Novel Proximal Sensing for Monitoring Soil Organic C Stocks and Condition

Soil information is needed for environmental monitoring to address current concerns over food, water and energy securities, land degradation, and climate change. We developed the Soil Condition ANalysis System (SCANS) to help address these needs. It integrates an automated soil core sensing system (...

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Main Authors: Viscarra Rossel, Raphael, Lobsey, C., Sharman, C., Flick, P., McLachlan, G.
Format: Journal Article
Published: American Chemical Society 2017
Online Access:http://hdl.handle.net/20.500.11937/74114
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author Viscarra Rossel, Raphael
Lobsey, C.
Sharman, C.
Flick, P.
McLachlan, G.
author_facet Viscarra Rossel, Raphael
Lobsey, C.
Sharman, C.
Flick, P.
McLachlan, G.
author_sort Viscarra Rossel, Raphael
building Curtin Institutional Repository
collection Online Access
description Soil information is needed for environmental monitoring to address current concerns over food, water and energy securities, land degradation, and climate change. We developed the Soil Condition ANalysis System (SCANS) to help address these needs. It integrates an automated soil core sensing system (CSS) with statistical analytics and modeling to characterize soil at fine depth resolutions and across landscapes. The CSS's sensors include a ?-ray attenuation densitometer to measure bulk density, digital cameras to image the measured soil, and a visible-near-infrared (vis-NIR) spectrometer to measure iron oxides and clay mineralogy. The spectra are also modeled to estimate total soil organic carbon (C), particulate, humus, and resistant organic C (POC, HOC, and ROC, respectively), clay content, cation exchange capacity (CEC), pH, volumetric water content, available water capacity (AWC), and their uncertainties. Measurements of bulk density and organic C are combined to estimate C stocks. Kalman smoothing is used to derive complete soil property profiles with propagated uncertainties. The SCANS provides rapid, precise, quantitative, and spatially explicit information about the properties of soil profiles with a level of detail that is difficult to obtain with other approaches. The information gained effectively deepens our understanding of soil and calls attention to the central role soil plays in our environment.
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institution Curtin University Malaysia
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spelling curtin-20.500.11937-741142019-03-25T05:10:24Z Novel Proximal Sensing for Monitoring Soil Organic C Stocks and Condition Viscarra Rossel, Raphael Lobsey, C. Sharman, C. Flick, P. McLachlan, G. Soil information is needed for environmental monitoring to address current concerns over food, water and energy securities, land degradation, and climate change. We developed the Soil Condition ANalysis System (SCANS) to help address these needs. It integrates an automated soil core sensing system (CSS) with statistical analytics and modeling to characterize soil at fine depth resolutions and across landscapes. The CSS's sensors include a ?-ray attenuation densitometer to measure bulk density, digital cameras to image the measured soil, and a visible-near-infrared (vis-NIR) spectrometer to measure iron oxides and clay mineralogy. The spectra are also modeled to estimate total soil organic carbon (C), particulate, humus, and resistant organic C (POC, HOC, and ROC, respectively), clay content, cation exchange capacity (CEC), pH, volumetric water content, available water capacity (AWC), and their uncertainties. Measurements of bulk density and organic C are combined to estimate C stocks. Kalman smoothing is used to derive complete soil property profiles with propagated uncertainties. The SCANS provides rapid, precise, quantitative, and spatially explicit information about the properties of soil profiles with a level of detail that is difficult to obtain with other approaches. The information gained effectively deepens our understanding of soil and calls attention to the central role soil plays in our environment. 2017 Journal Article http://hdl.handle.net/20.500.11937/74114 10.1021/acs.est.7b00889 American Chemical Society restricted
spellingShingle Viscarra Rossel, Raphael
Lobsey, C.
Sharman, C.
Flick, P.
McLachlan, G.
Novel Proximal Sensing for Monitoring Soil Organic C Stocks and Condition
title Novel Proximal Sensing for Monitoring Soil Organic C Stocks and Condition
title_full Novel Proximal Sensing for Monitoring Soil Organic C Stocks and Condition
title_fullStr Novel Proximal Sensing for Monitoring Soil Organic C Stocks and Condition
title_full_unstemmed Novel Proximal Sensing for Monitoring Soil Organic C Stocks and Condition
title_short Novel Proximal Sensing for Monitoring Soil Organic C Stocks and Condition
title_sort novel proximal sensing for monitoring soil organic c stocks and condition
url http://hdl.handle.net/20.500.11937/74114