
Geographic Data Mining and Knowledge Discovery
CRC Press
2nd Edition
Published on 27. May 2009
Book
Hardback
486 pages
978-1-4200-7397-3 (ISBN)
Description
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.
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.
Reviews / Votes
"... This book is about the rapidly growing field of geographic data mining-systematic procedures for searching through these vast resources in support of science, intelligence-gathering, and decision-making. It includes chapters on new methods of visualization and statistical analysis that together can produce new geographic knowledge out of the vast unorganized morass of information that is now available to us. This second edition of a work that first appeared in 2001 gives an essential and detailed update on developments in a rapidly advancing field."-Michael Goodchild, University of California, Santa Barbara, USA
More details
Series
Edition
2nd edition
Language
English
Place of publication
Bosa Roca
United States
Publishing group
Taylor & Francis Inc
Target group
Professional and scholarly
Professional Practice & Development
Product notice
Paper over boards
Illustrations
162 s/w Abbildungen
162 Illustrations, black and white
Dimensions
Height: 240 mm
Width: 161 mm
Thickness: 31 mm
Weight
892 gr
ISBN-13
978-1-4200-7397-3 (9781420073973)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Harvey J. Miller | Jiawei Han
Geographic Data Mining and Knowledge Discovery
E-Book
05/2009
2nd Edition
CRC Press
€191.99
Available for download

Harvey J. Miller | Jiawei Han
Geographic Data Mining and Knowledge Discovery
E-Book
05/2009
2nd Edition
CRC Press
€191.99
Available for download
Previous edition

Harvey J. Miller | Jiawei Han
Geographic Data Mining and Knowledge Discovery
Book
10/2001
1st Edition
Taylor & Francis
€166.38
Article exhausted; check for reprint
Persons
University of Utah, Salt Lake City, USA University of Illinois at Urbana-Champaign, USA
Content
Introduction. Spatiotemporal Data Mining Paradigms and Methodologies. Fundamentals of Spatial Data Warehousing for Geographic Knowledge Discovery. Analysis of Spatial Data with Map Cubes: Highway Traffic Data. Data Quality Issues and Geographic Knowledge Discovery. Spatial Classification and Prediction Models for Geospatial Data Mining. An Overview of Clustering Methods in Geographic Data Analysis. Computing Medoids in Large Spatial Datasets. Looking for a Relationship? Try GWR. Leveraging the Power of Spatial Data Mining to Enhance the Applicability of GIS Technology. Visual Exploration and Explanation in Geography: Analysis with Light. Multivariate Spatial Clustering and Geovisualization. Toward Knowledge Discovery about Geographic Dynamics in Spatiotemporal Databases. The Role of a Multitier Ontological Framework in Reasoning to Discover Meaningful Patterns of Sustainable Mobility. Periodic Pattern Discovery from Trajectories of Moving Objects. Decentralized Spatial Data Mining for Geosensor Networks. Beyond Exploratory Visualization of Space-Time Paths.