Perspectives on Spatial Data Analysis
This book takes both a retrospective and prospective view of the field of spatial analysis by combining selected reprints of classic articles by Arthur Getis with current observations by leading experts in the field. Four main aspects are highlighted, dea
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Arthur Getis
Luc Anselin Sergio J. Rey l
Editors
Perspectives on Spatial Data Analysis
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Editors Prof. Dr. Luc Anselin Prof. Dr. Sergio J. Rey School of Geographical Sciences Arizona State University Coor Hall 975 S Myrtle Avenue Tempe, AZ 85287-5302 USA [email protected] [email protected]
ISBN 978-3-642-01975-3 e-ISBN 978-3-642-01976-0 DOI: 10.1007/978-3-642-01976-0 Springer Heidelberg Dordrecht London New York Library of Congress Control Number: 2009931324 # Springer-Verlag Berlin Heidelberg 2010 This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable to prosecution under the German Copyright Law. The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. Cover design: SPi Publisher Services Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
To Arthur Getis
Preface
Spatial data analysis has seen explosive growth in recent years. Both in mainstream statistics and econometrics as well as in many applied fields, the attention to space, location, and interaction has become an important feature of scholarly work. The methods developed to deal with problems of spatial pattern recognition, spatial autocorrelation, and spatial heterogeneity have seen greatly increased adoption, in part due to the availability of user friendly desktop software. Through his theoretical and applied work, Arthur Getis has been a major contributing figure in this development. In this volume, we take both a retrospective and a prospective view of the field. We use the occasion of the retirement and move to emeritus status of Arthur Getis to highlight the contributions of his work. In addition, we aim to place it into perspective in light of the current state of the art and future directions in spatial data analysis. To this end, we elected to combine reprints of selected classic contributions by Getis with chapters written by key spatial scientists. These scholars were specifically invited to react to the earlier work by Getis with an eye toward assessing its impact, tracing out the evolution of related research, and to reflect on the future broadening of spatial analysis. The organization of the book follows four main themes in Getis’ contributions: •
Spatial analysis Pattern analysis Local statistics • Applications • •
For each of these themes,
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