Proximal Soil Sensing (Progress in Soil Science)

✍ Scribed by Raphael A. Viscarra Rossel (editor), Alex B. McBratney (editor), Budiman Minasny (editor)

• Publisher: Springer
• Year: 2010
• Tongue: English
• Leaves: 440
• Category: Library

✦ Synopsis

This book reports on developments in Proximal Soil Sensing (PSS) and high resolution digital soil mapping. PSS has become a multidisciplinary area of study that aims to develop field-based techniques for collecting information on the soil from close by, or within, the soil. Amongst others, PSS involves the use of optical, geophysical, electrochemical, mathematical and statistical methods. This volume, suitable for undergraduate course material and postgraduate research, brings together ideas and examples from those developing and using proximal sensors and high resolution digital soil maps for applications such as precision agriculture, soil contamination, archaeology, peri-urban design and high land-value applications, where there is a particular need for high spatial resolution information. The book in particular covers soil sensor sampling, proximal soil sensor development and use, sensor calibrations, prediction methods for large data sets, applications of proximal soil sensing, and high-resolution digital soil mapping.

Key themes: soil sensor sampling – soil sensor calibrations – spatial prediction methods – reflectance spectroscopy – electromagnetic induction and electrical resistivity – radar and gamma radiometrics – multi-sensor platforms – high resolution digital soil mapping - applications

Raphael A. Viscarra Rossel is a scientist at the Commonwealth Scientific and Industrial Research Organisation (CSIRO) of Australia.

Alex McBratney is Pro-Dean and Professor of Soil Science in the Faculty of Agriculture Food & Natural Resources at the University of Sydney in Australia.

Budiman Minasny is a Senior Research Fellow in the Faculty of Agriculture Food & Natural Resources at the University of Sydney in Australia.

