Remote sensing of the Earth's soil color in space and time

Rodnei Rizzo; Alexandre M.J.C. Wadoux; José A.M. Demattê; Budiman Minasny; Vidal Barrón; Eyal Ben-Dor; Nicolas Francos; Igor Savin; Raul Poppiel; Nelida E.Q. Silvero; Fabrício da Silva Terra; Nícolas Augusto Rosin; Jorge Tadeu Fim Rosas; Lucas Tadeu Greschuk; Maria V.R. Ballester; Andrés Mauricio Rico Gómez; Henrique Belllinaso; José Lucas Safanelli; Sabine Chabrillat; Peterson R. Fiorio; Bhabani Sankar Das; Brendan P. Malone; George Zalidis; Nikolaos Tziolas; Nikolaos Tsakiridis; Konstantinos Karyotis; Nikiforos Samarinas; Eleni Kalopesa; Asa Gholizadeh; Keith D. Shepherd; Robert Milewski; Emmanuelle Vaudour; Changkun Wang; Elsayed Said Mohamed Salama

doi:10.1016/j.rse.2023.113845

Remote sensing of the Earth's soil color in space and time

Rodnei Rizzo, Alexandre M.J.C. Wadoux, José A.M. Demattê^*, Budiman Minasny, Vidal Barrón, Eyal Ben-Dor, Nicolas Francos, Igor Savin, Raul Poppiel, Nelida E.Q. Silvero, Fabrício da Silva Terra, Nícolas Augusto Rosin, Jorge Tadeu Fim Rosas, Lucas Tadeu Greschuk, Maria V.R. Ballester, Andrés Mauricio Rico Gómez, Henrique Belllinaso, José Lucas Safanelli, Sabine Chabrillat, Peterson R. FiorioBhabani Sankar Das, Brendan P. Malone, George Zalidis, Nikolaos Tziolas, Nikolaos Tsakiridis, Konstantinos Karyotis, Nikiforos Samarinas, Eleni Kalopesa, Asa Gholizadeh, Keith D. Shepherd, Robert Milewski, Emmanuelle Vaudour, Changkun Wang, Elsayed Said Mohamed Salama

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

7 Scopus citations

Abstract

Abstract Soil color is a key indicator of soil properties and conditions, exerting influence on both agronomic and environmental variables. Conventional methods for soil color determination have come under scrutiny due to their limited accuracy and reliability. In response to these concerns, we developed an innovative system that leverages 35 years of satellite imagery in conjunction with in-situ soil spectral measurements. This approach enables the creation of a global soil color map with a fine spatial resolution of 30 m x 30 m. The system initially identifies bare earth areas worldwide using reflectance bands acquired from Landsat 4 through Landsat 8 between 1985 and 2020. Soil color was quantified using the CIE-XYZ coordinates, utilizing 8005 soil spectral measurements within the visible range (380–780 nm) as ground truth data. We established transfer functions to convert Landsat reflectance bands to standardized XYZ color coordinates. These transfer functions were subsequently applied to images of bare surfaces, covering approximately 38.5% of the Earth's surface. We validated the resulting global soil color map using statistical indices derived from an independent set of ground-truth spectral data, demonstrating a high degree of agreement. By creating the world's first global soil color map, we have set a baseline for future spatial and temporal monitoring of soil conditions, thus enhancing our understanding and management of our planet's vital soil resources.

Original language	English
Article number	113845
Journal	Remote Sensing of Environment
Volume	299
DOIs	https://doi.org/10.1016/j.rse.2023.113845
State	Published - 15 Dec 2023

Funding

Funders	Funder number
Soil Science Department in Luiz de Queiroz College of Agriculture, University of São Paulo
Fundação de Amparo à Pesquisa do Estado de São Paulo	2014/22262-0, 2016/26176-6, 2018/23760-4
Conselho Nacional de Desenvolvimento Científico e Tecnológico	150319/2021-5

Keywords

Color space models
Landsat
Remote sensing
Soil spatio-temporal monitoring
Soil spectroscopy
Spectral library

