In situ measurements of soil colour, mineral composition and clay content by vis–NIR spectroscopy

Rossel, Raphael A. Viscarra; Cattle, Stephen R.; Ortega, A.S.; Fouad, Youssef

doi:10.1016/j.geoderma.2009.01.025

Cited by 390 publications

(205 citation statements)

References 40 publications

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“…Although the technique is mainly used under controlled laboratory conditions, with the rise in available portable spectrometers, its application in situ [5], as well as from the air-and space-borne sensors, is growing [6,7]. Under in-situ measurement conditions, additional challenges associated with the variation of soil-to-sensor distance affect the accuracy of the measurement [8,9].…”

Section: Introductionmentioning

confidence: 99%

Agricultural Soil Spectral Response and Properties Assessment: Effects of Measurement Protocol and Data Mining Technique

et al. 2017

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Abstract:Soil spectroscopy has shown to be a fast, cost-effective, environmentally friendly, non-destructive, reproducible and repeatable analytical technique. Soil components, as well as types of instruments, protocols, sampling methods, sample preparation, spectral acquisition techniques and analytical algorithms have a combined influence on the final performance. Therefore, it is important to characterize these differences and to introduce an effective approach in order to minimize the technical factors that alter reflectance spectra and consequent prediction. To quantify this alteration, a joint project between Czech University of Life Sciences Prague (CULS) and Tel-Aviv University (TAU) was conducted to estimate Cox, pH-H 2 O, pH-KCl and selected forms of Fe and Mn. Two different soil spectral measurement protocols and two data mining techniques were used to examine seventy-eight soil samples from five agricultural areas in different parts of the Czech Republic. Spectral measurements at both laboratories were made using different ASD spectroradiometers. The CULS protocol was based on employing a contact probe (CP) spectral measurement scheme, while the TAU protocol was carried out using a CP measurement method, accompanied with the internal soil standard (ISS) procedure. Two spectral datasets, acquired from different protocols, were both analyzed using partial least square regression (PLSR) technique as well as the PARACUDA II ® , a new data mining engine for optimizing PLSR models. The results showed that spectra based on the CULS setup (non-ISS) demonstrated significantly higher albedo intensity and reflectance values relative to the TAU setup with ISS. However, the majority of statistics using the TAU protocol was not noticeably better than the CULS spectra. The paper also highlighted that under both measurement protocols, the PARACUDA II ® engine proved to be a powerful tool for providing better results than PLSR. Such initiative is not only a way to unlock current limitations of soil spectroscopy, but also offers considerable efficiency and cost-and time-saving possibilities, which lead to further improvements in prediction performance of spectral models.

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Section: Introductionmentioning

confidence: 99%

Agricultural Soil Spectral Response and Properties Assessment: Effects of Measurement Protocol and Data Mining Technique

et al. 2017

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“…Many studies report about the accuracy of predictions based on reflectance as for SOC, clay, carbonate content, pH etc. (Brodsky et al, 2011;Viscarra Rossel et al, 2009). These studies compared many soil samples from very different environmental circumstances using partial least squares regression method and resulted in relatively high R 2 values.…”

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confidence: 99%

Redistribution of Soil Organic Carbon Triggered by Erosion at Field Scale Under Subhumid Climate, Hungary

et al. 2016

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Soil organic carbon (SOC) has primary importance in terms of soil physics, fertility and even of climate change control. An intensively cultivated Cambisol was studied in order to quantify SOC redistribution under subhumid climate. One hundred soil samples were taken from the representative points of the solum along the slopes from the depth of 20-300 cm with a mean 1.2 % SOC content. They were measured by the simultaneous application of diffuse reflectance (240-1900 nm) and traditional physico-chemical methods in order to compare the results. On the basis of the results hierarchical cluster analyses were performed. The spatial pattern of the groups created were similar, and even though the classifications were not the same, diffuse reflectance has proven to be a suitable method for soil/sediment classification even within a given arable field. Both organic and inorganic carbon distribution was found a proper tool for estimations of past soil erosion process. Results show SOC enrichment on two sedimentary spots with different geomorphological positions. Soil organic matter compound also differs between the two spots due to selective deposition of the delivered organic matter. The components of low molecular weight reach the bottom of the slope and there can leach into the profile, while the more polymerised organic matter compounds are delivered and deposited even before, on a higher segment of the slope in an aggregated form. This spatial difference appears below the uppermost tilled soil layer as well; referring the lower efficiency of conventional ploughing tillage in spatial soil homogenisation.

