• Korean Journal of Remote Sensing
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• v.25 no.6
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• pp.559-569
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• 2009

During over decades, metadata on spatial data have been developed, and they have been widely applied at the national and international metadata standards such as file structure, format, and data model. However, in the web 2.0 paradigm toward user participation and openness, sources and contents of geospatial products are also diversified, not being limited to well-organized and structured data sets or databases. Especially, software products in both open source software and commercially packaged software are considered into important resources in the geospatial domain. But there are no reports or studies regarding software metadata from the side of software engineering or information technology, till now. The motivation of this study is based on practical needs to build search engine in the intelligent geospatial web. Brief review on current metadata standards is presented, and necessity for software metadata is discussed as well as related works. Basic elements, initially considered, of software metadata are presented. This work is the first attempt for software metadata, although it just covers geospatial software products. Further practical works to meet industrial demands need to actual applications of software metadata.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.3
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• pp.121-127
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• 2017

Recently, it has been actively Semantic Web studies for 2-dimensional data of the spatial data. 2-dimensional Semantic Web, are fused existing Geospatial Web and the Semantic Web, and integrate with the efficient cooperation of the vast non-spatial information on a variety of geospatial information and general Web, it is possible to provide it is a Web services technology of intelligent geographic information. However, in the research for multi-dimensional data processing, and in those who are missing overall, relevant standards also not been enacted. Therefore, in this paper, by applying a variety of base of the theory and technology related to this to take place the Ontology processing technology, multi-dimensional data processing is possible ontology, question, and suggested the contents of the reasoning. Also, we tried to apply what you have proposed respectively to the multi-dimensional query virtual scenario necessary.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.4
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• pp.125-134
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• 2013

Since 2012, the local autonomous governments, under the recommendations regarding cancellation of local committees directing overly-unexecuted urban planning facilities, have tried to prove validity of such facilities. Factors such as specific standards of cancelation process, will execute policies, diversification of local conditions, connectivity to nearby facilities and possible arise of civil complaints, however, all hinder overly-unexecuted urban planning facilities from getting revitalized. Considering that these unexecuted facilities that local governments have to manage increase in number every year, the burden continuously increases for the governments due to the difficulty of setting aside budget for performing validity checks on such facilities. This research aims to analyze the criteria regarding efficient and systematic method on confirming validity of overly-unexecuted urban planning facilities, to establish into several different processes according to defined categories, and to objectify and quantify such standards. Also, using intelligent spatial information such as digital map, LiDAR data and ortho-images, spatial information analysis method suitable for reassessment was chosen and applied to execute validity analysis regarding overly-unexecuted urban planning facilities.

• Journal of the Korea Society of Computer and Information
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• v.21 no.8
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• pp.49-55
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• 2016

In this study, we proposed the social map system prototype for intelligent crime prevention. For developing the social map system prototype, functional requirements were derived through the analysis of related cases and preceding studies. Derived requirements are providing a variety of map-based safety information, using crowdsourcing data such as SNS, connecting to intelligent CCTV. To satisfy these requirements, the prototype is developed with four main menus: the integrated search menu including social media data, the safety map menu providing a variety of safety and danger information, the community map menu to collect safety and danger information from users, and the CCTV menu providing the link to intelligent CCTV. The social map for intelligent crime prevention in this study is expected to greatly enhance the safety of local community with the provision of prompt response to risk information, safe route, etc. through actual service and user participation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.157-167
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• 2023

The use of big data for transportation often involves using data that includes personal information, such as the driver's driving routes and coordinates. This study explores the creation of a route choice prediction model using a large dataset from mobile navigation apps using federated learning. This privacy-focused method used distributed computing and individual device usage. This study established preprocessing and analysis methods for driver data that can be used in route choice modeling and compared the performance and characteristics of widely used learning methods with federated learning methods. The performance of the model through federated learning did not show significantly superior results compared to previous models, but there was no substantial difference in the prediction accuracy. In conclusion, federated learning-based prediction models can be utilized appropriately in areas sensitive to privacy without requiring relatively high predictive accuracy, such as a driver's preferred route choice.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.3955-3971
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• 2020

