Spatial Data Collections And Services

The book is concerned with the statistical theory for locating spatial sensors. It bridges the gap between spatial statistics and optimum design theory. After introductions to those two fields the topics of exploratory designs and designs for spatial trend and variogram estimation are treated. Special attention is devoted to describing new methodologies to cope with the problem of correlated observations.

With the onslaught of emergent technology in academia, libraries are privy to many innovative techniques to recognize and classify geospatial data?above and beyond the traditional map librarianship. As librarians become more involved in the development and provision of GIS services and resources, they encounter both problems and solutions. Integrating Geographic Information Systems into Library Services: A Guide for Academic Libraries integrates traditional map librarianship and contemporary issues in digital librarianship within a framework of a global embedded information infrastructure, addressing technical, legal, and institutional factors such as collection development, reference and research services, and cataloging/metadata, as well as issues in accessibility and standards.

Metadata play a fundamental role in both DLs and SDIs. Commonly defined as "structured data about data" or "data which describe attributes of a resource" or, more simply, "information about data", it is an essential requirement for locating and evaluating available data. Therefore, this book focuses on the study of different metadata aspects, which contribute to a more efficient use of DLs and SDIs. The three main issues addressed are: the management of nested collections of resources, the interoperability between metadata schemas, and the integration of information retrieval techniques to the discovery services of geographic data catalogs (contributing in this way to avoid metadata content heterogeneity).

The report describes potential applications of geographic information systems (GIS) and spatial analysis by HUD's Office of Policy Development and Research for understanding housing needs, addressing broader issues of urban poverty and community development, and improving access to information and services by the many users of HUD's data. It offers a vision of HUD as an important player in providing urban data to federal initiatives towards a spatial data infrastructure for the nation.

Map Librarianship identifies basic geoliteracy concepts and enhances reference and instruction skills by providing details on finding, downloading, delivering, and assessing maps, remotely sensed imagery, and other geospatial resources and services, primarily from trusted government sources. By offering descriptions of traditional maps, geographic information systems (GIS), remote sensing, and other geospatial technologies, the book provides a timely and practical guide for the map and geospatial librarian to blend confidence in traditional library skill sets. Includes rarely discussed concepts of citing and referencing maps and geospatial data, fair use and copyright Creates an awareness and appreciation of existing print map collections, while building digital stewardship with surrogate map and aerial imagery collections Provides an introduction to the theory and applications of GIS, remote sensing, participatory neogeography and neocartography practices, and other geospatial technologies Includes a list of geospatial resources with descriptions and illustrations of commonly used map types and formats, online geospatial data sources, and an introduction to the most commonly used geospatial software packages available, on both desktop and mobile platforms

As Web service technologies have matured in recent years, an increasing number of geospatial Web services designed to deal with spatial information over the network have emerged. Geospatial Web Services: Advances in Information Interoperability provides relevant theoretical frameworks and the latest empirical research findings and applications in the area. This book highlights the strategic role of geospatial Web services in a distributed heterogeneous environment and the life cycle of geospatial Web services for building interoperable geospatial applications.

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

Applied Spatial Data Analysis with R, second edition, is divided into two basic parts, the first presenting R packages, functions, classes and methods for handling spatial data. This part is of interest to users who need to access and visualise spatial data. Data import and export for many file formats for spatial data are covered in detail, as is the interface between R and the open source GRASS GIS and the handling of spatio-temporal data. The second part showcases more specialised kinds of spatial data analysis, including spatial point pattern analysis, interpolation and geostatistics, areal data analysis and disease mapping. The coverage of methods of spatial data analysis ranges from standard techniques to new developments, and the examples used are largely taken from the spatial statistics literature. All the examples can be run using R contributed packages available from the CRAN website, with code and additional data sets from the book's own website. Compared to the first edition, the second edition covers the more systematic approach towards handling spatial data in R, as well as a number of important and widely used CRAN packages that have appeared since the first edition. This book will be of interest to researchers who intend to use R to handle, visualise, and analyse spatial data. It will also be of interest to spatial data analysts who do not use R, but who are interested in practical aspects of implementing software for spatial data analysis. It is a suitable companion book for introductory spatial statistics courses and for applied methods courses in a wide range of subjects using spatial data, including human and physical geography, geographical information science and geoinformatics, the environmental sciences, ecology, public health and disease control, economics, public administration and political science. The book has a website where complete code examples, data sets, and other support material may be found: http://www.asdar-book.org. The authors have taken part in writing and maintaining software for spatial data handling and analysis with R in concert since 2003.

Advances in Geo-Spatial Information Science presents recent advances regarding fundamental issues of geo-spatial information science (space and time, spatial analysis, uncertainty modeling and geo-visualization), and new scientific and technological research initiatives for geo-spatial information science (such as spatial data mining, mobile data modeling, and location-based services). The book contains selected and revised papers presented at the joint International Conference on Theory, Data Handling and Modelling in GeoSpatial Information Science (Hong Kong, 26–28 May 2010), and brings together three related international academic communities: spatial information science, spatial data handling, and modeling geographic systems. Advances in Geo-Spatial Information Science will be of interest for academics and professionals interested in spatial information science, spatial data handling, and modeling of geographic systems.