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“…• sand, silt and clay content: near and mid infrared spectrometry (Lagacherie et al, 2008;Viscarra Rossel et al, 2009), γ-ray spectroscopy (Pracilio et al, 2006;Viscarra Rossel et al, 2007;Van der Klooster et al, 2011), electromagnetic induction methods (Triantafilis and Lesch, 2005;Cockx et al, 2009) • organic matter content: near and mid infrared spectrometry (Shonk et al, 1991;Ben-Dor et al, 2008) • water content: near and mid infrared spectrometry (Ben-Dor et al, 2008) Validation results of predictions of median grain size of sand fraction (M50) and bulk density by proximal sensing techniques were not found. This overview only focuses on scientifically published studies that included a sound validation of results.…”

Section: Appropriate Techniques For Predicting Soil Hydraulic Propertiesmentioning

confidence: 99%

A selection of sensing techniques for mapping soil hydraulic properties

Knotters

Egmond

Bakker

et al. 2017

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Data on soil hydraulic properties are needed as input for many models, such as models to predict unsaturated water movement and crop growth, and models to predict leaching of nutrients and pesticides to groundwater. The soil physics database of the Netherlands shows several lacunae, and a substantial part of the data were collected more than thirty years ago and thus might not represent actual soil hydraulic conditions. There is a need to fill lacunae in the soil physics dataset, to make the dataset up-to-date and to aggregate soil hydraulic properties observed at point scale to larger spatial units. The relationship between the unsaturated hydraulic conductivity K or the volumetric water content θ and the pressure head h can be described for example by equations such as the Mualem-Van Genuchten equations, the parameter values of which can be predicted from soil properties by using pedo-transfer functions. These soil properties include clay content, loam content, organic matter content and the median grain diameter of the sand fraction (50-2000 µm). Application of proximal sensing techniques in observing soil physics properties in the field might reduce the costs of data collection. The accuracy with which proximal sensing techniques can predict clay content, loam content, organic matter content and the median grain size of the sand fraction (50-2000 µm) needs to be assessed as these are the explanatory variables in the pedo-transfer functions. The aim of this study was to select on-the-go proximal sensing techniques that are able to quantify soil variables that are used in the pedo-transfer functions for prediction of the parameters of the Mualem-Van Genuchten equations. We conclude that near infrared spectrometry, γ-ray spectroscopy and electromagnetic induction methods have a potential in spatial prediction of clay, silt and sand content, and that near infrared spectrometry has a potential in spatial prediction of organic matter content and soil moisture content. The use of pedo-transfer functions requires also the parameters bulk density and median of the sand fraction (M50). Bulk density can be measured by a device called RhoC. However, its performance in predicting bulk density of terrestrial soils has not been validated yet. Most instruments are applied to measure fractions clay, silt and sand. The application of these instruments in the determination of M50 needs to be developed. Possibly the combination of specific surface area and fractions of fine and course sand can give an indication. On the other hand new pedo-transfer functions can be developed neglecting the M50 value while increasing the contribution of other explanatory variables.

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In situ measurements of soil colour, mineral composition and clay content by vis–NIR spectroscopy

Cited by 390 publications

References 40 publications

Agricultural Soil Spectral Response and Properties Assessment: Effects of Measurement Protocol and Data Mining Technique

Agricultural Soil Spectral Response and Properties Assessment: Effects of Measurement Protocol and Data Mining Technique

Redistribution of Soil Organic Carbon Triggered by Erosion at Field Scale Under Subhumid Climate, Hungary

A selection of sensing techniques for mapping soil hydraulic properties

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