Geostatistical Applications for Precision Agriculture
This book brings together in one place two dynamic subjects, precision agriculture and geostatistics, that have spatial variation at their core. Geostatistics is applied in precision agriculture (PA) to sampling, prediction, mapping, decision-making, econ
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M.A. Oliver Editor
Geostatistical Applications for Precision Agriculture
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Editor M.A. Oliver Visiting Professor in Soil Science Department of Soil Science The University of Reading Whiteknights, Reading RG6 6DW United Kingdom [email protected]
ISBN 978-90-481-9132-1 e-ISBN 978-90-481-9133-8 DOI 10.1007/978-90-481-9133-8 Springer Dordrecht Heidelberg London New York Library of Congress Control Number: 2010931684 © Springer Science+Business Media B.V. 2010 No part of this work may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, microfilming, recording or otherwise, without written permission from the Publisher, with the exception of any material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Cover legend: Harvesting a variable-rate nitrogen experiment on Cashmore Field, Silsoe, England. Photograph provided by Silsoe Research institute. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
Preface
This book brings together two dynamic subjects, precision agriculture and geostatistics, that have spatial variation at their core. Geostatistics is applied to many aspects of precision agriculture (PA) including sampling, prediction, mapping, decisionmaking, variable-rate applications, economics and so on. Contributions from experts in several fields of study illustrate how geostatistics can and has been used to advantage with data such as yield, soil, crops, pests, aerial photographs, remote and proximal imagery. Geostatistical techniques applied include variography, ordinary-, disjunctive-, factorial-, indicator-, regression-, simple-, space-time- and co-kriging, and geostatistical simulation. This book was requested by participants at the Sixth European Conference on Precision Agriculture in Skiathos, 2007 because the link between geostatistics and PA will increase as more intensive information on the soil and crops becomes available from sensors and on-the-go technology. This is not a recipe book, but is intended to guide readers in the use of appropriate techniques for the types of data and needs of the farmer in managing the land. All chapters include one or more case studies to illustrate the techniques. Chapter 1 sets the scene for the two main topics of the book. The two core techniques of geostatistics, variography and kriging, are described, together with examples of how they can be applied. Sampling for geostatistics is an important issue because it underpins sound results. Chapter 2 considers the importance of spatial scale in sampling, the use of ancillary data, a nested survey and existing variograms of soil or crop properties to guide sampling. Chapter 3 demonstrates the potential to optimize the design of soil sampling schemes if the variation of the target property is represented by a linear mixed model. Chapter 4 describes how calibrated yield data from monitors can be used to
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