The authors explore and explain current techniques for handling the specialised data that describes geographical phenomena in a study that will be of great value to computer scientists and geographers working with spatial databases.

Spatial 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. Table of Contents: Introduction / Spatial Data / Indexing / Spatial Query Evaluation / Spatial Networks / Applications of Spatial Data Management Technology

This book places spatial data within the broader domain of information technology (IT) while providing a comprehensive and coherent explanation of the guiding principles, methods, implementation and operational management of spatial databases within the workplace. The text explains the key concepts, issues and processes of spatial data implementation and provides a holistic management perspective.

This book provides a cross-section of cutting-edge research areas being pursued by researchers in spatial data handling and geographic information science (GIS). It presents selected papers on the advancement of spatial data handling and GIS in digital cartography, geospatial data integration, geospatial database and data infrastructures, geospatial data modeling, GIS for sustainable development, the interoperability of heterogeneous spatial data systems, location-based services, spatial knowledge discovery and data mining, spatial decision support systems, spatial data structures and algorithms, spatial statistics, spatial data quality and uncertainty, the visualization of spatial data, and web and wireless applications in GIS.

Spatial 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. Table of Contents: Introduction / Spatial Data / Indexing / Spatial Query Evaluation / Spatial Networks / Applications of Spatial Data Management Technology

This book guides animal ecologists, biologists and wildlife and data managers through a step-by-step procedure to build their own advanced software platforms to manage and process wildlife tracking data. This unique, problem-solving-oriented guide focuses on how to extract the most from GPS animal tracking data, while preventing error propagation and optimizing analysis performance. Based on the open source PostgreSQL/PostGIS spatial database, the software platform will allow researchers and managers to integrate and harmonize GPS tracking data together with animal characteristics, environmental data sets, including remote sensing image time series, and other bio-logged data, such as acceleration data. Moreover, the book shows how the powerful R statistical environment can be integrated into the software platform, either connecting the database with R, or embedding the same tools in the database through the PostgreSQL extension Pl/R. The client/server architecture allows users to remotely connect a number of software applications that can be used as a database front end, including GIS software and WebGIS. Each chapter offers a real-world data management and processing problem that is discussed in its biological context; solutions are proposed and exemplified through ad hoc SQL code, progressively exploring the potential of spatial database functions applied to the respective wildlife tracking case. Finally, wildlife tracking management issues are discussed in the increasingly widespread framework of collaborative science and data sharing. GPS animal telemetry data from a real study, freely available online, are used to demonstrate the proposed examples. This book is also suitable for undergraduate and graduate students, if accompanied by the basics of databases.

Spatial Data on Water: Geospatial Technologies and Data Management focuses on the worldwide corroborated difficulties in accessing data, a major hindrance in conducting water related studies in several domains. - Presents examples of research focused on water resource management - Includes a guide on how to manage water data using a geographic information system and a spatial data infrastructure - Provides several ideas and techniques to support integrated water data management