Details
| Original language | English |
|---|---|
| Article number | 113845 |
| Journal | Remote sensing of environment |
| Volume | 299 |
| Early online date | 25 Oct 2023 |
| Publication status | Published - 15 Dec 2023 |
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
ASJC Scopus subject areas
- Agricultural and Biological Sciences(all)
- Soil Science
- Earth and Planetary Sciences(all)
- Geology
- Earth and Planetary Sciences(all)
- Computers in Earth Sciences
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In: Remote sensing of environment, Vol. 299, 113845, 15.12.2023.
Research output: Contribution to journal › Article › Research › peer review
}
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
N1 - Funding Information: This research was funded by the following Brazilian institutions: São Paulo Research Foundation (FAPESP), grant number 2014/22262-0 , 2016/26176-6 , 2018/23760-4 ; National Council for Scientific and Technological Development (CNPq), grant number 150319/2021-5 . MHES RF ( 075-15-2022-321 ). For the purpose of Open Access, a CC-BY public copyright licence has been applied by the authors to the present document and will be applied to all subsequent versions up to the Author Accepted Manuscript arising from this submission. Funding Information: The authors are grateful to the Soil Science Department in Luiz de Queiroz College of Agriculture, University of São Paulo for funding and providing the facilities for the development of this research. The authors are also grateful to the Geotechnologies in Soil Science group for providing the soil database.
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
UR - http://www.scopus.com/inward/record.url?scp=85174587034&partnerID=8YFLogxK
U2 - 10.1016/j.rse.2023.113845
DO - 10.1016/j.rse.2023.113845
M3 - Article
AN - SCOPUS:85174587034
VL - 299
JO - Remote sensing of environment
JF - Remote sensing of environment
SN - 0034-4257
M1 - 113845
ER -