Due to the significant increase in the use of autonomous car technology, it is essential to integrate this technology with high-precision digital map data containing more precise and accurate roadway information, as compared to existing conventional map resources, to ensure the safety of self-driving operations. While existing map technologies may assist vehicles in identifying their locations via Global Positioning System, it is however difficult to update the environmental changes of roadways in these maps. Roadway vision algorithms can be useful for building autonomous vehicles that can avoid accidents and detect real-time location changes. We incorporate a hybrid architectural design that combines unsupervised classification of vision data with supervised joint fusion classification to achieve a better noise-resistant algorithm. We identify, via a deep learning approach, an intelligent hybrid fusion algorithm for fusing multimodal vision feature data for roadway classifications and characterize its improvement in accuracy over unsupervised identifications using image processing and supervised vision classifiers. We analyzed over 93,000 vision frame data collected from a test vehicle in real roadways. The performance indicators of the proposed hybrid fusion algorithm are successfully evaluated for the generation of roadway digital maps for autonomous vehicles, with a recall of 0.94, precision of 0.96, and accuracy of 0.92.

• Spatial Information Research
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• v.18 no.5
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• pp.83-92
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• 2010

Recently, as the Geospatial Web is combined with the Semantic Web in order to keep pace with the recent trends of information technology emphasizing interoperability, intelligence and individualization, the Geo Semantic Web was proposed, which is an intelligent geographical information Web service technology that can provide users with suitable information by connecting and integrating various types of spatial information and extensive aspatial information on the Web efficiently. For the Geo Semantic Web service, we need to develop Geo Ontology processing technologies that enable computers to process knowledge and information scattered around in the Web environment automatically. However, standards for Geo Ontology processing technologies have nod been established yet, and standardization organizations and various groups and agencies are conducting relevant studies. This paper analyzed various base theories and technologies related to Geo Ontology and developed a Geo Semantic Web system. The Geo Semantic Web system comprises Query Processing Manager that analyzes and processes Geo Semantic queries and manages sessions, Ontology Manager that generates and queries Geo Ontology and extracts spatial/aspatial data, and Clients. Finally, this paper proved the utility of the Geo Semantic Web system by applying it to a hypothetical scenario where Geo Semantic queries are required.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.1 s.31
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• pp.71-80
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• 2005

Recently, water quality problems are emerging as important social issues since water quality in rivers and lakes are significantly deteriorated. Thus, an accurate prediction system on reservoir water quality is required, as well as an integrated system which can provide a solution for taking away contaminated materials. This research aims to develop an intelligent decision support system, which uses a GIS enabling management and spatial analysis. The developed system is a prototype that can be applied into real spot. This research area includes the following main subjects; system analysis and design, geometry data collection and database implementation, data acquisition and analysis on reservoir water quality, interface design and development GIS, and development of an expert system for water quality forecasting by WASPS.

• Journal of Korean Society for Geospatial Information Science
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• v.12 no.1 s.28
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• pp.45-53
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• 2004

The purpose of this paper is to study a scheme to ITS service which enables the data (spatial, non-spatial and image) sharing among heterogeneous system (various environment) with employing the concept of object orientedness and to show Location Reference Technique of ITS Space DB for interoperability. Data warehouse service, query object service, interface object service, and naming object service have been identified for this. In addition, a metadata management object service and persistent object service based system framework has been devised. The proposed skeletal framework would be expected to be functioning well for ITS data sharing environment and for the interoperability support.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.3 s.37
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• pp.3-11
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• 2006

The need for edge detection about topography data from the high resolution satellite imagery is happening with increasing frequency according to many people utilize the its imagery as various fields recently. Many experts is recognizing of other GIS will make use of the road detection from the high resolution satellite imagery, including ITS (Intelligent Transportation Systems) and urban planning. This paper is comparative analysis of LPF (Low Pass Filtering) and HPF (High Pass Filtering) for roads edge detection from high resolution satellite imagery. As a result, LPF and HPF can be highlight selective pixels at edge area about input data. In case or applying to other techniques such as LPF for the same purpose, they aye more effective for wide road width which often cause the slight distortion of boundary or overall change of brightness values on the whole Image. Whereas, HPF has ability to enhance selectively detailed components in a target image.