This chapter provides a review on the state of soil visible–near infrared (vis–NIR) spectroscopy Our intention is for the review to serve as a source of up-to-date information on the past and current role of vis–NIR spectroscopy in soil science It should also provide critical discussion on issues surrounding the use of vis–NIR for soil analysis and on future directions To this end, we describe the fundamentals of visible and infrared diffuse reflectance spectroscopy and spectroscopic multivariate calibrations A review of the past and current role of vis–NIR spectroscopy in soil analysis is provided, focusing on important soil attributes such as soil organic matter (SOM), minerals, texture, nutrients, water, pH, and heavy metals We then discuss the performance and generalization capacity of vis–NIR calibrations, with particular attention on sample pretratments, covariations in data sets, and mathematical data preprocessing Field analyses and strategies for the practical use of vis–NIR are considered We conclude that the technique is useful to measure soil water and mineral composition and to derive robust calibrations for SOM and clay content Many studies show that we also can predict properties such as pH and nutrients, although their robustness may be questioned For future work we recommend that research should focus on: (i) moving forward with more theoretical calibrations, (ii) better understanding of the complexity of soil and the physical basis for soil reflection, and (iii) applications and the use of spectra for soil mapping and monitoring, and for making inferences about soils quality, fertility and function To do this, research in soil spectroscopy needs to be more collaborative and strategic The development of the Global Soil Spectral Library might be a step in the right direction

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Visible and Near Infrared Spectroscopy in Soil Science

https://romisatriawahono.net/lecture/rm/survey/machine%20learning/Wozniak%20-%20Multiple%20Classifier%20Systems%20-%202014.pdf

A survey of multiple classifier systems as hybrid systems

Mining data with random forests: A survey and results of new tests

The remarkable complexity of soil and its importance to a wide range of ecosystem services presents major challenges to the modeling of soil processes. Although major progress in soil models has occurred in the last decades, models of soil processes remain disjointed between disciplines or ecosystem services, with considerable uncertainty remaining in the quality of predictions and several challenges that remain yet to be addressed. First, there is a need to improve exchange of knowledge and experience among the different disciplines in soil science and to reach out to other Earth science communities. Second, the community needs to develop a new generation of soil models based on a systemic approach comprising relevant physical, chemical, and biological processes to address critical knowledge gaps in our understanding of soil processes and their interactions. Overcoming these challenges will facilitate exchanges between soil modeling and climate, plant, and social science modeling communities. It will allow us to contribute to preserve and improve our assessment of ecosystem services and advance our understanding of climate-change feedback mechanisms, among others, thereby facilitating and strengthening communication among scientific disciplines and society. We review the role of modeling soil processes in quantifying key soil processes that shape ecosystem services, with a focus on provisioning and regulating services. We then identify key challenges in modeling soil processes, including the systematic incorporation of heterogeneity and uncertainty, the integration of data and models, and strategies for effective integration of knowledge on physical, chemical, and biological soil processes. We discuss how the soil modeling community could best interface with modern modeling activities in other disciplines, such as climate, ecology, and plant research, and how to weave novel observation and measurement techniques into soil models. We propose the establishment of an international soil modeling consortium to coherently advance soil modeling activities and foster communication with other Earth science disciplines. Such a consortium should promote soil modeling platforms and data repository for model development, calibration and intercomparison essential for addressing contemporary challenges.

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Modeling Soil Processes: Review, Key Challenges, and New Perspectives

This review addresses the applicability of visible (Vis), near-infrared (NIR), and mid-infrared (MIR) reflectance spectroscopy for the prediction of soil properties. We address (1) the properties that can be predicted and the accuracy of the predictions, (2) the most suitable spectral regions for specific soil properties, (3) the number of predictions reported for each property, and (4) in-field versus laboratory spectral techniques.We found the following properties to be successfully predicted: soil water content, texture, soil carbon (C), cation exchange capacity, calcium and magnesium (exchangeable), total nitrogen (N), pH, concentration of metals/metalloids, microbial size, and activity. Generally, MIR produced better predictions than Vis-NIR, but Vis-NIR outperformed MIR for a number of properties (e.g., biological). An advantage of Vis-NIR is instrument portability although a new range of MIR portable devices is becoming available. In-field predictions for clay, water, total organic C, extra...

The Performance of Visible, Near-, and Mid-Infrared Reflectance Spectroscopy for Prediction of Soil Physical, Chemical, and Biological Properties

Geophysical instruments show great potential for the detailed quantification of soil stratigraphy. In this study, two electromagnetic induction sensors were evaluated on their capacity to map small-scale variations of the depth to the interface (z in ) in a two-layered soil. On a 2-ha study site, z in between the silty topsoil and the contrasting clayey subsoil was modeled first by relating the two apparent electrical conductivity (EC a ) measurements of the EM38DD sensor to observations of z in obtained by augering. A substantial number of these calibration observations was needed, however, to account for the modeling parameters. To avoid this step, an entirely noninvasive procedure was proposed based on one survey with the DUALEM-21S sensor. This sensor simultaneously records four EC a values with different coil configurations. These measurements correspond to four different depth response functions that allow modeling z in without calibration observations. The only assumption was a two-layered soil profile. The z in predictions were validated with 24 independent depth observations. Both procedures resulted in equal correlation coefficients (0.85) between predicted and measured z in and average estimation errors (0.26 m). This indicated that both sensors allowed the accurate mapping of the depth to a contrasting textural layer. With the EM38DD, calibration observations are needed, whereas the four different coil conurations of the DUALEM-21S sensor provided sufficient information to predict the interface depth without augering.

