• Journal of Korea Multimedia Society
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• v.22 no.12
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• pp.1466-1480
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• 2019

This paper addresses the efficient processing of all-farthest-neighbors (AFN) queries in spatial network databases. Given a set of data points P={p₁,p₂,…,p_|p|} in a spatial network, where the distance between two data points p and s, denoted by dist (p,s), is the length of the shortest path between them, an AFN query is defined as follows: find the farthest neighbor ω(p)∈P of each data point p such that dist(p,ω(p)) ≥ dist(p,s) for all s∈P. In this paper, we propose a shared execution algorithm called FAST (for All-Farthest-neighbors Search in spatial neTworks). Extensive experiments on real-world roadmaps confirm the efficiency and scalability of the FAST algorithm, while demonstrating a speedup of up to two orders of magnitude over a conventional solution.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.2
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• pp.23-32
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• 2004

The query optimizer's important task while a query is invoked is to estimate the fraction of records in the databases that satisfy the given query condition. The query result size estimation in spatial databases, like relational databases, proceeds to partition the whole input into a small number of subsets called “buckets” and then estimate the fraction of the input in the buckets. The accuracy of estimation is determined by the difference between the real data counts and approximations in the buckets, and is dependent on how to partition the buckets. Existing techniques for spatial databases are equi-area and equi-count techniques, which are respectively analogous in relation databases to equi-height histogram that divides the input value range into buckets of equal size and equi-depth histogram that is equal to the number of records within each bucket. In this paper we propose a new partitioning technique that determines buckets according to the maximal difference of area which is defined as the product of data ranges End frequencies of input. In this new technique we consider both data values and frequencies of input data simultaneously, and thus achieve substantial improvements in accuracy over existing approaches. We present a detailed experimental study of the accuracy of query result size estimation comparing the proposed technique and the existing techniques using synthetic as well as real-life datasets. Experiments confirm that our proposed techniques offer better accuracy in query result size estimation than the existing techniques for space query size, bucket number, data number and data size.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.10a
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• pp.27-40
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• 2004

When we derive multi-scale databases from a source spatial database, thegeometries and topological relations in the source database are transformed according to a predefined set of constraints. This means that the derived databases should be checked to see if the constraints are respected during the construction or updates of databases and to maintain the consistency of multi-scale databases. In this paper, we focus on the topological consistency between the source and derived databases, which is one of the important constraints to respect. In particular, we deal with the method of assessment of topological consistency, when 2-dimensional objects are collapsed to 1-dimensional ones. We introduce eight types of topological relations between 2-dimensional objects and 19 topological ones between 1-dimensional objects and propose four different strategies to convert 2-dimensional topological relations in the source database to 1-dimensional ones objects in the target database. With these strategies, we guarantee the topological consistency between multi-scale databases.

• Korean Journal of Geomatics
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• v.2 no.1
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• pp.75-82
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• 2002

The information system fields of spatial applications have rapidly grown during the last decade in Korea. Spatial data has been produced for a variety of systems without common standards until national GIS Committee defined the data exchange formats among spatial databases in the middle of 1990's. It aimed at promoting data sharing between the different systems in similar application fields. However, a considerable number of databases built prior to the introduction of the standards are not yet standard compliant but still play the roles of the main producers/consumers in the data collection field such as early developed huge AM/FM systems maintained by governmental organizations. The strong autonomy of these databases keeps their own data models, formats and descriptions from being standardized, which leads the sharing to a more difficult stage. Sharing is another way of data acquisition with least efforts and time away from direct collection. A data clearinghouse is the core module which directs users to the relevant data resources. The contents of datasets should be described with predefined metadata standards for precise indexing. Moreover, a number of technical problems have to be resolved for the common use of data between heterogeneous spatial database systems. However, the technical issues can be covered by the present information technologies. The difficulties persist in the political/institutional issues. Institutional issues are derived from the diverse sources such as political background, governmental policies, related laws and/or regulations. The paper will firstly make an analysis of current situation in terms of Korean policies, laws and regulations, secondly abstract the institutional issues from the situation analysis, lastly present guidelines for promoting spatial data sharing in Korea.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.726-729
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• 2004

Spatiotemporal phenomena are ubiquitous aspects of real world. In the spatial and temporal databases, integrity constraints maintain the semantics of specific application domain and relationship between domains when proceed update in the database. Efficient maintenance of data integrity has become a critical problem, since testing the validity of a large number of constraints in a large database and after each transaction is an expensive task. Especially, in spatiotemporal domain, data is more complex than traditional domains and very active. Additionally, it is not considered that unified frameworks deal with both spatial and temporal properties to handle integrity constraints. Therefore, there need a model to maintain integrity constraints in the unified frameworks and enforcement and management techniques in order to preserve consistence.

