Knowledge Discovery in Spatial Data

  • Yee Leung

Part of the Advances in Spatial Science book series (ADVSPATIAL)

Table of contents

About this book

Introduction

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.

Keywords

Algorithm Clustering Geographical Information System Knowledge Discovery Remote Sensing Spatial Data Mining classification data mining geographic data

Authors and affiliations

  • Yee Leung
    • 1
  1. 1.Dept. Geography &Chinese University of Hong KongShatin, New TerritoriesHong Kong/PR China

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-02664-5
  • Copyright Information Springer-Verlag Berlin Heidelberg 2009
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Humanities, Social Sciences and Law
  • Print ISBN 978-3-642-02663-8
  • Online ISBN 978-3-642-02664-5
  • Series Print ISSN 1430-9602
  • About this book