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£78.75

CRC Press Spatial Data Quality: From Process to Decisions

Name: Spatial Data Quality: From Process to Decisions
Brand: CRC Press
Price: 78.75 GBP
Availability: InStock

Geochemistry

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Description

Producing maps that depict the real world accurately has been a major concern of cartographers for centuries. This is especially true today as escalating access to geospatial data and the subsequent increase in user-generated content provided by Web 2.0 have significantly altered the typical processes used to produce, distribute, and use geospatial data. Focusing on users and decisions as well as the data, Spatial Data Quality: From Process to Decisions provides an up-to-date overview of scientific progress in this core sub-discipline of the Geographic Information Sciences. Presenting results from a number of current research projects in spatial data quality (SDQ) ― from the assessment of data accuracy to legal aspects relating to the quality of geographic information ― this reference reflects the changes in practice in response to the rapid technological developments over the past decade. An impressive panel of internationally recognized expert contributors focuses on the relationship between the quality of geographic data and the quality of decisions based on such data. Structured for easy reference, the first section of the book discusses conceptual approaches to SDQ, the second presents a number of applications of spatial data quality methods, the third looks at SDQ issues for remote sensing data, and the final section presents papers that consider the interface between the law and SDQ. In addition to the main chapters presented in each section, a number of shorter notes present on-going and recent research projects investigating various aspects of spatial data quality.

Product Specifications

Brand: CRC Press
Format: Paperback
ASIN: 113811782X
Category: Books > Subjects > Science, Nature & Maths > Chemistry > Geochemistry
Domain: Amazon UK
Release Date: 21 July 2017
Listed Since: 12 May 2017

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CRC Press Spatial Data Quality: From Process to Decisions

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