%0 Journal Article %1 Ceccato:October2002:0034-4257:198 %A P., Ceccato %A S., Flasse %D October 2002 %J Remote Sensing of Environment %K fire firemafs fires inversions modeling moisture optical radiative radiativetransfer reflectance remotesensing satellite vegetation wildfire %P 198-207(10) %R doi:10.1016/S0034-4257(02)00036-6 %T Designing a spectral index to estimate vegetation water content from remote sensing data - Part 2. Validation and applications %U http://www.ingentaconnect.com/content/els/00344257/2002/00000082/00000002/art00036 %V 82 %X The Global Vegetation Moisture Index (GVMI) was developed to retrieve vegetation water content from local to global scale rapidly and reliably using SPOT-VEGETATION data. This paper validates the GVMI with field measurements of vegetation water content measured over four different ecosystems in Senegal. Two of the sites show exact concordance between GVMI-derived and field-measured water content. The remaining two sites show differences in value but provide identical evolution over time. Comparison between ecosystems illustrates that GVMI-derived water content is consistent with field measurements of water content expressed as a quantity of water per unit area. Additional study shows that GVMI is not related to the vegetation moisture content expressed as a percentage of water per quantity of biomass. Comparison between the GVMI and NDVI methods also illustrates that the NDVI provides different information (vegetation greenness), which is not directly related to the quantity of water in the vegetation. Potential applications of the new GVMI are also discussed.

@article{Ceccato:October2002:0034-4257:198, abstract = {The Global Vegetation Moisture Index (GVMI) was developed to retrieve vegetation water content from local to global scale rapidly and reliably using SPOT-VEGETATION data. This paper validates the GVMI with field measurements of vegetation water content measured over four different ecosystems in Senegal. Two of the sites show exact concordance between GVMI-derived and field-measured water content. The remaining two sites show differences in value but provide identical evolution over time. Comparison between ecosystems illustrates that GVMI-derived water content is consistent with field measurements of water content expressed as a quantity of water per unit area. Additional study shows that GVMI is not related to the vegetation moisture content expressed as a percentage of water per quantity of biomass. Comparison between the GVMI and NDVI methods also illustrates that the NDVI provides different information (vegetation greenness), which is not directly related to the quantity of water in the vegetation. Potential applications of the new GVMI are also discussed.}, added-at = {2008-11-06T15:47:08.000+0100}, author = {P., Ceccato and S., Flasse}, biburl = {https://www.bibsonomy.org/bibtex/2540911a2cc4fa48d368b040a73a7e21d/jgomezdans}, description = {IngentaConnect Designing a spectral index to estimate vegetation water content f...}, doi = {doi:10.1016/S0034-4257(02)00036-6}, interhash = {a4852d131a555a0afc92c353ee87b404}, intrahash = {540911a2cc4fa48d368b040a73a7e21d}, journal = {Remote Sensing of Environment}, keywords = {fire firemafs fires inversions modeling moisture optical radiative radiativetransfer reflectance remotesensing satellite vegetation wildfire}, pages = {198-207(10)}, timestamp = {2008-11-06T15:47:08.000+0100}, title = {Designing a spectral index to estimate vegetation water content from remote sensing data - Part 2. Validation and applications}, url = {http://www.ingentaconnect.com/content/els/00344257/2002/00000082/00000002/art00036}, volume = 82, year = {October 2002} }