A global spectral library to characterize the world’s soil

Soil provides ecosystem services, supports human health and habitation, stores carbon and regulates emissions of greenhouse gases. Unprecedented pressures on soil from degradation and urbanization are threatening agro-ecological balances and food security. It is important that we learn more about so...

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Autores principales: Viscarra Rossel, Raphael A., Behrens, T, Ben-Dor, E., Brown, D.J., Demattê, JAM, Shepherd, Keith D., Shi, Z, Stenberg, B, Stevens, A, Adamchuk, V, Aïchik, H, Barthèsl, BG, Bartholomeus, H.M., Bayer, AD, Bernoux, Martial, Böttchero, K, Brodský, L, Du, CW, Chappell, A, Fouad, Y, Genot, V, Gómez, C., Grunwald, S., Gubler, A, Hedley, CB, Knadel, M, Morrás, HJM, Nocita, M, Ramírez Lopez, L., Roudier, P., Rufasto Campos, EM, Sanborn, P, Sellitto, VM, Sudduth, KA, Rawlins, BG, Walter, C, Winowiecki, Leigh Ann, Hong, SY, Ji, W
Formato: Journal Article
Lenguaje:Inglés
Publicado: Elsevier 2016
Materias:
Acceso en línea:https://hdl.handle.net/10568/70992
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author Viscarra Rossel, Raphael A.
Behrens, T
Ben-Dor, E.
Brown, D.J.
Demattê, JAM
Shepherd, Keith D.
Shi, Z
Stenberg, B
Stevens, A
Adamchuk, V
Aïchik, H
Barthèsl, BG
Bartholomeus, H.M.
Bayer, AD
Bernoux, Martial
Böttchero, K
Brodský, L
Du, CW
Chappell, A
Fouad, Y
Genot, V
Gómez, C.
Grunwald, S.
Gubler, A
Hedley, CB
Knadel, M
Morrás, HJM
Nocita, M
Ramírez Lopez, L.
Roudier, P.
Rufasto Campos, EM
Sanborn, P
Sellitto, VM
Sudduth, KA
Rawlins, BG
Walter, C
Winowiecki, Leigh Ann
Hong, SY
Ji, W
author_browse Adamchuk, V
Aïchik, H
Bartholomeus, H.M.
Barthèsl, BG
Bayer, AD
Behrens, T
Ben-Dor, E.
Bernoux, Martial
Brodský, L
Brown, D.J.
Böttchero, K
Chappell, A
Demattê, JAM
Du, CW
Fouad, Y
Genot, V
Grunwald, S.
Gubler, A
Gómez, C.
Hedley, CB
Hong, SY
Ji, W
Knadel, M
Morrás, HJM
Nocita, M
Ramírez Lopez, L.
Rawlins, BG
Roudier, P.
Rufasto Campos, EM
Sanborn, P
Sellitto, VM
Shepherd, Keith D.
Shi, Z
Stenberg, B
Stevens, A
Sudduth, KA
Viscarra Rossel, Raphael A.
Walter, C
Winowiecki, Leigh Ann
author_facet Viscarra Rossel, Raphael A.
Behrens, T
Ben-Dor, E.
Brown, D.J.
Demattê, JAM
Shepherd, Keith D.
Shi, Z
Stenberg, B
Stevens, A
Adamchuk, V
Aïchik, H
Barthèsl, BG
Bartholomeus, H.M.
Bayer, AD
Bernoux, Martial
Böttchero, K
Brodský, L
Du, CW
Chappell, A
Fouad, Y
Genot, V
Gómez, C.
Grunwald, S.
Gubler, A
Hedley, CB
Knadel, M
Morrás, HJM
Nocita, M
Ramírez Lopez, L.
Roudier, P.
Rufasto Campos, EM
Sanborn, P
Sellitto, VM
Sudduth, KA
Rawlins, BG
Walter, C
Winowiecki, Leigh Ann
Hong, SY
Ji, W
author_sort Viscarra Rossel, Raphael A.
collection Repository of Agricultural Research Outputs (CGSpace)
description Soil provides ecosystem services, supports human health and habitation, stores carbon and regulates emissions of greenhouse gases. Unprecedented pressures on soil from degradation and urbanization are threatening agro-ecological balances and food security. It is important that we learn more about soil to sustainably manage and preserve it for future generations. To this end, we developed and analyzed a global soil visible–near infrared (vis–NIR) spectral library. It is currently the largest and most diverse database of its kind. We show that the information encoded in the spectra can describe soil composition and be associated to land cover and its global geographic distribution, which acts as a surrogate for global climate variability. We also show the usefulness of the global spectra for predicting soil attributes such as soil organic and inorganic carbon, clay, silt, sand and iron contents, cation exchange capacity, and pH. Using wavelets to treat the spectra, which were recorded in different laboratories using different spectrometers and methods, helped to improve the spectroscopic modelling. We found that modelling a diverse set of spectra with a machine learning algorithm can find the local relationships in the data to produce accurate predictions of soil properties. The spectroscopic models that we derived are parsimonious and robust, and using them we derived a harmonized global soil attribute dataset, which might serve to facilitate research on soil at the global scale. This spectroscopic approach should help to deal with the shortage of data on soil to better understand it and to meet the growing demand for information to assess and monitor soil at scales ranging from regional to global. New contributions to the library are encouraged so that this work and our collaboration might progress to develop a dynamic and easily updatable database with better global coverage. We hope that this work will reinvigorate our community's discussion towards larger, more coordinated collaborations. We also hope that use of the database will deepen our understanding of soil so that we might sustainably manage it and extend the research outcomes of the soil, earth and environmental sciences towards applications that we have not yet dreamed of.