✦ Table of Contents

Foreword
Proximal Soil Sensing: Looking, Touching, Feeling
Preface
Acknowledgements
Contents
About the Editors
Contributors
Part I Overview
1 Sampling for High-Resolution Soil Mapping
1.1 Introduction
1.2 Materials and Methods
1.2.1 Sensor Sampling: Some Theory
1.2.1.1 Optimisation for Equipment Type A
1.2.1.2 Optimisation for Equipment Type B
1.2.2 Sensor Sampling: Some Experiments
1.2.3 Calibration Sampling
1.2.3.1 Latin Hypercube Sampling
1.2.3.2 Sampling by Response Surface Methodology
1.2.3.3 Model-Based Sampling for Universal Kriging
1.2.3.4 Sampling by Fuzzy Cluster Analysis
1.3 Results and Discussion
1.4 Conclusions
References
2 Development of On-the-Go Proximal Soil Sensor Systems
2.1 Introduction
2.2 Sensor Development Review
2.2.1 Electrical and Electromagnetic Sensors
2.2.2 Optical and Radiometric Sensors
2.2.3 Mechanical Sensors
2.2.4 Acoustic and Pneumatic Sensors
2.2.5 Electrochemical Sensors
2.3 Sensor Applications
2.3.1 Multisensor Data Fusion
2.3.2 Sensor Deployment
2.4 Conclusions
References
3 Diffuse Reflectance Spectroscopy for High-Resolution Soil Sensing
3.1 Introduction
3.2 Fundamentals of Diffuse Reflectance Spectroscopy
3.3 Soil Diffuse Reflectance Spectra
3.3.1 Vis--NIR
3.3.2 Mid-IR
3.4 Mathematical Preprocessing of Spectra
3.5 Spectroscopic Multivariate Calibrations
3.6 Spectroscopic Calibrations for Predictions of Soil Properties
3.6.1 Visible--Near-Infrared (Vis--NIR) Calibrations
3.6.2 Mid-Infrared (Mid-IR) Calibrations
3.6.3 Generalisation and Limitations of Spectroscopic Calibrations
3.7 Proximal Soil Sensing Using Portable Spectrometers
3.8 Conclusions
References
4 High-Resolution Digital Soil Mapping: Kriging for Very Large Datasets
4.1 Introduction
4.2 Spatial Covariance Function
4.3 Kriging: Optimal Linear Spatial Prediction
4.4 Soil Properties on a Portion of Nowley Farm, New South Wales, Australia
4.5 Conclusions
References
Part II Soil Sensing and Sampling
5 The Sun Has Shone Here Antecedently
5.1 Introduction
5.2 High-Resolution Digital Soil Sensing and Mapping
5.3 The Precocious and Prescient Contribution of Haines and Keen
5.3.1 The Rationale: Cultivation and Soil Strength
5.3.2 The Sensor: A (Pre-electronic) Design for a Soil Draught Force Sensor
5.3.3 Data Logging: Analogue Data Recording
5.3.4 Data Analysis: Spatial Variation and Data Filtering
5.3.5 The Product: The First High-Resolution Digital Soil Map
5.4 Degrees of Separation
5.5 Conclusions
References
6 Proximal Soil Nutrient Sensing Using Electrochemical Sensors
6.1 Introduction
6.2 Proximal Soil Sensing Using Electrochemical Sensors
6.2.1 Electrochemical Sensors
6.2.2 Soil Nutrient Analysis Using Electrochemical Sensors
6.2.3 PSS: Stationary In Situ Analysis
6.2.4 PSS: On-the-Go
6.2.4.1 Direct Soil Measurement
6.2.4.2 Agitated Soil Measurement (ASM)
6.2.4.3 Batch/Chamber-Based Methods
6.2.4.4 Flow Injection Analysis (FIA)
6.2.5 Addressing Limitations of Electrochemical Sensors for Proximal Soil Sensing
6.3 Conclusions
References
7 DIGISOIL: An Integrated System of Data Collection Technologies for Mapping Soil Properties
7.1 Introduction
7.2 Objectives
7.3 Strategy and Workplan
7.4 From Soil Threats to Geophysical Properties
7.5 Conclusions
References
8 iSOIL: An EU Project to Integrate Geophysics, Digital Soil Mapping, and Soil Science
8.1 Introduction
8.2 General Objectives
8.3 Motivation of the Project
8.3.1 Development of Geophysical Techniques
8.3.2 Development of Geophysical Transfer Functions
8.3.3 Digital Soil Mapping
8.4 Structure of the Project
8.5 Conclusions
References
9 Conditioned Latin Hypercube Sampling for Calibrating Soil Sensor Data to Soil Properties
9.1 Introduction
9.2 Theory
9.3 Applications
9.4 Results and Discussion
References
10 Response Surface Sampling of Remotely Sensed Imagery for Precision Agriculture
10.1 Introduction
10.2 Material and Methods
10.2.1 Remote Sensing and Image Processing
10.2.2 Directed Sampling
10.2.3 Ground Sampling
10.2.4 Statistical Analysis and Mapping
10.3 Results and Discussion
10.4 Conclusions
References
Part III Soil UV, Visible, and Infrared Spectral Sensing
11 Mid- Versus Near-Infrared Spectroscopy for On-Site Analysis of Soil
