• Spatial Information Research
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• v.13 no.4 s.35
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• pp.373-380
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• 2005

Mobile Mapping Systems are effective systems to acquire the position and image data using vehicle equipped with the GPS (Global Positioning System), IMU (Inertial Measurement Unit), and CCD camera. They are used in various fields of road facility management, map update, and etc. In the general photogrammetry such as aerial photogrammetry, GCP (Ground Control Point)s are needed to compute the image exterior orientation elements (the position and attitude of camera). These points are measured by field survey at the time of data acquisition. But it costs much time and money. Moreover, it is not possible to make sufficient GCP as much as we want. However Mobile Mapping Systems are more efficient both in time and money because they can obtain the position and attitude of camera at the time of photographing. That is, Image Orientation Technique must use GCP to compute the image exterior orientation elements, but on the other hand Direct Georeferencing can directly compute the image exterior orientation elements by GPS/INS. In this paper, we analyze about the positional accuracy comparison of ground point using the Image Orientation Technique and Direct Georeferencing Technique.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.1
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• pp.9-21
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• 2009

This study presents a useful heuristic algorithm to classify vehicle classes using vehicle length information, which is extracted from inductive loop vehicle signatures. A high-speed scanning equipment was used to extract more detailed change of inductance magnitude for individual vehicles. Vehicle detection time and individual vehicle speeds were used to derive vehicle length information that is an input of the proposed algorithm. The spatial and temporal transferability tests were further conducted to evaluate algorithm. The spatial and temporal transferability tests were further conducted to evaluate algorithm performance more systematically. It is expected that the proposed method would be useful for obtaining vehicle classification information from wide-spread existing loop infrastructure.

• Journal of the Korean association of regional geographers
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• v.14 no.6
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• pp.718-735
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• 2008

Park-and- Rides are intermodal transfer facilities providing a staging location for travellers to transfer between transportation modes. They are an alternative to alleviate transportation problems such as traffic congestion and air pollution in metropolitan areas. Siting Park-and-Ride facilities belongs to a kind of multi-criteria spatial decision making problems being associated with a combination of various location factors. The purpose of this paper is to provide a method and procedure to evaluate the location suitability of Park-and-Ride facilities using GIS(Geographic Information Systems). Using GIS-based suitability analysis, land value, landuse, road accessibility, public transportation accessibility, possibility to intercept automobile trips, distance to activity center and competition with existing facilities were evaluated as location factors. The suitabilities of individual factors were combined to produce a composite map with a specific weight scheme. Then a given number of sites with high suitability score were selected as potential facility locations and their demand were evaluated based on a commutershed with parabolic shape. The suggested method and procedure will provide useful information in determining Park-and-Ride sites and designing their structure.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.4 s.38
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• pp.61-70
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• 2006

This paper presents photogrammetric processing to generate digital elevation models using SPOT-5 HRG stereo images and deals with the accuracy potential of HRG (High Resolution Geometry) supermode imagery for DEM generation. After bundle adjustment was preformed for sensor modelling, digital surface models were generated through the procedures of Epipolar image resampling and image matching. The DEM extracted from HRG imagery was compared along several test sections with the the refernce DEM which was obtained from the digital topographic maps of a scale of 1 to 5000. The ratio of the zone with DEM errors less than 5m to the whole zone was 53.8%, and about 2.5m RMSE was showed when assuming that the zones larger than 5m were affected by clouds, water bodies and buildings and excluding those zones from accuracy evaluation. In addition, the three-dimensional bird's eye view model and 3D building model were producted based on the DSM which was extracted from SPOT-5 HRG data.

• Journal of Korea Spatial Information System Society
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• v.10 no.2
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• pp.13-24
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• 2008

A next generation video based car navigation is researched to supplement the drawbacks of existed 2D based navigation and to provide the various services for safety driving. The components of this navigation system could be a load object database, identification module for load lines, and crossroad identification module, etc. In this paper, we proposed the traffic lights and road sign recognition method which can be effectively exploited for crossroad recognition in video-based car navigation systems. The method uses object color information and other spatial features in the video image. The results show average 90% recognition rate from 30m to 60m distance for traffic lights and 97% at 40-90m distance for load sign. The algorithm also achieves 46msec/frame processing time which also indicates the appropriateness of the algorithm in real-time processing.

