@article{fdi:010093271,
  title = {{A} global soil spectral grid based on space sensing},
  author = {{D}ematt{\^e}, {J}.{A}.{M}. and {R}izzo, {R}. and {R}osin, {N}.{A}. and {P}oppiel, {R}.{R}. and {M}acedo {N}ovais, {J}.{J}. and {A}ccorsi {A}morim, {M}.{T}. and {R}odriguez-{A}lbarracín, {H}.{S}. and {T}adeu {F}im {R}osas, {J}. and dos {A}njos {B}artsch, {B}. and {G}uadagnin {V}ogel, {L}. and {M}inasny, {B}. and {G}runwald, {S}. and {G}e, {Y}. and {B}en-{D}or, {E}. and {G}holizadeh, {A}. and {G}omez, {C}{\'e}cile and {C}habrillat, {S}. and {F}rancos, {F}. and {F}iantis, {D}. and {B}elal, {A}. and {T}sakiridis, {N}. and {K}alopesa, {E}. and {N}aimi, {S}. and {A}youbi, {S}. and {T}ziolas, {N}. and {D}as, {B}. {S}. and {Z}alidis, {G}. and {F}rancelino, {M}. {R}. and de {M}ello, {D}. {C}. and {H}afshejani, {N}.{A}. and {P}eng, {Y}. and {M}a, {Y}. and {C}oblinski, {J}.{A}. and {W}adoux, {A}.{M}..{J}.{C}. and {S}avin, {I}. and {M}alone, {B}.{P}. and {K}aryotis, {K}. and {M}ilewski, {R}. and {V}audour, {E}. and {W}ang, {C}. and {S}alama, {E}.{S}.{M}. and {S}hepherd, {K}.{D}.},
  editor = {},
  language = {{ENG}},
  abstract = {{S}oils provide a range of essential ecosystem services for sustaining life, including climate regulation. {A}dvanced technologies support the protection and restoration of this natural resource. {W}e developed the first fine-resolution spectral grid of bare soils by processing a spatiotemporal satellite data cube spanning the globe. {L}andsat imagery provided a 30 m composite soil image using the {G}eospatial {S}oil {S}ensing {S}ystem ({GEOS}3), which calculates the median of pixels from the 40-year time series (1984-2022). {T}he map of the {E}arth's bare soil covers nearly 90 % of the world's drylands. {T}he modeling resulted in 10 spectral patterns of soils worldwide. {R}esults indicate that plant residue and unknown soil patterns are the main factors that affect soil reflectance. {E}levation and the shortwave infrared ({SWIR}2) band show the highest importance, with 78 and 80 %, respectively, suggesting that spectral and geospatial proxies provide inference on soils. {W}e showcase that spectral groups are associated with environmental factors (climate, land use and land cover, geology, landforms, and soil). {T}hese outcomes represent an unprecedented information source capable of unveiling nuances on global soil conditions. {I}nformation derived from reflectance data supports the modeling of several soil properties with applications in soil-geological surveying, smart agriculture, soil tillage optimization, erosion monitoring, soil health, and climate change studies. {O}ur comprehensive spectrally-based soil grid can address global needs by informing stakeholders and supporting policy, mitigation planning, soil management strategy, and soil, food, and climate security interventions.},
  keywords = {{MONDE}},
  booktitle = {},
  journal = {{S}cience of {T}he {T}otal {E}nvironment},
  volume = {968},
  numero = {},
  pages = {178791 [14 ]},
  ISSN = {0048-9697},
  year = {2025},
  DOI = {10.1016/j.scitotenv.2025.178791},
  URL = {https://www.documentation.ird.fr/hor/fdi:010093271},
}