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Geostatistical Applications for Precision Agriculture
- Source :
- Geostatistical Applications for Precision Agriculture
- Publication Year :
- 2010
- Publisher :
- Springer Netherlands, 2010.
-
Abstract
- 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
Details
- Database :
- OpenAIRE
- Journal :
- Geostatistical Applications for Precision Agriculture
- Accession number :
- edsair.doi...........8d41d777d381b812bfdcc464ae407e7f
- Full Text :
- https://doi.org/10.1007/978-90-481-9133-8