%0 Journal Article %1 Steven2003Intercalibration %A Steven, Michael D. %A Malthus, Timothy J. %A Baret, Frederic %A Xu, Hui %A Chopping, Mark J. %D 2003 %J Remote Sensing of Environment %K deteco, remota %N 4 %P 412--422 %R 10.1016/j.rse.2003.08.010 %T Intercalibration of vegetation indices from different sensor systems %U http://dx.doi.org/10.1016/j.rse.2003.08.010 %V 88 %X Spectroradiometric measurements were made over a range of crop canopy densities, soil backgrounds and foliage colour. The reflected spectral radiances were convoluted with the spectral response functions of a range of satellite instruments to simulate their responses. When Normalised Difference Vegetation Indices (NDVI) from the different instruments were compared, they varied by a few percent, but the values were strongly linearly related, allowing vegetation indices from one instrument to be intercalibrated against another. A table of conversion coefficents is presented for AVHRR, ATSR-2, Landsat MSS, TM and ETM+, SPOT-2 and SPOT-4 HRV, IRS, IKONOS, SEAWIFS, MISR, MODIS, POLDER, Quickbird and MERIS (see for glossary of acronyms). The same set of coefficients was found to apply, within the margin of error of the analysis, for the Soil Adjusted Vegetation Index SAVI. The relationships for SPOT vs. TM and for ATSR-2 vs. AVHRR were directly validated by comparison of atmospherically corrected image data. The results indicate that vegetation indices can be interconverted to a precision of 1-2\%. This result offers improved opportunities for monitoring crops through the growing season and the prospects of better continuity of long-term monitoring of vegetation responses to environmental change.

@article{Steven2003Intercalibration, abstract = {Spectroradiometric measurements were made over a range of crop canopy densities, soil backgrounds and foliage colour. The reflected spectral radiances were convoluted with the spectral response functions of a range of satellite instruments to simulate their responses. When Normalised Difference Vegetation Indices (NDVI) from the different instruments were compared, they varied by a few percent, but the values were strongly linearly related, allowing vegetation indices from one instrument to be intercalibrated against another. A table of conversion coefficents is presented for AVHRR, ATSR-2, Landsat MSS, TM and ETM+, SPOT-2 and SPOT-4 HRV, IRS, IKONOS, SEAWIFS, MISR, MODIS, POLDER, Quickbird and MERIS (see for glossary of acronyms). The same set of coefficients was found to apply, within the margin of error of the analysis, for the Soil Adjusted Vegetation Index SAVI. The relationships for SPOT vs. TM and for ATSR-2 vs. AVHRR were directly validated by comparison of atmospherically corrected image data. The results indicate that vegetation indices can be interconverted to a precision of 1-2\%. This result offers improved opportunities for monitoring crops through the growing season and the prospects of better continuity of long-term monitoring of vegetation responses to environmental change.}, added-at = {2008-05-07T20:18:23.000+0200}, author = {Steven, Michael D. and Malthus, Timothy J. and Baret, Frederic and Xu, Hui and Chopping, Mark J.}, biburl = {https://www.bibsonomy.org/bibtex/22f7d7545454a2f20bf42ac22d6fc866b/jgomezdans}, citeulike-article-id = {1146864}, doi = {10.1016/j.rse.2003.08.010}, interhash = {b721bab1e2af43184a4a5f793e3c6c81}, intrahash = {2f7d7545454a2f20bf42ac22d6fc866b}, journal = {Remote Sensing of Environment}, keywords = {deteco, remota}, month = {December}, number = 4, pages = {412--422}, posted-at = {2007-03-08 10:32:54}, priority = {0}, timestamp = {2008-05-07T20:18:25.000+0200}, title = {Intercalibration of vegetation indices from different sensor systems}, url = {http://dx.doi.org/10.1016/j.rse.2003.08.010}, volume = 88, year = 2003 }