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A global vegetation index for SeaWiFS: Design and applications

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Remote Sensing and Climate Modeling: Synergies and Limitations

Part of the book series: Advances in Global Change Research ((AGLO,volume 7))

Abstract

Optimized vegetation indices provide a convenient approach to estimate crucial plant properties on the basis of satellite data. This paper describes the steps followed to implement an index optimized to estimate the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) on the basis of data generated by the SeaWiFS instrument, and the preliminary results obtained. Index values are computed on the basis of top of atmosphere bidirectional reflectance factor values in the blue, red and near-infrared domains, as well as information on the geometry of illumination and observation. Results obtained with SeaWiFS data are used to evaluate the performance of the index. This case study documents the ability of the index to discriminate between various surface types, and its insensitivity to changes in the geometrical conditions of observation and to atmospheric effects. The operational environment set up at SAI to process SeaWiFS data is outlined and selected standard retrievals resulting from a monthly composite analysis are shown as examples of the products generated.

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References

  • Beiward, A., J. C. Taylor, M. J. Stuttard, E. Bignal, J. Mathews, and D. Curtis (1990) An unsupervised approach to the classification of semi-natural vegetation from Landsat Thematic Mapper data, Internationaljournal of Remote Sensing, 11, 429–445.

    Article  Google Scholar 

  • Bulgarelli, B. and F. Mélin (2000) SeaWiFS data processing code REMBRANDT version 1.0: code elements, COASTS Annual Report 2000, Technical Report EUR NC, EC Joint Research Centre.

    Google Scholar 

  • Cihlar, J., J. Chen, Z. Li, F. Huan, R. Latifovic, and R. Dixon (1998) Can inter-annual land surface signal be discerned in composite AVHRR data? Journal of Geophysical Research, 103, 23,163–23,172.

    Article  Google Scholar 

  • Ehrlich, D. and E. F. Lambin (1996) Broad scale land-cover classification and inter-annual climatic variability, International Journal of Remote Sensing, 17, 845–862.

    Article  Google Scholar 

  • Fiasse, S. and M. M. Verstraete (1994) Monitoring the environment with vegetation indices: Comparison of NDVI and GEMI using AVHRR data over Africa, in F. Veroustraete and R. Ceulemans (Eds.), Vegetation, Modelling and Climatic Change Effects, 107–135. The Hague: SPB Academic Publishing.

    Google Scholar 

  • Gobron, N., B. Pinty, and M. M. Verstraete (1997) Presentation and application of an advanced model for the scattering of light by vegetation in the solar domain, in Proceedings of the 7th ISPRS International Symposium on Physical Measurements and Signatures in Remote Sensing, Courchevel, France, 7–11 April 1997, 267–273, Balkema/Rotterdam/Brookfield.

    Google Scholar 

  • Gobron, N., B. Pinty, M. M. Verstraete, and Y. Govaerts (1999) The MERIS Global Vegetation Index (MGVI): Description and preliminary application, International Journal of Remote Sensing, 20, 1917–1927.

    Article  Google Scholar 

  • Gobron, N., B. Pinty, M. M. Verstraete, and J.-L. Widlowski (2000a) Advanced vegetation indices optimized for up-coming sensors: Design, performance and applications, IEEE Transactions on Geoscience and Remote Sensing, in print.

    Google Scholar 

  • Gobron, N., B. Pinty, M. M. Verstraete, J. V. Martonchik, Y. Knyazikhin, and D. J. Diner (2000b) The potential of multi-angular spectral measurements to characterize land surfaces: Conceptual approach and exploratory application, Journal of Geophysical Research, in print.

    Google Scholar 

  • Gobron, N., B. Pinty, M. M. Verstraete, and F. Mélin (2000c) Development of a Vegetation Index Optimized for the SeaWiFS Instrument ATBD, Version 2.0 Technical Report EUR EN, Space Applications Institute, In print.

    Google Scholar 

  • Gobron, N., M. M. Verstraete, and B. Pinty (1998) Development of a spectral index optimized for the GLI Instrument Algorithm Theoretical Basis Document, Technical Report EUR 18138 EN, Space Applications Institute.