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10.1016/j.rse.2023.113845

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Rizzo, R., Wadoux, A. M. J. C., Demattê, J. A. M., Minasny, B., Barrón, V., Ben-Dor, E., Francos, N., Savin, I., Poppiel, R., Silvero, N. E. Q., Terra, F. D. S., Rosin, N. A., Rosas, J. T. F., Greschuk, L. T., Ballester, M. V. R., Gómez, A. M. R., Belllinaso, H., Safanelli, J. L., Chabrillat, S., ... Salama, E. S. M. (2023). Remote sensing of the Earth's soil color in space and time. Remote Sensing of Environment, 299, Article 113845. https://doi.org/10.1016/j.rse.2023.113845

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title = "Remote sensing of the Earth's soil color in space and time",

abstract = "Abstract Soil color is a key indicator of soil properties and conditions, exerting influence on both agronomic and environmental variables. Conventional methods for soil color determination have come under scrutiny due to their limited accuracy and reliability. In response to these concerns, we developed an innovative system that leverages 35 years of satellite imagery in conjunction with in-situ soil spectral measurements. This approach enables the creation of a global soil color map with a fine spatial resolution of 30 m x 30 m. The system initially identifies bare earth areas worldwide using reflectance bands acquired from Landsat 4 through Landsat 8 between 1985 and 2020. Soil color was quantified using the CIE-XYZ coordinates, utilizing 8005 soil spectral measurements within the visible range (380–780 nm) as ground truth data. We established transfer functions to convert Landsat reflectance bands to standardized XYZ color coordinates. These transfer functions were subsequently applied to images of bare surfaces, covering approximately 38.5% of the Earth's surface. We validated the resulting global soil color map using statistical indices derived from an independent set of ground-truth spectral data, demonstrating a high degree of agreement. By creating the world's first global soil color map, we have set a baseline for future spatial and temporal monitoring of soil conditions, thus enhancing our understanding and management of our planet's vital soil resources.",

keywords = "Color space models, Landsat, Remote sensing, Soil spatio-temporal monitoring, Soil spectroscopy, Spectral library",

author = "Rodnei Rizzo and Wadoux, {Alexandre M.J.C.} and Dematt{\^e}, {Jos{\'e} A.M.} and Budiman Minasny and Vidal Barr{\'o}n and Eyal Ben-Dor and Nicolas Francos and Igor Savin and Raul Poppiel and Silvero, {Nelida E.Q.} and Terra, {Fabr{\'i}cio da Silva} and Rosin, {N{\'i}colas Augusto} and Rosas, {Jorge Tadeu Fim} and Greschuk, {Lucas Tadeu} and Ballester, {Maria V.R.} and G{\'o}mez, {Andr{\'e}s Mauricio Rico} and Henrique Belllinaso and Safanelli, {Jos{\'e} Lucas} and Sabine Chabrillat and Fiorio, {Peterson R.} and Das, {Bhabani Sankar} and Malone, {Brendan P.} and George Zalidis and Nikolaos Tziolas and Nikolaos Tsakiridis and Konstantinos Karyotis and Nikiforos Samarinas and Eleni Kalopesa and Asa Gholizadeh and Shepherd, {Keith D.} and Robert Milewski and Emmanuelle Vaudour and Changkun Wang and Salama, {Elsayed Said Mohamed}",

note = "Publisher Copyright: {\textcopyright} 2023 Elsevier Inc.",

year = "2023",

month = dec,

day = "15",

doi = "10.1016/j.rse.2023.113845",

language = "אנגלית",

volume = "299",

journal = "Remote Sensing of Environment",

issn = "0034-4257",

publisher = "Elsevier Inc.",

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Rizzo, R, Wadoux, AMJC, Demattê, JAM, Minasny, B, Barrón, V, Ben-Dor, E, Francos, N, Savin, I, Poppiel, R, Silvero, NEQ, Terra, FDS, Rosin, NA, Rosas, JTF, Greschuk, LT, Ballester, MVR, Gómez, AMR, Belllinaso, H, Safanelli, JL, Chabrillat, S, Fiorio, PR, Das, BS, Malone, BP, Zalidis, G, Tziolas, N, Tsakiridis, N, Karyotis, K, Samarinas, N, Kalopesa, E, Gholizadeh, A, Shepherd, KD, Milewski, R, Vaudour, E, Wang, C & Salama, ESM 2023, 'Remote sensing of the Earth's soil color in space and time', Remote Sensing of Environment, vol. 299, 113845. https://doi.org/10.1016/j.rse.2023.113845

TY - JOUR

T1 - Remote sensing of the Earth's soil color in space and time

AU - Rizzo, Rodnei

AU - Wadoux, Alexandre M.J.C.

