• Journal of Cadastre & Land InformatiX
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• v.47 no.2
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• pp.49-60
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• 2017

Recently, the use of mashup that integrates real-time data with spatial data such as tiled map and satellite imagery has been increased significantly. As the use of mashup has been extended to various fields of O2O, LBS, Smart City, and Autonomous Driving, the performance of mashup has become more important. Therefore, this study aims to compare and analyze the performance of various map platforms, when large amounts of real-time data are integrated with spatial data. Specifically, we compare the performance of most popular map platforms available in Korea, such as Google Maps, OpenStreetMap, Daum Map, Naver Map, olleh Map, and VWorld. We also compare the performance using most common web browsers of Chrome, Firefox and Internet Explorer. In the performance analysis, we measured and compared the initialization time of basic map and the mashup time of real-time data for the above map platforms. From analysis results, we could find that Google Maps, OpenStreetMap, VWorld, and olleh Map platforms showed a better performance than the others.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.11
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• pp.569-584
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• 2016

In this paper, we present a spatial knowledge extractor implemented in Hadoop MapReduce parallel, distributed computing environment. From a large spatial dataset, this knowledge extractor automatically derives a qualitative spatial knowledge base, which consists of both topological and directional relations on pairs of two spatial objects. By using R-tree index and range queries over a distributed spatial data file on HDFS, the MapReduce-enabled spatial knowledge extractor, MRSPAKE, can produce a web-scale spatial knowledge base in highly efficient way. In experiments with the well-known open spatial dataset, Open Street Map (OSM), the proposed web-scale spatial knowledge extractor, MRSPAKE, showed high performance and scalability.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06c
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• pp.255-257
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• 2011

본 연구에서는 각종 웹사이트와 이메일을 통해 전달되는 회의공지에 포함된 회의장소를 나타내는 문자열로부터 실제 위치를 추정하는 시스템을 설계 및 구현하였다. 직접 구현한 NER과 Relation-type Classification 모듈을 사용하였으며, 장소에 대한 모델은 기존의 지리정보시스템들과의 상호 운용성을 위하여 OpenStreetMap[6]과 Geonames[7]의 데이터 구조를 참조하여 설계되었고, 실제 위치를 구하기 위하여 내부자원 외에도, 각종 오픈API들을 외부자원으로 활용하였다.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.10
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• pp.439-446
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• 2015

Recently, semantic trajectories which combine GPS positions and POIs(Point of Interests) become more popular in order to expand location based services. To construct semantic trajectories, the existing algorithms exploit the extent information of POIs described as polygons and find overlapping regions between GPS positions and the extents. However, the algorithms are not applicable in the condition where the extent information is not provided such as in Google Map, Naver Map, OpenStreetMap and most of the open geographic information systems. In this paper, we provide a novel algorithm to construct semantic trajectories only with GPS positions and POI points but without POI extents.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.5
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• pp.431-438
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• 2017

The information management system for urban planning, urban management and related decision making is increasing an importance in recent years. Especially, the information about 3D buildings in urban area is necessary for urban management related precise location based service. However, it takes a lot of time, effort, and costs to produce 3D modeling data of buildings. These problems have been found in many studies, but the research to solve these problems is still necessary. In this study, we have tested an efficient 3D modeling method of building to solve these problems. SketchUp was used to test 3D modeling methods with OSM(OpenStreetMap) data. The other 3D modeling method using a digital map was tested. The 3D modeling of building data was efficient using PlaceMaker, which can use OSM data. In addition, modeling was possible through simple editing of the digital map and automatic building generation. The efficiency of the research results is presented by comparing with the traditional method based on the regulation and the stadard man power issued by Korean government. These two 3D modeling methods of building tested through the study can be used as basic data for related research and work. Additional studies should be conducted to improve the accuracy of the building model and determine how to obtain height data efficiently.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.4
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• pp.745-754
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• 2019

As GeoWeb 2.0 technologies are widely used, various kinds of services that mashup spatial data and user data are being developed. In particular, various spatial information platforms such as Google Maps, OpenStreetMap, Daum Map, Naver Map, olleh Map, and VWorld based on GeoWeb 2.0 technologies support mashup service. The mashup service which is supported through the Open APIs of the platforms, provides various kinds of spatial data such as 2D map, 3D map, and aerial image. Also, application fields using the mashup service are greatly expanded. Recently, as user data for mashup have been greatly increased, there was a problem in mashup performance. However, the research on the mashup performance improvement is currently insufficient, even the research on the mashup performance comparison of various platforms has not been performed. In this paper, we perform comparative analysis of the mashup performance for large amounts of user data and spatial data using various spatial information platforms available in Korea. Specifically, we propose two performance analysis indexes of mashup time and user interaction time in order to analyze the mashup performance efficiently. Also, we implement a system for the performance analysis. Finally, from the performance analysis result, we propose a spatial information platform that can be efficiently applied to cases when user data increases greatly and user interaction occurs frequently.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.599-607
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• 2021

