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Designing a spectral index to estimate vegetation water content from remote sensing data: Part 1 - Theoretical approach

by: Ceccato P., Gobron N., Flasse S., Pinty B., and Tarantola S.

In: Remote Sensing of Environment, Vol. 82 (October 2002) , p. 188-19710.

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URL:	http://www.ingentaconnect.com/content/els/00344257/2002/00000082/00000002/art00037
DOI:	10.1016/S0034-4257(02)00037-8

This paper describes the methodology used to create a spectral index to retrieve vegetation water content from remotely sensed data in the solar spectrum domain. A global sensitivity analysis GSA using radiative transfer models is used to understand and quantify vegetation water content effects on the signal measured at three levels: leaf, canopy, and atmosphere. An index is then created that optimises retrieval of vegetation water content in terms of water quantity per unit area at canopy level and minimises perturbing effects of geophysical and atmospheric effects. The new index, optimised for the new SPOT-VEGETATION sensor, is presented as an example. Limitations and robustness of the index are also discussed.

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IngentaConnect Designing a spectral index to estimate vegetation water content f...

BibTeX record

@article{Ceccato:October2002:0034-4257:188,
  abstract = {This paper describes the methodology used to create a spectral index to retrieve vegetation water content from remotely sensed data in the solar spectrum domain. A global sensitivity analysis (GSA) using radiative transfer models is used to understand and quantify vegetation water content effects on the signal measured at three levels: leaf, canopy, and atmosphere. An index is then created that optimises retrieval of vegetation water content (in terms of water quantity per unit area at canopy level) and minimises perturbing effects of geophysical and atmospheric effects. The new index, optimised for the new SPOT-VEGETATION sensor, is presented as an example. Limitations and robustness of the index are also discussed.},
  added-at = {2008-11-06T15:45:14.000+0100},
  author = {P., Ceccato and N., Gobron and S., Flasse and B., Pinty and S., Tarantola},
  biburl = {http://www.bibsonomy.org/bibtex/22e87dcb3a43c415ab87c3f710776609a/jgomezdans},
  description = {IngentaConnect Designing a spectral index to estimate vegetation water content f...},
  doi = {doi:10.1016/S0034-4257(02)00037-8},
  interhash = {1d69269b63d12db940ef57feedb31b57},
  intrahash = {2e87dcb3a43c415ab87c3f710776609a},
  journal = {Remote Sensing of Environment},
  keywords = {Radiative fire firemafs fires moisture radiativetransfer remotesensing vegetation wildfire},
  pages = {188-197(10)},
  timestamp = {2008-11-06T15:45:14.000+0100},
  title = {Designing a spectral index to estimate vegetation water content from remote sensing data: Part 1 - Theoretical approach},
  url = {http://www.ingentaconnect.com/content/els/00344257/2002/00000082/00000002/art00037},
  volume = 82,
  year = {October 2002}
}

Endnote record

%0 Journal Article
%1 Ceccato:October2002:0034-4257:188
%A P., Ceccato
%A N., Gobron
%A S., Flasse
%A B., Pinty
%A S., Tarantola
%D October 2002
%J Remote Sensing of Environment
%K 
%P 188-197(10)
%T Designing a spectral index to estimate vegetation water content from remote sensing data: Part 1 - Theoretical approach
%R doi:10.1016/S0034-4257(02)00037-8
%U http://www.ingentaconnect.com/content/els/00344257/2002/00000082/00000002/art00037
%V 82
%X This paper describes the methodology used to create a spectral index to retrieve vegetation water content from remotely sensed data in the solar spectrum domain. A global sensitivity analysis (GSA) using radiative transfer models is used to understand and quantify vegetation water content effects on the signal measured at three levels: leaf, canopy, and atmosphere. An index is then created that optimises retrieval of vegetation water content (in terms of water quantity per unit area at canopy level) and minimises perturbing effects of geophysical and atmospheric effects. The new index, optimised for the new SPOT-VEGETATION sensor, is presented as an example. Limitations and robustness of the index are also discussed.