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Book: Spatial Data Management

TitleSpatial Data Management
Authors
KeywordsSpatial data infrastructures
Geospatial data
Database management
Issue Date2012
PublisherMorgan & Claypool
Citation
Mamoulis, N. Spatial Data Management. San Rafael, Calif.: Morgan & Claypool. 2012 How to Cite?
AbstractSpatial database management deals with the storage, indexing, and querying of data with spatial features, such as location and geometric extent. Many applications require the efficient management of spatial data, including Geographic Information Systems, Computer Aided Design, and Location Based Services. The goal of this book is to provide the reader with an overview of spatial data management technology, with an emphasis on indexing and search techniques. It first introduces spatial data models and queries and discusses the main issues of extending a database system to support spatial data. It presents indexing approaches for spatial data, with a focus on the R-tree. Query evaluation and optimization techniques for the most popular spatial query types (selections, nearest neighbor search, and spatial joins) are portrayed for data in Euclidean spaces and spatial networks. The book concludes by demonstrating the ample application of spatial data management technology on a wide range of related application domains: management of spatio-temporal data and high-dimensional feature vectors, multi-criteria ranking, data mining and OLAP, privacy-preserving data publishing, and spatial keyword search.
Persistent Identifierhttp://hdl.handle.net/10722/166462
ISBN
Series/Report no.Synthesis Lectures on Data Management; # 21

 

DC FieldValueLanguage
dc.contributor.authorMamoulis, Nen_US
dc.date.accessioned2012-09-20T08:36:32Z-
dc.date.available2012-09-20T08:36:32Z-
dc.date.issued2012en_US
dc.identifier.citationMamoulis, N. Spatial Data Management. San Rafael, Calif.: Morgan & Claypool. 2012-
dc.identifier.isbn9781608458325-
dc.identifier.urihttp://hdl.handle.net/10722/166462-
dc.description.abstractSpatial database management deals with the storage, indexing, and querying of data with spatial features, such as location and geometric extent. Many applications require the efficient management of spatial data, including Geographic Information Systems, Computer Aided Design, and Location Based Services. The goal of this book is to provide the reader with an overview of spatial data management technology, with an emphasis on indexing and search techniques. It first introduces spatial data models and queries and discusses the main issues of extending a database system to support spatial data. It presents indexing approaches for spatial data, with a focus on the R-tree. Query evaluation and optimization techniques for the most popular spatial query types (selections, nearest neighbor search, and spatial joins) are portrayed for data in Euclidean spaces and spatial networks. The book concludes by demonstrating the ample application of spatial data management technology on a wide range of related application domains: management of spatio-temporal data and high-dimensional feature vectors, multi-criteria ranking, data mining and OLAP, privacy-preserving data publishing, and spatial keyword search.-
dc.languageengen_US
dc.publisherMorgan & Claypoolen_US
dc.relation.ispartofseriesSynthesis Lectures on Data Management; # 21-
dc.subjectSpatial data infrastructures-
dc.subjectGeospatial data-
dc.subjectDatabase management-
dc.titleSpatial Data Managementen_US
dc.typeBooken_US
dc.identifier.emailMamoulis, N: nikos@cs.hku.hken_US
dc.identifier.authorityMamoulis, N=rp00155en_US
dc.identifier.hkuros208290en_US
dc.identifier.spage1-
dc.identifier.epage133-
dc.publisher.placeSan Rafael, Calif.-

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