@article{fdi:010053912,
  title = {{A}ssessing soil carbon stocks under pastures through orbital remote sensing},
  author = {{S}zakacs, {G}. {G}. {J}. and {C}erri, {C}. {C}. and {H}erpin, {U}. and {B}ernoux, {M}artial},
  editor = {},
  language = {{ENG}},
  abstract = {{T}he growing demand of world food and energy supply increases the threat of global warming due to higher greenhouse gas emissions by agricultural activity. {T}herefore, it is widely admitted that agriculture must establish a new paradigm in terms of environmental sustainability that incorporate techniques for mitigation of greenhouse gas emissions. {T}his article addresses to the scientific demand to estimate in a fast and inexpensive manner current and potential soil organic carbon ({SOC}) stocks in degraded pastures, using remote sensing techniques. {F}our pastures on sandy soils under {B}razilian {C}errado vegetation in {S}ao {P}aulo state were chosen due to their {SOC} sequestration potential, which was characterized for the soil depth 0-50 cm. {S}ubsequently, a linear regression analysis was performed between {SOC} and {L}eaf {A}rea {I}ndex ({LAI}) measured in the field ({LAI}(field)) and derived by satellite ({LAI}(satellite)) as well as {SOC} and pasture reflectance in six spectra from 450 nm - 2350 nm, using the {E}nhanced {T}hematic {M}apper ({ETM}+) sensor of satellite {L}andsat 7. {A} high correlation between {SOC} and {LAI}(field) ({R}-2 = 0.9804) and {LAI}(satellite) ({R}-2 = 0.9812) was verified. {T}he suitability of satellite derived {LAI} for {SOC} determination leads to the assumption, that orbital remote sensing is a very promising {SOC} estimation technique from regional to global scale.},
  keywords = {{B}razil ; leaf {A}rea {I}ndex ; soil organic carbon ; pasture degradation ; spectral reflectance ; climate change},
  booktitle = {},
  journal = {{S}cientia {A}gricola},
  volume = {68},
  numero = {5},
  pages = {574--581},
  ISSN = {0103-9016},
  year = {2011},
  URL = {https://www.documentation.ird.fr/hor/fdi:010053912},
}