to development of computer technology, the utilization of the fourth generation of digital photogrammetry progresses favorable. Especially the method of using digital video camera is very practicable and has an advantage such as a profitability for the amateur. In road field which if centrical facilities of national industry, this method was utilized to acquire road information for the safety diagnosis or maintenance. In this study, 3-dimensional position information of road centerline was extracted using digital video camera which has practicality and economical efficiency. This data could be a basic source in road information project.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.8 no.4
• /
• pp.44-51
• /
• 2005

In this study, the method of extracting road centerline's coordinate and road facilities is presented using RC helicopter photogrammetry system. From the survey of extracted road centerline, the errors turned out to be -0.117m ~ 0.103m on the X-axis and -0.014m ~ 0.009m on the Y-axis when RC Helicopter photogrammetry system utilized. By application of this system, hereafter, not only management of road facilities but also construction of DB would be enable which need positioning and design of alignment on the access is not easy area such as traffic congestion or toparchy area.

• International Journal of Highway Engineering
• /
• v.14 no.1
• /
• pp.1-8
• /
• 2012

The horizontal alignment of road is deeply related with the stability of the road and traffic capacity. It is necessary to analyze horizontal alignment of road accurately for efficient maintenance of the road and relevance judgment about the standard. Recently the study on horizontal alignment of road using Lidar data and GPS was concluded, but they were many problem analyzing horizontal alignment radius of curvature in wide area. In this study, the tool which the radius of curvature can evaluate the suitability about "Rules about the Road Structure & Facilities Standards" by using center lines of the road of the digital map tries to implement on GIS. The interface was designed and implemented which can automatically estimate the Road Centerline Horizontal Alignment by using $ESRI^{(R)}$ $ArcObject^{TM}$.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
• /
• 2007.04a
• /
• pp.471-474
• /
• 2007

On the road, geometric structure such as horizontal alignment, vortical alignment and crossing inclination ate important to explain characteristics of road and safety analysis. Especially, horizontal and vortical alignment are have to do with safety of covering. In existing road, for the safety analysis or alignment improvement and expansion pavement, it needs alignment factor of road. Alignment factor of road can be acquired by design drawing. But, design drawing can be not exist because of rack of facility management and national policy that centered to construction. And also, existing design drawing have a lot of differences in comparison with another existing design drawing cause of alignment improvement. In this case, for the precise analysis of alignment, 3-dimensional location information on the road centerline and acquisition of location information which related geometric structure are must to be preceded. In this study, therefore, it provide alignment factors which needed to alignment improvement and road safety analysis by acquisition of road space information and extraction of road centerline data using LiDAR data.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.1249-1251
• /
• 2003

In this paper, a framework for creating road network from road edges is proposed. The present framework mainly includes two modules: road modeler and network generator. Road modeler creates the road polygons from the original road edges, and network generator performs converting road polygons to road network with good connectivity at all intersections. A prototype system is also built, and some experimental results are also presented to demonstrate the effectiveness of the proposed framework.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.36 no.5
• /
• pp.335-341
• /
• 2018

The KDE (Kernel Density Estimation) technique in GIS (Geographic Information System) has been widely used as a method for determining whether a phenomenon occurring in space forms clusters. Most human-generated events such as traffic accidents and retail stores are distributed according to a road network. Even if events on forward and rear roads have short Euclidean distances, network distances may increase and the correlation between them may be low. Therefore, the NKDE (Network-based KDE) technique has been proposed and applied to the urban space where a road network has been developed. KDE is being studied in the field of business GIS, but there is a limit to the microscopic analysis of economic activity along a road. In this study, the NKDE technique is applied to the analysis of urban phenomena such as the density of shops rather than traffic accidents that occur on roads. The results of the NKDE technique are also compared to pedestrian networks and road centerline networks. The results show that applying NKDE to microscopic trade area analysis can yield relatively accurate results. In addition, it was found that pedestrian network data that can consider the movement of actual pedestrians are necessary for accurate trade area analysis using NKDE.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.30 no.4
• /
• pp.379-388
• /
• 2012

The Road Name Address system has begun to be applied and widely used since 2011. However, the Digital Map, or the national representative basic map, has no reference to the Road Name Address system. It causes some difficulties to use the Digital Map under the Road Name Address system. In this paper, we suggest a method for generating the expanded Digital Map by adding information about Road Name Address system into the objects of the Digital Map. First, object matching pairs between the road section layer from the Road Name Address Map and the road centerline layer from the Digital Map are found. Then attributes to be copied from the Road Name Address map to the Digital Map are extracted by comparing their attribute tables. Finally the extracted attributes are copied from the Road Name Address Map to the Digital Map. The expanded road centerline layer of the Digital Map then has attributes about road name according to the Road Name Address system, so that the georeferencing of the Digital Map according to the Road Name Address system becomes possible.

• Proceedings of the KSR Conference
• /
• 2011.10a
• /
• pp.51-56
• /
• 2011

The train travels on the track and, thus, the rear wheels precisely follow the paths of the front wheels. On the contrary, in the vehicles running on the road like automobiles, buses and trucks, the front wheels try to drag the rear ones toward them and across the inside of the curve. Off-tracking is defined as the radial offset between the path of the centerline of the front axle and the path of the centerline of the following axle. In the case of the bimodal tram with AWS(all wheel steering), the off-tracking decrease but the rear swing-out values increase because of the rear steering at the reverse phase angle. Thus, in order to determine the swept path width, maximum road width at the minimum turning radius, off-tracking and swing-out should be considered for the bimodal tram. In this paper, trajectory simulations were carried out for the various condition such as front steering, front and rear steering and suppression of swing-out to optimize the swept path width.

• Journal of Cadastre & Land InformatiX
• /
• v.44 no.1
• /
• pp.127-138
• /
• 2014

It can be effective to extract and apply the updated information from the newly updated map data for updating road data of topographic map. In this study, update target data and update reference data are overlaid and the update objects are explored using network matching technique. And the network objects are classified into five matching and update cases and the update processes for each case are applied to the test data. For this study, road centerline data of digital topographic map is used as an update target data and road data of Korean Address Information System is used as an update reference data. The buffer-based network matching method is applied to the two data and the matching and update cases are classified after calculating the overlaid ratio of length. The newly updated road centerline data of digital topographic map is generated from the application of update process for each case. As a result, the update information can be extracted from the different map dataset and applied to the road network data updating.