Vijay Gandhi, James M. Kang, Shashi Shekhar · Wiley Encyclopedia of Computer Science and Engineering · 2008
Abstract Spatial database research has continued to advance greatly in the last three decades addressing the growing data management and analysis needs of spatial applications. This research has produced a taxonomy of models for space, conceptual models, spatial query languages and query processing, spatial file organization and indexes, and spatial data mining. However, emerging needs for spatial database systems include the handling of 3‐D spatial data, temporal dimension with spatial data, and spatial data visualization. In addition, the rise of new systems such as sensor networks and multicore processors is likely to have an impact in spatial databases. The goal of this article is to provide a broad overview of the recent advancements in spatial databases and of research needs in each area.
Cited by 1
Gandhi, Vijay, Kang, James, Shekhar, Shashi · Defense Technical Information Center (DTIC) · 2007
Spatial database research has continued to advance greatly since three decades ago, addressing the growing data management and analysis needs of spatial applications. This research has produced a taxonomy of models for space, conceptual models, spatial query languages and query processing, spatial file organization and indexes, and spatial data mining. However, emerging needs for spatial database systems include the handling of 3D spatial data, temporal dimension with spatial data, and spatial data visualization. In addition, the rise of new systems such as sensor networks and multi-core processors is likely to have an impact in spatial databases. The goal of this paper is to provide a broad overview of the recent advancements in spatial databases and research needs in each area.
Cited by 0
Vijay Gandhi, James M. Kang, Shashi Shekhar · 2007
Spatial database research has continued to advance greatly since three decades ago, addressing the growing data management and analysis needs of spatial applications. This research has produced a taxonomy of models for space, conceptual models, spatial query languages and query processing, spatial file organization and indexes, and spatial data mining. However, emerging needs for spatial database systems include the handling of 3D spatial data, temporal dimension with spatial data, and spatial data visualization. In addition, the rise of new systems such as sensor networks and multi-core processors is likely to have an impact in spatial databases. The goal of this paper is to provide a broad overview of the recent advancements in spatial databases and research needs in each area.
Cited by 0
Ralf Hartmut Güting · Wiley Encyclopedia of Electrical and Electronics Engineering · 1999
Abstract The sections in this article are Modeling and Querying Implementation
Cited by 1
Adam C. Winstanley, Peter Mooney · Elsevier eBooks · 2019
Cited by 0
Gandhi, Vijay, Kang, James, Shekhar, Shashi · University of Minnesota Digital Conservancy (University of Minnesota) · 2007
Spatial database research has continued to advance greatly since three decades ago, addressing the growing data management and analysis needs of spatial applications. This research has produced a taxonomy of models for space, conceptual models, spatial query languages and query processing, spatial file organization and indexes, and spatial data mining. However, emerging needs for spatial database systems include the handling of 3D spatial data, temporal dimension with spatial data, and spatial data visualization. In addition, the rise of new systems such as sensor networks and multi-core processors is likely to have an impact in spatial databases. The goal of this paper is to provide a broad overview of the recent advancements in spatial databases and research needs in each area.
Cited by 0Open access
Yannis Manalopoulos, Apostolos N. Papadopoulos, Michael Vassilakopoulos · IGI Global eBooks · 2005
Section I: Modeling and Systems, Chapter I. Survey on Spatial Data Modeling Approaches, Chapter II. Integrating Web Data and Geographic Knowledge into Spatial Databases, Section II: Indexing Techniques, Chapter III. Object-Relational Spatial Indexing, Chapter IV. Quadtree-Based Image Representation and Retrieval, Chapter V. Indexing Multi-Dimensional Trajectories for Similarity Queries, Section III: Query Processing and Optimization, Chapter VII. Spatial Joins: Algorithms, Cost Models and Optimization Techniques, Section IV: Moving Objects, Chapter VIII. Applications of Moving Objects Databases, Chapter IX. Simple and Incremental Nearest-Neighbor Search in Spatiotemporal Databases, Chapter X. Management of Large Moving Objects Datasets: Indexing, Benchmarking and Uncertainty in Movement Representation, Section V: Data Mining, Chapter XI. Spatiotemporal Prediction using Data Mining Tools, Chapter XII. Mining in Spatiotemporal Databases, Chapter XIII. Similarity Learning in GIS: An Overview of Definitions, Prerequisites and Challenges
Cited by 21
Vijay Gandhi, James D. Kang, Shashi Shekhar · 2007
Cited by 3
Hong Kang, Kailin Tang, Qi Liu et al. · 2007
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Donnay, Jean-Paul · Open Repository and Bibliography (University of Liège) · 2006
peer reviewed
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Winstanley, Adam C. · MURAL - Maynooth University Research Archive Library (National University of Ireland, Maynooth) · 2009
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Shashi Shekhar, Pusheng Zhang, Sanjay Chawla · Encyclopedia of Social Measurement · 2005
Cited by 14
2009
Spatial database management systems (1–6) aim at the effective and efficient management of data related to space in the physical world (geography, urban planning, astronomy, human anatomy, fluid flow, or an
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Betsy George, Shashi Shekhar · Encyclopedia of Database Systems · 2009
Cited by 2
SpringerReference · 2011
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SpringerReference · 2011
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Michael Vassilakopoulos · IGI Global eBooks · 2009
A Spatial Database is a database that offers spatial data types, a query language with spatial predicates, spatial indexing techniques, and efficient processing of spatial queries. All these fields have attracted the focus of researchers over the past 25 years. The main reason for studying spatial databases has been applications that emerged during this period, such as Geographical Information Systems, Computer-Aided Design, Very Large Scale Integration design, Multimedia Information Systems, and so forth. In parallel, the field of temporal databases, databases that deal with the management of timevarying data, attracted the research community since numerous database applications (i.e., Banking, Personnel Management, Transportation Scheduling) involve the notion of time.
Cited by 1
Panos Kalnis · Encyclopedia of Database Systems · 2009
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Péter Révész · Encyclopedia of GIS · 2016
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Péter Révész · Encyclopedia of GIS · 2017
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