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spelling CGSpace709922025-03-13T09:44:20Z A global spectral library to characterize the world’s soil Viscarra Rossel, Raphael A. Behrens, T Ben-Dor, E. Brown, D.J. Demattê, JAM Shepherd, Keith D. Shi, Z Stenberg, B Stevens, A Adamchuk, V Aïchik, H Barthèsl, BG Bartholomeus, H.M. Bayer, AD Bernoux, Martial Böttchero, K Brodský, L Du, CW Chappell, A Fouad, Y Genot, V Gómez, C. Grunwald, S. Gubler, A Hedley, CB Knadel, M Morrás, HJM Nocita, M Ramírez Lopez, L. Roudier, P. Rufasto Campos, EM Sanborn, P Sellitto, VM Sudduth, KA Rawlins, BG Walter, C Winowiecki, Leigh Ann Hong, SY Ji, W soil databases statistical methods spectroscopy machine learning soil chemicophysical properties suelo bases de datos métodos estadísticos espectroscopia aprendizaje electrónico propiedades fisico-químicas suelo Soil provides ecosystem services, supports human health and habitation, stores carbon and regulates emissions of greenhouse gases. Unprecedented pressures on soil from degradation and urbanization are threatening agro-ecological balances and food security. It is important that we learn more about soil to sustainably manage and preserve it for future generations. To this end, we developed and analyzed a global soil visible–near infrared (vis–NIR) spectral library. It is currently the largest and most diverse database of its kind. We show that the information encoded in the spectra can describe soil composition and be associated to land cover and its global geographic distribution, which acts as a surrogate for global climate variability. We also show the usefulness of the global spectra for predicting soil attributes such as soil organic and inorganic carbon, clay, silt, sand and iron contents, cation exchange capacity, and pH. Using wavelets to treat the spectra, which were recorded in different laboratories using different spectrometers and methods, helped to improve the spectroscopic modelling. We found that modelling a diverse set of spectra with a machine learning algorithm can find the local relationships in the data to produce accurate predictions of soil properties. The spectroscopic models that we derived are parsimonious and robust, and using them we derived a harmonized global soil attribute dataset, which might serve to facilitate research on soil at the global scale. This spectroscopic approach should help to deal with the shortage of data on soil to better understand it and to meet the growing demand for information to assess and monitor soil at scales ranging from regional to global. New contributions to the library are encouraged so that this work and our collaboration might progress to develop a dynamic and easily updatable database with better global coverage. We hope that this work will reinvigorate our community's discussion towards larger, more coordinated collaborations. We also hope that use of the database will deepen our understanding of soil so that we might sustainably manage it and extend the research outcomes of the soil, earth and environmental sciences towards applications that we have not yet dreamed of. 2016-04 2016-02-11T20:06:32Z 2016-02-11T20:06:32Z Journal Article https://hdl.handle.net/10568/70992 en Open Access Elsevier Viscarra Rossel, R.A.; Behrens, T.; Ben-Dor, E.; Brown, D.J.; Demattê, J.A.M.; Shepherd, K.D.; Shi, Z.; Stenberg, B.; Stevens, A.; Adamchuk, V.; Aïchik, H.; Barthèsl, B.G.; Bartholomeus, H.M.; Bayer, A.D.; Bernoux, M.; Böttchero, K.; Brodský, L.; Du, C.W.; Chappell, A.; Fouad, Y.; Genot, V.; Gomez, C.; Grunwald, S.; Gubler, A.; Hedley, C.B.; Knadel, M.; Morrás, H.J.M.; Nocita, M.; Ramirez-Lopez, L.; Roudier, P.; Rufasto Campos, E.M.; Sanborn, P.; Sellitto, V.M.; Sudduth, K.A.; Rawlins, B.G.; Walter, C.; Winowiecki, Leigh Ann; Hong, S.Y.; Ji, W.. 2016. A global spectral library to characterize the world’s soil. Earth-Science Reviews 155:198-230.
spellingShingle soil
databases
statistical methods
spectroscopy
machine learning
soil chemicophysical properties
suelo
bases de datos
métodos estadísticos
espectroscopia
aprendizaje electrónico
propiedades fisico-químicas suelo
Viscarra Rossel, Raphael A.
Behrens, T
Ben-Dor, E.
Brown, D.J.
Demattê, JAM
Shepherd, Keith D.
Shi, Z
Stenberg, B
Stevens, A
Adamchuk, V
Aïchik, H
Barthèsl, BG
Bartholomeus, H.M.
Bayer, AD
Bernoux, Martial
Böttchero, K
Brodský, L
Du, CW
Chappell, A
Fouad, Y
Genot, V
Gómez, C.
Grunwald, S.
Gubler, A
Hedley, CB
Knadel, M
Morrás, HJM
Nocita, M
Ramírez Lopez, L.
Roudier, P.
Rufasto Campos, EM
Sanborn, P
Sellitto, VM
Sudduth, KA
Rawlins, BG
Walter, C
Winowiecki, Leigh Ann
Hong, SY
Ji, W
A global spectral library to characterize the world’s soil
title A global spectral library to characterize the world’s soil
title_full A global spectral library to characterize the world’s soil
title_fullStr A global spectral library to characterize the world’s soil
title_full_unstemmed A global spectral library to characterize the world’s soil
title_short A global spectral library to characterize the world’s soil
title_sort global spectral library to characterize the world s soil
topic soil
databases
statistical methods
spectroscopy
machine learning
soil chemicophysical properties
suelo
bases de datos
métodos estadísticos
espectroscopia
aprendizaje electrónico
propiedades fisico-químicas suelo
url https://hdl.handle.net/10568/70992
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