• Journal of Korea Multimedia Society
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• v.13 no.12
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• pp.1739-1747
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• 2010

The damage of natural disasters has occurred on huge scale more frequently than before. The damage caused by the disasters are summarized and are analyzed, and are managed as a very general type of documentation, not showing the position of previous damage records and related information such as weather, facilities of CCTV, hospitals, and gas station on the maps. Therefore, it needs to provide map-based searching systems considering damaged area as well as search key-words. This paper focuses on the development of a search system based on the map to manage previous disaster records and related information each disaster using spatial databases. This system consists of three modules, which are databases to store disaster data, the SQL procedure-based search module to extract needed information from the constructed databases, and the map module to express the search results on the map. This paper will contribute to provide framework of a system development for managing the disaster information according to each year and disaster based on the maps and to be utilized as the basic framework in developing damage prediction and prevention systems for disasters in future.

• Journal of KIISE:Databases
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• v.27 no.2
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• pp.238-246
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• 2000

The distance join has been introduced previously, which finds nearest pairs in the order of distance incrementally among two spatial data sets built with multidimensional indexes like R-trees. We propose efficient K-distance joins when the number(K) of pairs to find is preset. Especially, we develop a distance join algorithm with bi-directional expansion and optimized plane sweeping using selection method of sweep axis and direction. The experiments on real spatial data sets show that the proposed algorithm is much better than the former algorithms.

• Electronics and Telecommunications Trends
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• v.39 no.4
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• pp.1-9
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• 2024

As Advanced Air Mobility (AAM) technologies evolve, ensuring accurate navigation and localization in complex urban airspaces has become crucial. Because the Global Navigation Satellite System (GNSS) is prone to vulnerabilities in urban flight environment, an alternative localization technique is required. This paper examines vision-based localization technologies to enhance GNSS-free navigation. In addition, we explore various geo-referencing studies that utilize pre-existing spatial databases to improve the accuracy of vision-based localization under GNSS-denied conditions. This paper discusses the various types of onboard vision camera sensors, vision-based localization, spatial information databases, feature extraction methods, and matching techniques that contribute to the development of a vision-based localization and geo-referencing system for AAM, ensuring safety and reliability in urban operations.

• Journal of KIISE:Databases
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• v.33 no.4
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• pp.396-408
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• 2006

Moving object databases manage a large amount of past location data which are accumulated as the time goes. To retrieve fast the past location of moving objects, we need index structures which consider features of moving objects. The KDB-tree has a good performance in processing range queries. Although we use the KDB-tree as an index structure for moving object databases, there has an over-split problem in the spatial domain since the feature of moving object databases is to increase the time domain. Because the over-split problem reduces spatial regions in the MBR of nodes inverse proportion to the number of splits, there has a problem that the cost for processing spatial-temporal range queries is increased. In this paper, we propose the dynamic split strategy of the KDB-tree to process efficiently the spatial-temporal range queries. The dynamic split strategy uses the space priority splitting method for choosing the split domain, the recent time splitting policy for splitting a point page to maximize the space utilization, and the last division policy for splitting a region page. We compare the performance of proposed dynamic split strategy with the 3DR-tree, the MV3R-tree, and the KDB-tree. In our performance study for range queries, the number of node access in the MKDB-tree is average 30% less than compared index structures.

• Journal of KIISE:Databases
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• v.32 no.1
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• pp.43-55
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• 2005

Spatiotemporal databases support methods of recording and querying for spatiotemporal data to user by offering both spatial management and historical information on various types of objects in the real world. We can answer to the following query in real world: 'What is the average of volume of pesticide sprayed for cach farm land from April to August on 2001, within some query window' Such aggregation queries have both temporal and spatial constraint. However, previous works for aggregation are attached only to temporal aggregation or spatial aggregation. So they have problems that are difficult to apply for spatiotemporal data directly which have both spatial and temporal constraint. Therefore, in this paper, we propose spatiotemporal aggregate functions for analysis of spatiotemporal data which have spatiotemporal characteristic, such as stCOUNT, stSUM, stAVG, stMAX, stMIN. We also show that our proposal resulted in the convenience and improvement of query in application systems, and facility of analysis on spatiotemporal data which the previous temporal or spatial aggregate functions are not able to analyze, by applying to the estate management system. Then, we show the validity of our algorithm performance through the evaluation of spatiotemporal aggregate functions.