11.1 Introduction
11.2 Materials and Methods
11.2.1 Soil Samples
11.2.2 Compositional Determination
11.2.3 Fourier Transform Spectrometer (FTS)
11.2.4 Non-FTS NIR Spectroscopy
11.2.5 Chemometrics
11.3 Results and Discussion
11.4 Conclusions
References
12 Determination of Soil Nitrate and Organic Matter Content Using Portable, Filter-Based Mid-Infrared Spectroscopy
12.1 Introduction
12.2 Materials and Methods
12.2.1 FTIR/ATR Spectrometer Tests
12.2.2 Portable Filter-Based Spectrometer Tests
12.2.2.1 Nitrate Experiments
12.2.2.2 Organic Matter Experiments
12.3 Results and Discussion
12.3.1 FTIR/ATR Spectrometer Test Results
12.3.2 Filter-Based Spectrometer Test Results
12.3.2.1 Nitrate Results
12.3.2.2 Organic Matter Results
12.4 Conclusions
References
13 VNIR Spectroscopy Estimates of Within-Field Variability in Soil Properties
13.1 Introduction
13.2 Materials and Methods
13.2.1 Study Site and Soil Sampling
13.2.2 Spectral Data Acquisition
13.2.3 Analysis Procedures
13.3 Results and Discussion
13.3.1 Variability in Soil Properties
13.3.2 Predictive Capability of Spectral Regions
13.3.3 Regression Kriging
13.4 Conclusions
References
14 Infrared Sensors to Map Soil Carbon in Agricultural Ecosystems
14.1 Introduction
14.2 Materials and Methods
14.2.1 Soil Samples
14.2.2 Spectral Measurements
14.2.2.1 Airborne Measurements
14.2.2.2 Proximal Measurements
14.2.2.3 Laboratory Measurements
14.2.3 Chemometrics
14.3 Results and Discussion
14.3.1 Calibration and Validation
14.3.2 Potential for Optimising Sampling Design
14.3.3 Remote Sensing of Soil Carbon
14.4 Conclusions
References
15 Predicting Soil Carbon and Nitrogen Concentrations and Pasture Root Densities from Proximally Sensed Soil Spectral Reflectance
15.1 Introduction
15.2 Materials and Methods
15.2.1 Contact Probe Modification and Measurement Techniques
15.2.2 Site Locations and Sample Collection
15.2.3 Measurement of Soil Properties
15.2.4 Spectral Pre-processing and Data Analysis
15.2.5 Regression Model Accuracy
15.3 Results and Discussion
15.3.1 C and N Prediction of Taupo--Rotorua Allophanic, Pumice, and Tephric Recent Soil
15.3.2 Comparison Between H and V Method for Fluvial Recent Soil
15.3.3 Vertical Method on Fluvial Recent Soil Collected in Autumn (May)
15.3.4 Is the Calibration Model Influenced by Temporal Variations in the Soil?
15.3.5 Root Density Prediction on Ramiha and Manawatu Soil
15.4 Conclusions
References
16 Diagnostic Screening of Urban Soil Contaminants Using Diffuse Reflectance Spectroscopy
16.1 Introduction
16.2 Materials and Methods
16.2.1 Location
16.2.2 Diffuse Spectral Reflectance Measurements
16.2.3 Statistical Analysis
16.2.4 Diagnostic Screening of Soil Contaminants
16.3 Results and Discussion
16.3.1 Exploratory Data Analysis
16.3.2 Spectroscopic Analysis
16.3.3 Diagnostic Screening Using Ordinal Logistic Regression
16.4 Conclusions
References
17 Using Wavelets to Analyse Proximally Sensed Vis--NIRSoil Spectra
17.1 Introduction
17.2 Materials and Methods
17.2.1 The Soil Spectral Library
17.2.2 Proximal Vis--NIR Sensing of Soil Profiles
17.2.3 The Wavelet Transform
17.2.4 Multivariate Calibrations
17.3 Results
17.3.1 The Soil Vis--NIR Spectral Library and Validation Samples
17.3.2 A Multiresolution Analysis (MRA)
17.3.3 The Wavelet Transform for Data Compression and Multivariate Calibrations
17.3.4 Denoising by Back-Transforming the Wavelet Coefficients
17.4 Discussion
17.5 Conclusions
References
18 Mapping Soil Surface Mineralogy at Tick Hill, North-Western Queensland, Australia, Using Airborne Hyperspectral Imagery
18.1 Introduction
18.2 Tick Hill Study Area
18.3 Materials and Methods
18.3.1 Geoscience Mapping Data and Processing
18.3.2 Airborne HyMap Data Processing for Mineral Mapping
18.3.3 Field Samples and Related Laboratory Analyses
18.3.4 Field Validation of Airborne Mineral-Mapping Results
18.4 Results and Discussion
18.4.1 Field Samples
18.4.2 Airborne Versus Field Spectra
18.4.3 Mineral Group Abundances
18.4.4 Clay Mineral Abundances
18.4.5 Clay Mineral Physicochemistry
18.4.6 Other Products
18.4.7 Integrated Mineral Analysis
18.5 Conclusions
References
Part IV Soil Sensing by Electromagnetic Induction and Electrical Resistivity