AU - Demattê, José A.M.

AU - Minasny, Budiman

AU - Barrón, Vidal

AU - Ben-Dor, Eyal

AU - Francos, Nicolas

AU - Savin, Igor

AU - Poppiel, Raul

AU - Silvero, Nelida E.Q.

AU - Terra, Fabrício da Silva

AU - Rosin, Nícolas Augusto

AU - Rosas, Jorge Tadeu Fim

AU - Greschuk, Lucas Tadeu

AU - Ballester, Maria V.R.

AU - Gómez, Andrés Mauricio Rico

AU - Belllinaso, Henrique

AU - Safanelli, José Lucas

AU - Chabrillat, Sabine

AU - Fiorio, Peterson R.

AU - Das, Bhabani Sankar

AU - Malone, Brendan P.

AU - Zalidis, George

AU - Tziolas, Nikolaos

AU - Tsakiridis, Nikolaos

AU - Karyotis, Konstantinos

AU - Samarinas, Nikiforos

AU - Kalopesa, Eleni

AU - Gholizadeh, Asa

AU - Shepherd, Keith D.

AU - Milewski, Robert

AU - Vaudour, Emmanuelle

AU - Wang, Changkun

AU - Salama, Elsayed Said Mohamed

PY - 2023/12/15

Y1 - 2023/12/15

N2 - Abstract Soil color is a key indicator of soil properties and conditions, exerting influence on both agronomic and environmental variables. Conventional methods for soil color determination have come under scrutiny due to their limited accuracy and reliability. In response to these concerns, we developed an innovative system that leverages 35 years of satellite imagery in conjunction with in-situ soil spectral measurements. This approach enables the creation of a global soil color map with a fine spatial resolution of 30 m x 30 m. The system initially identifies bare earth areas worldwide using reflectance bands acquired from Landsat 4 through Landsat 8 between 1985 and 2020. Soil color was quantified using the CIE-XYZ coordinates, utilizing 8005 soil spectral measurements within the visible range (380–780 nm) as ground truth data. We established transfer functions to convert Landsat reflectance bands to standardized XYZ color coordinates. These transfer functions were subsequently applied to images of bare surfaces, covering approximately 38.5% of the Earth's surface. We validated the resulting global soil color map using statistical indices derived from an independent set of ground-truth spectral data, demonstrating a high degree of agreement. By creating the world's first global soil color map, we have set a baseline for future spatial and temporal monitoring of soil conditions, thus enhancing our understanding and management of our planet's vital soil resources.

AB - Abstract Soil color is a key indicator of soil properties and conditions, exerting influence on both agronomic and environmental variables. Conventional methods for soil color determination have come under scrutiny due to their limited accuracy and reliability. In response to these concerns, we developed an innovative system that leverages 35 years of satellite imagery in conjunction with in-situ soil spectral measurements. This approach enables the creation of a global soil color map with a fine spatial resolution of 30 m x 30 m. The system initially identifies bare earth areas worldwide using reflectance bands acquired from Landsat 4 through Landsat 8 between 1985 and 2020. Soil color was quantified using the CIE-XYZ coordinates, utilizing 8005 soil spectral measurements within the visible range (380–780 nm) as ground truth data. We established transfer functions to convert Landsat reflectance bands to standardized XYZ color coordinates. These transfer functions were subsequently applied to images of bare surfaces, covering approximately 38.5% of the Earth's surface. We validated the resulting global soil color map using statistical indices derived from an independent set of ground-truth spectral data, demonstrating a high degree of agreement. By creating the world's first global soil color map, we have set a baseline for future spatial and temporal monitoring of soil conditions, thus enhancing our understanding and management of our planet's vital soil resources.

KW - Color space models

KW - Landsat

KW - Remote sensing

KW - Soil spatio-temporal monitoring

KW - Soil spectroscopy

KW - Spectral library

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U2 - 10.1016/j.rse.2023.113845

DO - 10.1016/j.rse.2023.113845

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AN - SCOPUS:85174587034

SN - 0034-4257

VL - 299

JO - Remote Sensing of Environment

JF - Remote Sensing of Environment

M1 - 113845

ER -

Remote sensing of the Earth's soil color in space and time

Abstract

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Keywords

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