Street-view images, which are omnidirectional scenes centered on a specific location on the road, can provide various obstacle information for the pedestrians. Pedestrian network data for the navigation services should reflect the up-to-date obstacle information to ensure the mobility of pedestrians, including people with disabilities. In this study, the object detection model was trained for the bollard as a major obstacle in Seoul using street-view images and a deep learning algorithm. Also, a process for updating information about the presence and number of bollards as obstacle properties for the crosswalk node through spatial matching between the detected bollards and the pedestrian nodes was proposed. The missing crosswalk information can also be updated concurrently by the proposed process. The proposed approach is appropriate for crowdsourcing data as the model trained using the street-view images can be applied to photos taken with a smartphone while walking. Through additional training with various obstacles captured in the street-view images, it is expected to enable efficient information update about obstacles on the road.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.340-340
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• 2023

최근 전 세계가 극단적 집중호우로 인한 대규모 홍수로 인해 극심한 몸살을 앓고 있다. 특히, 설계빈도를 초과하는 강우로 인해 도시지역에서 발생하는 도시침수는 그 특성상 막대한 인명과 재산상의 피해를 유발하므로 이를 사전에 예방하고 피해를 줄이기 위한 노력이 매우 시급한 실정이다. 도시유역 침수 해석을 위한 수치모의는 대상 유역의 현재 대비 상황을 판단할 수 있을 뿐만 아니라 하수관로 증설 효과 파악, 빗물저류조의 침수저감 효과 분석, 빗물배수펌프장의 적정용량 파악 등에 매우 효율적이다. 정확도 높은 도시침수 해석을 위해서는 고해상도 DEM 또는 DSM 지형자료뿐만 아니라 토지이용도 및 지하에 매설되어 있는 하수관망(하수관로, 맨홀, 배수펌프장 등) 자료의 활용이 필수적이다. 그러나 저개발 국가나 미계측유역의 경우에는 신뢰도 높은 하수관망 자료를 얻기가 매우 어려울 뿐만 아니라 해당 자료가 존재하지 않는 경우도 빈번해 도시침수 해석이 곤란한 경우가 다수 발생한다. 따라서 본 연구에서는 GIS 형태로 제공되는 Open Street Map(OSM)의 도로망 정보를 이용해 가상의 하수관망을 생성하는 방법론을 제시하고 서울시 사당유역을 미계측유역으로 가정해 가상의 하수관망을 생성해 그 적용성을 평가하였다. 본 연구에서 제시된 결과는 하수관망 자료의 획득이 곤란한 지역의 도시침수 예측이나 효과적인 하수관망 설계에 활용될 수 있을 것으로 판단된다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.11-19
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• 2018

Recently, many companies offer various web-based map that is based on GIS(Geographic Information System) information. Google Map, Open street, Bing Map, Naver Map, Daum Map, Vwolrd Map, etc are the few examples of such system. In this paper, we propose a method to visualize ocean forecasting model data considering the flow diagram of tidal current, streamline expression algorithm, and user convenience by using vector field data information that is currently being served. It is confirmed that the proposed method of the flow diagram of tidal current, and stream line expression algorithm is faster than that of conventional ocean prediction model data by more than 2 times.

• Journal of IKEEE
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• v.25 no.4
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• pp.756-761
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• 2021

Dynamic route guidance (DRG) finds the fastest path from a source to a destination location considering the real-time congestion information. In Korea, the traffic state information is available by the public transportation data (PTD) which is indexed on top of the node-link map (NLM). While the NLM is the authoritative low-detailed road network for major roads only, the OpenStreetMap road network (ORN) supports not only a high-detailed road network but also a few open-source routing engines, such as OSRM and Valhalla. In this paper, we propose a DRG framework based on road network matching between the NLM and ORN. This framework regularly retrieves the NLM-indexed PTD to construct a historical speed profile which is then mapped to ORN. Next, we extend the Valhalla routing engine to support dynamic routing based on the historical speed profile. The numerical results at the Yeoui-do island with collected 11-month PTD show that our DRG framework reduces the travel time up to 15.24 % and improves the estimation accuracy of travel time more than 5 times.