Geostatistical Applications for Precision Agriculture

Transcription

1 M.A. Oliver Editor Geostatistical Applications for Precision Agriculture Springer

2 Contents 1 An Overview of Geostatistics and Precision Agriculture 1 M.A. Oliver 1.1 Introduction A Brief History of Geostatistics A Brief History of Precision Agriculture A Brief History of Geostatistics in Precision.. Agriculture The Theory or Geostatistics Stationarity The Variogram Geostatistical Prediction: Kriging Case Study: Football Field Summary Statistics Variography Kriging Conclusions 31 References 32 2 Sampling in Precision Agriculture 35 R. Kerry, M.A. Oliver and Z.L. Frogbrook 2.1 Introduction The Importance of Spatial Scale for Sampling How Can Geostatistics Help? How can the Variogram be Used to Guide Sampling? Variograms to Guide Sampling Nested Survey and Analysis: Reconnaissance Variogram, Variograms from Ancillary 40 Data Use of the Variogram to Guide Sampling for Bulking Case Study The Variogram to Guide Grid-Based Sampling The Variogram and Kriging Equations Half the Variogram Range 'Rule of Thumb' as a Guide to Sampling Interval 54 vii

3 viii Contents 2.5 Variograms to Improve Predictions from Sparse Sampling Residual Maximum Likelihood (REML) Variogram Estimator Standardized Variograms Conclusions 61 References 62 3 Sampling in Precision Agriculture, Optimal Designs from Uncertain Models 65 B.P. Marchant and R.M. Lark 3.1 Introduction The Linear Mixed Model: Estimation, Predictions and Uncertainty The Model Estimation Prediction Uncertainty Optimizing Sampling Schemes by Spatial Simulated Annealing Spatial Simulated Annealing Objective Functions from the LMM Optimized Sample Scheme for Single Phase Geostatistical Surveys Adaptive Exploratory Surveys to Estimate the Variogram A Case Study in Soil Sampling Conclusions 85 References 86 4 The Spatial Analysis of Yield Data 89 T.W. Griffin 4.1 Introduction Background of Site-Specific Yield Monitors Concept of a Yield Monitor Calibration and Errors Common Uses of Yield Monitor Data Profitability of Yield Monitors Quantity and Quality of Product Managing Yield Monitor Data Quality of Yield Monitor Data Challenges in the Use of Yield Data for Decision Making Aligning Spatially Disparate Spatial Data Layers Spatial Statistical Analysis of Yield Monitor Data Explicit Modelling of Spatial Effects 101

4 Contents ix Spatial Interaction Structure Empirical Determination of Spatial Neighbourhood Structure Case Study: Spatial Analysis of Yield Monitor Data from a Field-Scale Experiment Case Study Data Data Analysis Case Study Results Case Study Summary Conclusion 113 References Space-Time Geostatistics for Precision Agriculture: A Case Study of NDVI Mapping for a Dutch Potato Field 117 G.B.M. Heuvelink and KM. van Egmond 5.1 Introduction Description of the Lauwersmeer Study Site and Positional Correction of NDVI Data Exploratory Data Analysis of Lauwersmeer Data Space-Time Geostatistics Characterization of the Trend Characterization of the Stochastic Residual Application of Space-Time Geostatistics to the Lauwersmeer Farm Data Characterization of the Trend Characterization of the Stochastic Residual Space-Time Kriging Discussion and Conclusions 134 References Delineating Site-Specific Management Units with Proximal Sensors 139 D.L. Corwin and S.M. Lesch 6.1 Introduction The Need for Site-Specific Management Definition of Site-Specific Management Unit (SSMU) Proximal Sensors Objective Directed Sampling with a Proximal Sensor Complexity of Proximal Sensor Measurements and the Role of Geostatistics Practical Consideration of Differences in Support Delineation of SSMUs with a Proximal Sensor Geostatistical Mixed Linear Model 146

5 x Contents Soil Sampling Strategies Based on Geo-Referenced Proximal Sensor Data Applications of Geostatistical Mixed Linear Models to Proximal Sensor Directed Surveys Case Study Using Apparent Soil Electrical Conductivity (ECa) - San Joaquin Valley, CA Materials and Methods Results and Discussion Conclusion 161 References Using Ancillary Data to Improve Prediction of Soil and Crop Attributes in Precision Agriculture 167 P. Goovaerts and R. Kerry 7.1 Introduction Theory Variogram and Cross-Variogram Cokriging Simple Kriging with Local Means Kriging with an External Drift Case Study 1: The Yattendon Site Site Description and Available Data Data Preparation Variograms Leave-One-Out Cross-Validation Patterns of Variation How Small Can the Sample Size of Primary Data be when Secondary Data are Available? Case Study 2: The Wallingford Site Site Description and Available Data Leave-One-Out Cross-Validation Using Grid Sampled Data Patterns of Variation Conclusions 192 References Spatial Variation and Site-Specific Management Zones 195 R. Khosla, D.G. Westfall, R.M. Reich, J.S. Mahal andw.j.gangloff 8.1 Introduction Quantifying Spatial Variation in Soil and Crop Properties Site-Specific Management Zones Soil Properties, Crops and Geographic Distribution of Management Zones Techniques of Delineating Management Zones 202

6 Contents xi 8.4 Statistical Evaluation of Management Zone Delineation Techniques: A Case Study Conclusions 215 References Weeds, Worms and Geostatistics 221 R. Webster 9.1 Introduction Weeds Nematodes Lives of Nematodes Geostatistical Applications Case Study Economics The Future for Geostatistics in Precise Pest Control 239 References The Analysis of Spatial Experiments 243 M.J. Pringle, TEA. Bishop, R.M. Lark, B.M. Whelan and A.B. McBratney 10.1 Introduction Background Management-Class Experiments Case Study I: REML-Based Analysis of a Management-Class Experiment Local-Response Experiments Case Study II: Analysis of a Local-Response Experiment Alternative Approaches to Experimentation Issues for the Future Conclusions 264 References Application of Geostatistical Simulation in Precision Agriculture 269 R. Gebbers and S. de Bruin 11.1 Introduction Basics of Geostatistical Simulation Theory Sequential Gaussian Simulation Transformation of Probability Distributions Case Study I: Uncertainty of a ph Map Introduction Materials and Methods Results and Discussion Summary and Conclusions 286

7 xii Contents 11.3 Case Study II: Uncertainty in the Position of Geographic Objects Introduction Methods Study Site Conclusions Case Study III: Uncertainty Propagation in Soil Mapping Introduction Materials and Methods Results and Discussion Conclusions Application of Geostatistical Simulation in Precision Agriculture: Summary 300 References Geostatistics and Precision Agriculture: A Way Forward 305 J.K. Schueller 12.1 Introduction Weather, Time and Space Farmers, Advisors and Researchers Issues, Ideas and Questions Past, Present and Future 312 References 312 Appendix: Software 313 A.I Geostatistics in GenStat 313 A.2 VESPER 315 A.2.1 Background 315 A.2.2 The Software 316 A.2.3 Applications 320 A.3 SGeMS and Other Software 321 A.3.1 SGeMS 321 A.3.2 Other Software 322 References 322 Index 325