    Google Scholar 

  • Govaerts, Y., M. M. Verstraete, B. Pinty, and N. Gobron (1999) Designing optimal spectral indices: A feasibility and proof of concept study, International Journal of Remote Sensing, 20, 1853–1873.

    Article  Google Scholar 

  • Hame, T., K. Anderson, A. Lohi, M. Kohl, R. Paivinen, E. Carfagna, H. Jean, I. Spence, T. leToan, S. Quegan, C. Estreguil, S. Folving, and P. Kennedy (1999) Validated forest variable mapping across Europe using multi-resolution data-results of the FMERS study, in Remote sensing and forest monitoring International IUFRO Conference, Rogow, Poland, June 1–3.

    Google Scholar 

  • Holben, B. N. (1986) Characteristics of maximum-value composite images from temporal AVHRR data, Internationaljournal of Remote Sensing, 7, 1417–1434.

    Article  Google Scholar 

  • Huete, A. R., H. Q. Liu, K. Batchily, and W. van Leeuven (1997) A comparison of vegetation indices over a global set of TM images for EOS-MODIS, Remote Sensing of Environment, 59, 440–451.

    Article  Google Scholar 

  • Kaufman, Y. J. and D. Tanré (1992) Atmospherically resistant vegetation index (ARVI) for EOS-MODIS, IEEE Transactions on Geoscience and Remote Sensing, 30, 261–270.

    Article  Google Scholar 

  • Loveland, T. R. and A. S. Belward (1997) The IGBP-DIS global 1 km land cover data set, DIScover: First results, International Journal of Remote Sensing, 18, 3289–3295.

    Article  Google Scholar 

  • Loveland, T. R., Z. Zhu, D. O. Ohlen, J. F. Brown, B. C. Reed, and L. Yang (1999) An analysis of the IGBP global land-cover characterization process, Photogrammetric Engineering and Remote Sensing, 65, 1021–1032.

    Google Scholar 

  • Meyer, D., M. M. Verstraete, and B. Pinty (1995) The effect of surface anisotropy and viewing geometry on the estimation of NDVI from AHVRR, Remote Sensing Review, 12, 3–27.

    Article  Google Scholar 

  • Rahman, H., B. Pinty, and M. M. Verstraete (1993) Coupled surface-atmosphere reflectance (CSAR) model. 2. Semiempirical surface model usable with NOAA Advanced Very High Resolution Radiometer data, Journal of Geophysical Research, 98, 20,791–20,801.

    Google Scholar 

  • Verstraete, M. M. and B. Pinty (1996) Designing optimal spectral indices for remote sensing applications, IEEE Transactions on Geoscience and Remote Sensing, 34, 1254–1265.

    Article  Google Scholar 

  • Verstraete, M. M., B. Pinty, and N. Gobron (1998) Development of a Spectral Index Optimized for the VEGETATION Instrument, Report Phase 1, http://www-vegetation.cst.cnes.fr:8050/vgtprep/verstraete/report2.html.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Space Applications Institute, EC Joint Research Centre, Ispra, Italy

    N. Gobron, F. Mélin, B. Pinty, M. M. Verstraete, J.-L. Widlowski & G. Bucini

Authors
  1. N. Gobron
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  2. F. Mélin
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  3. B. Pinty
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  4. M. M. Verstraete
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  5. J.-L. Widlowski
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  6. G. Bucini
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Editor information

Editors and Affiliations

  1. Department of Geography, University of Fribourg, Switzerland

    Martin Beniston

  2. Space Applications Institute, Joint Research Centre, Ispra (VA), Italy

    Michel M. Verstraete

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© 2001 Kluwer Academic Publishers

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Gobron, N., Mélin, F., Pinty, B., Verstraete, M.M., Widlowski, JL., Bucini, G. (2001). A global vegetation index for SeaWiFS: Design and applications. In: Beniston, M., Verstraete, M.M. (eds) Remote Sensing and Climate Modeling: Synergies and Limitations. Advances in Global Change Research, vol 7. Springer, Dordrecht. https://doi.org/10.1007/0-306-48149-9_1

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  • DOI: https://doi.org/10.1007/0-306-48149-9_1

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-90-481-5648-1

  • Online ISBN: 978-0-306-48149-9

  • eBook Packages: Springer Book Archive

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