19 Combining Proximal and Penetrating Soil Electrical Conductivity Sensors for High-Resolution Digital Soil Mapping
19.1 Introduction
19.2 Materials and Methods
19.2.1 Soil Landscapes, Measurements, and Observations
19.2.2 ECa--P Measurement
19.2.3 ECa--M Measurement
19.2.4 Proximal ECa Measurement
19.3 Results and Discussion
19.3.1 Soil Profile ECa
19.3.2 ECa--P Predicted Depth to Claypan
19.3.3 Calibrating ECa to ECa--P Features
19.3.4 Profile Sources of Proximal ECa
19.4 Conclusions
References
20 A Neural Network Approach to Topsoil Clay Prediction Using an EMI-Based Soil Sensor
20.1 Introduction
20.2 Materials and Methods
20.2.1 Study Site and Data Collection
20.2.2 Neural Network Analysis
20.2.3 Multivariate Linear Regression
20.3 Results and Discussion
20.4 Conclusions
References
21 Field Determination of Soil Moisture in the Root Zone of Deep Vertosols Using EM38 Measurements: Calibration and Application Issues
21.1 Introduction
21.2 Materials and Methods
21.2.1 Study Area
21.2.2 EM38 Depth--Response Function
21.2.3 Field Calibration and Prediction of Average Moisture Content at Depth
21.3 Results and Discussion
21.4 Conclusions
References
22 Can the EM38 Probe Detect Spatial Patterns of Subsoil Compaction?
22.1 Introduction
22.2 Materials and Methods
22.2.1 Measurement of Penetration Resistance (PR)
22.2.2 Measurement of Apparent Electrical Conductivity (ECa)
22.2.3 Study Sites
22.3 Results and Discussion
22.4 Conclusions
References
23 Changes in Field Soil Water Tracked by Electrical Resistivity
23.1 Introduction
23.2 Materials and Methods
23.2.1 Characteristics of the Soils Studied
23.2.2 Soil Water Content Monitoring at the Field Scale
23.2.3 Electrical Monitoring Over Time
23.2.4 Spatial and Temporal Variability Analysis
23.3 Results and Discussion
23.3.1 Statistical Relationship Between Electrical Resistivity and Soil Water Content
23.3.2 Spatial Analysis of the Experimental Data
23.3.3 Temporal Analysis of the Experimental Data
23.4 Conclusion
References
24 Is a Systematic Two-Dimensional EMI Soil Survey Always Relevant for Vineyard Production Management? A Test on Two Pedologically Contrasting Mediterranean Vineyards
24.1 Introduction
24.2 Materials and Methods
24.2.1 Location, Geology, and Pedology
24.2.2 Geophysical Surveys
24.2.3 Soil Survey
24.2.4 NDVI Maps of Vine Vigour and Map Comparison
24.3 Results
24.3.1 Relations Between NDVI, Soil, and ECa
24.3.2 Differences Between Different ECa Measurements
24.3.2.1 Erratic Shifting with Mobile EMI
24.3.2.2 Comparison Between R--ECa and I--ECa
24.3.3 Electrical Conductivity of Different Soils and Materials in the Two Blocks
24.3.4 Soil Type Detection with R--ECa Data
24.4 Discussion and Conclusions
References
Part V Radar and Gamma Radiometric Sensors
25 Full-Waveform Modelling and Inversion of Ground-Penetrating Radar Data for Non-invasive Characterisation of Soil Hydrogeophysical Properties
25.1 Introduction
25.2 Ground-Penetrating Radar
25.3 Full-Waveform Analysis of Proximal GPR Data
25.3.1 GPR Forward Modelling
25.3.1.1 Antenna Equation in the Frequency Domain
25.3.1.2 Zero-Offset Green's Function for Multilayered Media
25.3.2 Model Inversion
25.3.3 Model Validation and Applications
25.4 Conclusions
References
26 Using Proximal Sensors to Continuously Monitor Agricultural Soil Physical Conditions for Tillage Management
26.1 Introduction
26.2 Materials and Methods
26.2.1 Description of the Sensors
26.2.2 Field Experiment
26.2.3 Data Acquisition
26.3 Results and Discussion
26.3.1 Soil Physical Conditions
26.3.2 Radar Data
26.3.3 Capacitance Probe
26.3.4 Mechanical Resistance Probe
26.3.5 Tillage Effects on Seedling Emergence
26.4 Conclusions
References
27 Gamma Ray Sensor for Topsoil Mapping: The Mole
27.1 Introduction
27.2 Equipment and Data Analysis Methods
27.2.1 Hardware
27.2.2 Spectral Data Analysis
27.2.3 Fingerprinting and Soil Sampling
27.3 Applications
27.4 Future Developments
27.5 Conclusions
References
28 Gamma Ray Sensing for Cadmium Risk Assessment in Agricultural Soil and Grain: A Case Study in Southern Sweden
28.1 Introduction
28.2 Materials and Methods
28.3 Results and Discussion
28.4 Conclusions
References
