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The aim of this book is to bring together a series of contributions from experts in the field to cover the major aspects of the application of geostatistics in precision agriculture. The focus will not be on theory, although there is a need for some theory to set the methods in their appropriate context. The subject areas identified and the authors selected have applied the methods in a precision agriculture framework. The papers will reflect the wide range of methods available and how they can be applied practically in the context of precision agriculture. This book is likely to have more impact as it becomes increasingly possible to obtain data cheaply and more farmers use onboard digital maps of soil and crops to manage their land. It might also stimulate more software development for geostatistics in PA.

Geostatistical Applications for Precision Agriculture

Preface 1 An Overview of Geostatistics and Precision Agriculture; M. A. Oliver Abstract; 1.1 Introduction; 1.2 The Theory of Geostatistics; 1.3 Case study: Football Field 2 Sampling in Precision Agriculture: Part I; R. Kerry, M. A. Oliver and Z. L. Frogbrook Abstract; 2.1 Introduction; 2.2 Variograms to guide sampling; 2.3 Use of the variogram to guide sampling for bulking; 2.4 The variogram to guide grid-based sampling; 2.5 Variograms to improve predictions from sparse sampling; 2.6 Conclusions; References 3 Sampling in Precision Agriculture, Optimal Designs from Uncertain Models; B. P. Marchant and R. M. Lark Abstract; 3.1 Introduction; 3.2 The linear mixed model: estimation, predictions and uncertainty; 3.3 Optimizing sampling schemes by spatial simulated annealing; 3.4 Conclusions; References 4 The Spatial Analysis of Yield Data; T. W. Griffin Abstract; 4.1 Introduction; 4.2 Background of site-specific yield monitors; 4.3 Managing Yield Monitor Data; 4.4 Spatial statistical analysis of yield monitor data; 4.5 Case study: Spatial analysis of yield monitor data from a field-scale experiment; 4.6 Conclusion; References 5 Space-time Geostatistics for Precision Agriculture: A Case Study of NDVI Mapping for a Dutch Potato Field; G. B. M. Heuvelink and F. M. van Egmond Abstract; 5.1 Introduction; 5.2 Description of the Lauwersmeer study site and positional correction of NDVI data; 5.3 Exploratory data analysis of Lauwersmeer data; 5.4 Space-time geostatistics; 5.5 Application of space-time geostatistics to the Lauwersmeer farm data; 5.6 Discussion and Conclusions; References 6 Delineating Site-specific Management Units with Proximal Sensors; D. L. Corwin and S. M. Lesch; Abstract; 6.1 Introduction; 6.2 Directed Sampling with a Proximal Sensor; 6.3 Delineation of SSMUs with a Proximal Sensor; 6.4 Case Study Using Apparent Soil Electrical Conductivity (ECa) - San Joaquin Valley, CA; 6.5 Conclusion; References 7 Using Ancillary Data to Improve Prediction of Soil and Crop Attributes in Precision Agriculture; P. Goovaerts and R. Kerry Abstract; 7.1 Introduction; 7.2 Theory; 7.3 Case study 1: the Yattendon site; 7.4 Case Study 2: the Wallingford site; 7.5 Conclusions; References 8 Spatial Variation and Site-specific Management Zones; R. Khosla, D. G. Westfall, R. M. Reich, J.S. Mahal and W. J. Gangloff Abstract; 8.1 Introduction; 8.2 Quantifying spatial variation in soil and crop properties; 8.3 Site-specific management zones; 8.4 Statistical evaluation of management zone delineation techniques: A case study; 8.5 Conclusions; References 9 Weeds, Worms and Geostatistics; R. Webster Abstract; 9.1 Introduction; 9.2 Weeds; 9.3 Nematodes; 9.4 The future of geostatistics in precise pest control; References 10 The Analysis of Spatial Experiments; M.J. Pringle, T.F.A. Bishop, R.M. Lark, B.M. Whelan and A.B. McBratney Abstract; 10.1 Introduction; 10.2 Background; 10.3 Management-class experiments; 10.4 Local-response experiments; 10.5 Alternative approaches to experimentation; 10.6 Issues for the future 10.7 Conclusions; References 11 Application of Geostatistical Simulation in Precision Agriculture; R. Gebbers and S. de Bruin Abstract; 11.1 Introduction;11.2 Case study I: uncertainty of a pH map; 11.3 Case study II: uncertainty in the position of geographic objects; 11.4 Case study III: uncertainty propagation in soil mapping; 11.5 Application of geostatistical simulation in precision agriculture: summary; References 12 Geostatistics and Precision Agriculture: A Way Forward; J. K. Schueller Abstract; 12.1 Introduction; 12.2 Weather, time, and space; 12.3 Farmers, advisors and researchers; 12.4 Issues, ideas and questions; 12.5 Past, present, and future; References Appendix: Software Index