Books  Data Analysis & Modelling  Cartography, Remote Sensing, Image Analysis & GIS 

Principles of Modeling Uncertainties in Spatial Data and Spatial Analysis

By: Wenzhong Shi

412 pages, Col & b/w figs

CRC Press

Hardback | Oct 2009 | #171405 | ISBN-13: 9781420059274
Availability: Usually dispatched within 6 days Details
NHBS Price: £102.00 $125/€115 approx

About this book

Modeling uncertainties in geographic information science is essential to the development of the field. This book addresses one of the fundamental theoretical issues: uncertainties in spatial data and analysis. Along with the latest research findings, the text provides methods to control uncertainties in GIS applications. The author contributes his own unique research in modeling positional uncertainty based on probability theory and statistics. New areas, such as uncertainty-based spatial mining, are introduced providing a new prospective on the theory and applications of GIS. Researchers, students, and professionals working in GIS can benefit from the insightful presentation of new ideas.


Introduction. Uncertainty Sources of Spatial Data and Spatial Analyses. Mathematical Foundations. Modeling Positional Uncertainties in Linear Features in GIS. Modeling Uncertainties in Digital Evolution Models. Modeling Thematic Uncertainties in GIS Data. Modeling Integrated Positional and Thematic Elements. Modeling Uncertain Topological Relations. Modeling Positional Uncertainties in Overlay Analysis. Modeling Positional Uncertainty in Buffer Analysis. Uncertainty Visualization. Uncertainty Metadata for Spatial Data. Uncertainty-Based Spatial Data Mining. Quality Control for Cadastral Data. Web Service-Based GIS Data Quality Information System.

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The Hong Kong Polytech University, Kowloon

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