@article{fdi:010084296,
  title = {{T}he {B}razilian {S}oil {S}pectral {S}ervice ({B}ra{S}pec{S}) : a user-friendly system for global soil spectra communication [+ {C}orrection]},
  author = {{D}ematte, {J}. {A}. {M}. and {P}aiva, {A}. {F}. {D}. and {P}oppiel, {R}. {R}. and {R}osin, {N}. {A}. and {R}uiz, {L}. {F}. {C}. and {M}ello, {F}. {A}. {D}. and {M}inasny, {B}. and {G}runwald, {S}. and {G}e, {Y}. {F}. and {B}en {D}or, {E}. and {G}holizadeh, {A}. and {G}omez, {C}{\'e}cile and {C}habrillat, {S}. and {F}rancos, {N}. and {A}youbi, {S}. and {F}iantis, {D}. and {B}iney, {J}. {K}. {M}. and {W}ang, {C}. {K}. and {B}elal, {A}. and {N}aimi, {S}. and {H}afshejani, {N}. {A}. and {B}ellinaso, {H}. and {M}oura-{B}ueno, {J}. {M}. and {S}ilvero, {N}. {E}. {Q}.},
  editor = {},
  language = {{ENG}},
  abstract = {{A}lthough many {S}oil {S}pectral {L}ibraries ({SSL}s) have been created globally, these libraries still have not been operationalized for end-users. {T}o address this limitation, this study created an online {B}razilian {S}oil {S}pectral {S}ervice ({B}ra{S}pec{S}). {T}he system was based on the {B}razilian {S}oil {S}pectral {L}ibrary ({BSSL}) with samples collected in the {V}isible-{N}ear-{S}hort-wave infrared (vis-{NIR}-{SWIR}) and {M}id-infrared ({MIR}) ranges. {T}he interactive platform allows users to find spectra, act as custodians of the data, and estimate several soil properties and classification. {T}he system was tested by 500 {B}razilian and 65 international users. {U}sers accessed the platform (besbbr.com.br), uploaded their spectra, and received soil organic carbon ({SOC}) and clay content prediction results via email. {T}he {B}ra{S}pec{S} prediction provided good results for {B}razilian data, but performed variably for other countries. {P}rediction for countries outside of {B}razil using local spectra ({E}xternal {C}ountry {S}oil {S}pectral {L}ibraries, {E}x{CSSL}) mostly showed greater performance than {B}ra{S}pec{S}. {C}lay {R}-2 ranged from 0.5 ({B}ra{S}pec{S}) to 0.8 ({E}x{CSSL}) in vis-{NIR}-{SWIR}, but {B}ra{S}pec{S} {MIR} models were more accurate in most situations. {T}he development of external models based on the fusion of local samples with {BSSL} formed the {G}lobal {S}oil {S}pectral {L}ibrary ({GSSL}). {T}he {GSSL} models improved soil properties prediction for different countries. {N}evertheless, the proposed system needs to be continually updated with new spectra so they can be applied broadly. {A}ccordingly, the online system is dynamic, users can contribute their data and the models will adapt to local information. {O}ur community-driven web platform allows users to predict soil attributes without learning soil spectral modeling, which will invite end-users to utilize this powerful technique.},
  keywords = {proximal soil sensing ; soil spectral library ; spectroscopy ; soil analysis ; soil quality ; precision agriculture ; community practice ; soil health monitoring ; {BRESIL} ; {MONDE}},
  booktitle = {},
  journal = {{R}emote {S}ensing},
  volume = {14},
  numero = {3},
  pages = {740 [27 + {C}orrection in {R}emote {S}ensing.2022, 14, 6,1459, 2 p.]},
  year = {2022},
  DOI = {10.3390/rs14030740},
  URL = {https://www.documentation.ird.fr/hor/fdi:010084296},
}