Comparing the EM38DD and DUALEM-21S Sensors for Depth-to-Clay Mapping

Key soil and topographic properties to delineate potential management classes for precision agriculture in the European loess area

On-line measurement of soil properties using the visible (Vis) and near infrared (NIR) spectroscopy is sensitive to soil-to-sensor distance ( D ) and angle ( α ) variations, which have prevented the successful development of on-line soil sensors so far. This study was undertaken to minimise these variations through optimising the three-point linkage of the tractor to improve the quality of soil spectra and the accuracy of plant available phosphorus (P-avl) measured with an on-line soil sensor. The sensor consisted of a tine, to the back of which an optical probe was attached to acquire soil spectra in diffuse reflectance mode from the bottom of the trench opened by the tine. A mobile, fibre-type, Vis–NIR spectrophotometer (Zeiss Corona 45 visnir fibre, Germany), with a measurement range of 306.5–1710.9 nm was used. Five lengths of the third point link ( L ) of the tractor of 545, 550, 555, 560 and 565 mm were selected to evaluate the quality of spectra collected on-line at 0.15 m tine depth. The on-line measured spectra were corrected to remove the effect of D and α . The correction was evaluated by estimating the accuracy of predicting P-avl using on-line measured spectra and a previously developed P-avl calibration model. Results showed that the best quality of spectra measured on-line was obtained for L of 555 mm, at which D and α vanished. This finding was supported by the maximum value of average maximum reflectance (AMR) of 75.7% obtained and by 100% successfully collected spectra. The worst quality of spectra was obtained at L of 545 mm, with the largest D of 6 mm and the largest α of 0.6°. Values of L of 560 and 565 mm led to a decrease in the AMR (43.3 and 33.2%, respectively), while recording 100% successful spectra. Correction of on-line measured spectra led to clear improvements in the accuracy of on-line measured P-avl. A lower root mean square error (RMSE) of 1.07 mg 100 g −1 and higher ratio of prediction deviations (RPD) of 1.42 were obtained with corrected spectra as compared to uncorrected spectra (RMSE = 1.15 and RPD = 1.39). In addition, the correction of spectra resulted in an increase in the degree of similarity between laboratory and on-line measured P-avl maps by 29.6%. These results suggest the need for optimising the tractor hydraulic three-point linkage set up, and for spectra correction in order to improve the accuracy of on-line measured soil properties.

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Optimum three-point linkage set up for improving the quality of soil spectra and the accuracy of soil phosphorus measured using an on-line visible and near infrared sensor

A pedotransfer function to evaluate the soil profile textural heterogeneity using proximally sensed apparent electrical conductivity

The multiple coil configurations of two electromagnetic induction sensors were tested on afield with strong electrical and magnetic contrasts. The first sensor, EM38DD, measures either the apparent electrical conductivity (ECa or sigma(a)) or the apparent magnetic susceptibility (MSa or chi(a)) of the soil at two coil orientations. The second sensor, DUALEM-21S, measures both ECa and MSa at two coil orientations and two coil separations. The goal was to test if measuring with the multiple coils resulted in a better detection of near-surface artefacts and the natural soil variability. The ECa of all coil configurations was closely related to the depth of a clay substrate beneath the topsoil sandy loam, which was verified by soil augering. Configurations with a shallower theoretical depth of exploration were less influenced by the clay substrate. Combining two coil configurations revealed important ECa anomalies, not visible on individual measurements, associated with a brick wall foundation and a former ditch. The MSa maps showed totally different anomaly patterns, related to anthropogenic disturbances in the soil, such as the filling-in with brick rubble of a former pond. Depending on the depth and thickness of the disturbance and the relative response of the sensor configurations, the MSa anomalies were entirely positive for one configuration but other configurations also had negative anomalies. It was concluded that multiple coil configurations provide a better insight into the buildup of the soil profile and are better able to detect anomalies than single measurements.

L. Cockx

Papers

Comparing the EM38DD and DUALEM-21S Sensors for Depth-to-Clay Mapping

Key soil and topographic properties to delineate potential management classes for precision agriculture in the European loess area

Optimum three-point linkage set up for improving the quality of soil spectra and the accuracy of soil phosphorus measured using an on-line visible and near infrared sensor

A pedotransfer function to evaluate the soil profile textural heterogeneity using proximally sensed apparent electrical conductivity

Evaluating the multiple coil configurations of the EM38DD and DUALEM‐21S sensors to detect archaeological anomalies