Knowledge Discovery in Spatial Data

✍ Scribed by Yee Leung (auth.)

Publisher: Springer-Verlag Berlin Heidelberg
Year: 2009
Tongue: English
Leaves: 381
Series: Advances in Spatial Science
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

This book deals with knowledge discovery and data mining in spatial and temporal data, seeking to present novel methods that can be employed to discover spatial structures and processes in complex data. Spatial knowledge discovery is examined through the tasks of clustering, classification, association/relationship, and process. Among the covered topics are discovery of spatial structures as natural clusters, identification of separation surfaces and extraction of classification rules from statistical and algorithmic perspectives, detecting local and global aspects of non-stationarity of spatial associations and relationships, unraveling scaling behaviors of time series data, including self-similarity, and long range dependence. Particular emphasis is placed on the treatment of scale, noise, imperfection and mixture distribution. Numerical examples and a wide scope of applications are used throughout the book to substantiate the conceptual and theoretical arguments.

✦ Table of Contents

Front Matter....Pages i-xxix
Introduction....Pages 1-12
Discovery of Intrinsic Clustering in Spatial Data....Pages 13-96
Statistical Approach to the Identification of Separation Surface for Spatial Data....Pages 97-142
Algorithmic Approach to the Identification of Classification Rules or Separation Surface for Spatial Data....Pages 143-221
Discovery of Spatial Relationships in Spatial Data....Pages 223-276
Discovery of Structures and Processes in Temporal Data....Pages 277-319
Summary and Outlooks....Pages 321-327
Back Matter....Pages 329-360

✦ Subjects

Regional/Spatial Science; Quantitative Geography

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