Description
Implement Your Own Applications Using Online GIS
An in-depth study detailing the online applications of geographic information systems (GIS), Online GIS and Spatial Metadata, Second Edition outlines how GIS data are published, organized, accessed, searched, maintained, purchased, and processed over the web. This latest work describes how the internet has become a platform for the delivery and integration of geographic information. It highlights the growth that has taken place since the first edition and includes new chapters on popular XML formats used in online GIS, SDI Metadata Portals, Mobile GIS and Location-Based services. It also updates metadata standards and explains how metadata links it all together.
Designed To Help Non-Technical Readers Understand Technical Issues
The book provides a brief overview of the basic technology of online GIS before introducing the technical methods used to develop and implement GIS on the web. It includes an introduction to the protocols and standards now in use online and provides technical background and real-world examples of scripts, markup, and other elements that make this technology work. Expanding on the previous edition, the book offers a global perspective of online GIS, contains links and references to online resources, and includes future directions, applications, and trends.
Reviewing major advances that have occurred over the past decade, this seminal work:
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- Discusses the detail of four XML-based standards now in common use for Online GIS and spatial metadata
- Outlines the nature of Information Networks, systems in which information is distributed across many different sites
- Examines the conceptual framework of metadata, by studying the RDF and similar standards for the Web
- Describes several metadata standards in use around the world for spatial metadata
- Provides current examples of SDI metadata portals, catalogues, and clearinghouses
- Looks at ways in which distributed information can be built into data warehouses, and introduces basic ideas in data mining