• Journal of the Korean Society for information Management
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• v.29 no.1
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• pp.135-156
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• 2012

The purpose of this study is to ascertain librarian's perceptions on their users' library access and its patterns. Interviews with seven library staff reveal physical accessibility issues including spatial relationships between libraries and other facilities such as shopping malls and schools, travel distance, transportation mode, and temporal perspectives of library access. The results from the interviews corroborate the findings from secondary analysis using household travel data. However, interviewees do not have a clear picture of how much their users travel and spend to access their libraries. This is true, even though these factors are critical to analyze physical accessibility. Based on the findings, this study makes recommendations to improve the accessibility of public libraries. Suggestions include the concept of sponsorships with other facilities, the placing of material drop-boxes on the main route, and providing library programs during lunch time.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.3
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• pp.33-40
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• 2011

This paper presents the prediction and evaluation of landslide using LRA(logistic regression analysis) and ANN (Artificial Neural Network) methods. In order to assess the landslide, we selected Sarabong, Byeoldobong area and Mt. Song-ak in Jeju Island. Five factors which affect the landslide were selected as: slope angle, elevation, porosity, dry density, permeability. So as to predict and evaluate the landslide, firstly the weight value of each factor was analyzed by LRA(logistic regression analysis) and ANN(Artificial Neural Network) methods. Then we got two prediction maps using AcrView software through GIS(Geographic Information System) method. The comparative analysis reveals that the slope angle and porosity play important roles in landslide. Prediction map generated by LRA method is more accurate than ANN method in Jeju. From the prediction map, we found that the most dangerous area is distributed around the road and path.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.3
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• pp.29-34
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• 2008

Demand for car navigation systems has been an explosive increase because of prevalence of owner-drivers, spare time spread, and so on. In addition, car navigation systems are achieving a rapid growth to be the important part of telematics industry with services such as real-time traffic information and DMB(Digital Multimedia Broadcasting). The network data, one of the composition components in car navigation systems, is most important component because that is abstract of real world road network and base data in pathfinding. However most of the car navigation systems have been stand-alone system. Thus user's network data becomes outdated according to the time passing and does not reflect the change of road information in real world. To overcome this problem, users have to update network data in car navigation systems periodically. This method is quite cumbersome process. For this reason, this study proposed a new update method to serve the difference network data on user's device and the real world in real time, and simulated to verify.

• Journal of Korean Society for Geospatial Information Science
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• v.10 no.1 s.19
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• pp.59-66
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• 2002

The rapid change of industrial structure causes to increase distribution cost and requires necessity of physical distribution system urgently. Traffic situation is getting extremely worse and traffic jam has led to increasing expense of physical distribution delivery which dominates 20% of distribution cost. In this situation, the shortest and most suitable path search system is required by modern people who must waste a lot of time for moving with a car or on the street as well as many companies. for these reasons, we developed the shortest-path-searching system applying the dijkstra algorithm which is one of the effective shortest path algorithm to GIS, and it was constructed by considering realistic urban traffic and the pattern of street in a physical situation. Also, this system was developed to be updated weight data automatically, considering the dynamic change of traffic situation such as a traffic information service which will be served in real time. Finally, we designed this system to serve on web by using MapObjects IMS.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.352-357
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• 2006

매년 도로와 주차공간의 확장보다 차량의 수가 빠르게 증가하여 그에 따라 불법 주차 관리의 어려움이 증가하고 있다. 이러한 문제점을 해결하기 위해 지능형 주차 관리 시스템이 필요하게 되었다. 본 논문에서는 획득된 차량 영상에서 수직 에지의 특징을 이용하여 번호판 영역과 개별 코드를 추출하고, 추출된 개별 코드를 퍼지 신경망 알고리즘을 제안하여 학습 및 인식한다. 본 논문에서는 차량 번호판 영역을 검출하기 위해 프리윗 마스크를 적용하여 수직 에지를 찾고, 차량 번호판의 정보를 이용하여 잡음을 제거한 후에 차량 번호판 영역을 추출한다. 추출된 차량 번호판 영역은 반복 이진화방법을 적용하여 이진화하고, 이진화된 차량 번호판 영역에 대해서 수직 분포도와 수평 분포도를 이용하여 번호판의 개별 코드를 추출한다 추출된 개별 코드는 제안된 퍼지 신경망 알고리즘을 적용하여 인식한다. 제안된 퍼지 신경망은 입력층과 중간층간의 학습 구조로는 FCM 알고리즘을 적용하고 중간층과 출력층간의 학습 구조는 Max_Min 신경망을 적용한다. 제안된 방법의 추출 및 인식 성능을 평가하기 위하여 실제 차량 영상 150장을 대상으로 실험한 결과, 기존의 차량 번호판 인식 방법보다 효율적이고 인식 성능이 개선된 것을 확인하였다.