Miller / Han Geographic Data Mining and Knowledge Discovery, Second Edition

2. Auflage 2009
ISBN: 978-1-4200-7398-0
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 486 Seiten

Reihe: Chapman & Hall/CRC Data Mining and Knowledge Discovery Series

The Definitive Volume on Cutting-Edge Exploratory Analysis of Massive Spatial and Spatiotemporal Databases
Since the publication of the first edition of Geographic Data Mining and Knowledge Discovery, new techniques for geographic data warehousing (GDW), spatial data mining, and geovisualization (GVis) have been developed. In addition, there has been a rise in the use of knowledge discovery techniques due to the increasing collection and storage of data on spatiotemporal processes and mobile objects. Incorporating these novel developments, this second edition reflects the current state of the art in the field.
New to the Second Edition

- Updated material on geographic knowledge discovery (GKD), GDW research, map cubes, spatial dependency, spatial clustering methods, clustering techniques for trajectory data, the INGENS 2.0 software, and GVis techniques

- New chapter on data quality issues in GKD

- New chapter that presents a tree-based partition querying methodology for medoid computation in large spatial databases

- New chapter that discusses the use of geographically weighted regression as an exploratory technique

- New chapter that gives an integrated approach to multivariate analysis and geovisualization

- Five new chapters on knowledge discovery from spatiotemporal and mobile objects databases

Geographic data mining and knowledge discovery is a promising young discipline with many challenging research problems. This book shows that this area represents an important direction in the development of a new generation of spatial analysis tools for data-rich environments. Exploring various problems and possible solutions, it will motivate researchers to develop new methods and applications in this emerging field.

Zielgruppe

Computer scientists, geographic information scientists, and remote sensing specialists.

Autoren/Hrsg.

Miller, Harvey J.

Han, Jiawei

Fachgebiete

• Geowissenschaften Geographie | Raumplanung Geodäsie, Kartographie, GIS, Fernerkundung
• Geowissenschaften Geologie Geodäsie, Kartographie, Fernerkundung

Inhaltsverzeichnis

Introduction
Harvey J. Miller and Jiawei Han

Spatiotemporal Data Mining Paradigms and Methodologies
John F. Roddick and Brian G. Lees

Fundamentals of Spatial Data Warehousing for Geographic Knowledge Discovery
Yvan Bédard and Jiawei Han

Analysis of Spatial Data with Map Cubes: Highway Traffic Data
Chang-Tien Lu, Arnold P. Boedihardjo, and Shashi Shekhar
NEW! Data Quality Issues and Geographic Knowledge Discovery
Marc Gervais, Yvan Bedard, Marie-Andree Levesque, Eveline Bernier, and Rodolphe Devillers

Spatial Classification and Prediction Models for Geospatial Data Mining
Shashi Shekhar, Ranga Raju Vatsavai, and Sanjay Chawla

An Overview of Clustering Methods in Geographic Data Analysis
Jiawei Han, Jae-Gil Lee, and Micheline Kamber
NEW! Computing Medoids in Large Spatial Datasets
Kyriakos Mouratidis, Dimitris Papadias, Spiros Papadimitriou
NEW! Looking for a Relationship? Try GWR
A. Stewart Fotheringham, Martin Charlton, and Urška Demšar

Leveraging the Power of Spatial Data Mining to Enhance the Applicability of GIS Technology
Donato Malerba, Antonietta Lanza, and Annalisa Appice

Visual Exploration and Explanation in Geography: Analysis with Light
Mark Gahegan
NEW! Multivariate Spatial Clustering and Geovisualization
Diansheng Guo
NEW! Toward Knowledge Discovery about Geographic Dynamics in Spatiotemporal Databases}
May Yuan
NEW! The Role of a Multitier Ontological Framework in Reasoning to Discover Meaningful Patterns of Sustainable Mobility
Monica Wachowicz, Jose Macedo, Chiara Renso, and Arend Ligtenberg
NEW! Periodic Pattern Discovery from Trajectories of Moving Objects
Huiping Cao, Nikos Mamoulis, and David W. Cheung
NEW! Decentralized Spatial Data Mining for Geosensor Networks
Patrick Laube and Matt Duckham
NEW! Beyond Exploratory Visualization of Space-Time Paths
Menno-Jan Kraak and Otto Huisman