29 Use of EM38 and Gamma Ray Spectrometry as Complementary Sensors for High-Resolution Soil Property Mapping
29.1 Introduction
29.2 Materials and Methods
29.2.1 Location and Soil
29.2.2 EM38 and γ-Radiometric Survey
29.2.3 Sensor Response and Interpretation
29.3 Results and Discussion
29.4 Conclusions
References
Part VI Multisensor Systems and Other Sensors
30 Field-Scale Draught Resistance and Soil Moisture Measurement in Australia Using a Tine-Based ForceCapacitance Sensing System
30.1 Introduction
30.2 Materials and Methods
30.3 Results and Discussion
30.3.1 Transect
30.3.2 Whole Paddock
30.4 Conclusions
References
31 Sensor-Based Mapping of Soil Quality on Degraded Claypan Landscapes of the Central United States
31.1 Introduction
31.2 Materials and Methods
31.2.1 Soil ECa
31.2.2 Yield Mapping
31.2.3 Claypan Hydraulic Properties
31.2.4 Soil Compaction
31.3 Results and Discussion
31.3.1 Claypan Topsoil Depth
31.3.2 Claypan Hydraulic Properties
31.3.3 Soil Organic Carbon
31.3.4 Nutrients
31.3.5 Soil Compaction
31.4 Conclusions
References
32 Proximal Sensing Methods for Mapping Soil Water Status in an Irrigated Maize Field
32.1 Introduction
32.2 Materials and Methods
32.2.1 Study Site
32.2.2 Electromagnetic Induction Mapping and Soil AWC
32.2.3 Soil Moisture Measurement
32.2.3.1 Time Domain Reflectometry (TDR)
32.2.3.2 Collection of Vis--NIR Soil Reflectance Spectra
32.2.3.3 Spectral Data Pre-processing
32.3 Results and Discussion
32.3.1 Electromagnetic Induction Mapping and Soil AWC
32.3.2 Soil Moisture Measurements
32.3.3 Vis--NIR Soil Reflectance Spectra
32.4 Conclusions
References
33 Comparing the Ability of Multiple Soil Sensors to Predict Soil Properties in a Scottish Potato Production System
33.1 Introduction
33.2 Materials and Methods
33.2.1 On-the-Go Soil Survey
33.2.2 Manual Soil Sampling
33.2.3 Multivariate Data Analysis
33.3 Results and Discussion
33.3.1 Comparison of the Usefulness of Individual Sensors
33.3.2 Multi-sensors vs. Single Sensor
33.3.3 Discussion
33.3.4 Other Considerations
33.4 Conclusions
References
34 Spatial Variability and Pattern of Selected Properties of Agricultural Soils in the Czech Republic Measured by Indirect Proximal and Remote Sensing
34.1 Introduction
34.2 Materials and Methods
34.2.1 Experimental Field Description
34.2.2 Soil Sampling and Soil Property Determination
34.2.3 Proximal and Remote Measurement Methods
34.2.4 Data Evaluation, Statistical, and Geostatistical Analyses
34.3 Results and Discussion
34.3.1 Geostatistical Analysis
34.3.2 Discussion
34.4 Conclusions
References
Part VII Applications
35 Inverse Meta-modelling of Yield-Monitor Data for Estimating Soil-Available Water-Holding Capacities at a Farm Resolution of 10 m
35.1 Introduction
35.2 Materials and Methods
35.2.1 Key Assumptions
35.2.2 Study Site and Available Data
35.2.3 Creating a Meta-model
35.2.4 Estimating 'Effective' Hydraulic Properties
35.2.5 Validating 'Effective' AWCs
35.3 Results and Discussion
35.4 Conclusions
References
36 Reconstructing Palaeotopography at the Beginning of the Weichselian Glacial Stage Using an Electromagnetic Induction Sensor
36.1 Introduction
36.2 Materials and Methods
36.2.1 Study Site
36.2.2 Electromagnetic Induction Sensing
36.2.3 Mobile ECa Measurement Equipment and ECa Mapping
36.2.4 Depth to Tertiary Clay Observations
36.2.5 Relationship Between ECa-V and Depth to Tertiary Clay
36.2.6 Relationship Between the Combined ECa-V and ECa-H and Depth to Tertiary Clay
36.3 Results and Discussion
36.3.1 Relationship Between ECa-V and Depth to Tertiary Clay
36.3.2 Relationship Between the Combined ECa-V and ECa-H and Depth to Tertiary Clay
36.3.3 Validation of Predicted Depth of Tertiary Clay
36.3.4 Palaeotopography Beneath the Loess Cover
36.4 Conclusions
References
Postscript: Where to from Here?
Soil Sensing and Sampling
Future Work
Soil UV, Visible, and Infrared Spectral Sensing
Future Work
Soil Sensing by Electromagnetic Induction and Electrical Resistivity
Future Work
Radar and Gamma Radiometric Sensors
Future Work
Multi-sensor Systems and Other Sensors
Future Work
Applications
Future Work
Initiatives
FP7 Projects iSoil and Digisoil
IUSS WG-PSS
Global Soil Spectral Library
Index