2006, English, Article edition: Forest leaf area index determination : a multiyear satelliteindependent method based on within-stand normalized difference vegetation index spatial variability Le Maire, G.; François, C.; Soudani, Kamel; ...

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Physical Description
  • text
Published
  • HAL - CCSD
  • 2006
Language
  • English

Edition details

Title
  • Forest leaf area index determination : a multiyear satelliteindependent method based on within-stand normalized difference vegetation index spatial variability
Author
  • Le Maire, G.
  • François, C.
  • Soudani, Kamel
  • Davi, H.
  • Le Dantec, V.
  • Saugier, Bernard
  • Dufrene, E.
Published
  • HAL - CCSD
  • 2006
Physical Description
  • text
Subjects
Notes
  • The Leaf Area Index (LAI) and its spatial distribution are key features to describe the forest ecophysiological processes. A stable and reproducible relationship is obtained between the LAI and the standard deviation sNDVI of the pixel-based satellite-derived normalized difference vegetation indices (NDVI) of forest stands. In situ measurements of LAI have been performed with the LAI-2000 Plant Canopy Analyser over 8 years in the managed Fontainebleau forest (France) on about 31 stands each year, including oak, beech, and mixed oak-beech stands. Simultaneous satellite images have been acquired, atmospherically and geometrically corrected, and included into a geographic information system to get the mean NDVI and the sNDVI for each stand. A total of six different satellites with a 20- to 30-m spatial resolution have been considered over the eight studied years: SPOT1, SPOT2, SPOT4, LANDSAT ETM+, IKONOS, and HYPERION. The mean LAI of a stand is linked to the sNDVI with a unique relationship that appears to be mostly year- and satellite-independent, because the sNDVI is nearly insensitive to additive or proportional shifts on NDVI. The theoretical bases of the sNDVI-LAI relationship are investigated. The results show the combined importance of the shape of the within-stand LAI distribution (following a Weibull probability density function) and the shape of the within-stand LAI-NDVI curves (showing a saturation). The root mean square error of the predicted LAI over the 259 samples is 1.14 m2/​m2 when all years and satellites are considered, using the following equation: LAI =​ 2.45 ln(sNDVI) 5.58 (r2 =​ 0.63).
  • HAL:ird-00392224, version 1
  • HAL:http:/​/​hal.ird.fr/​ird-00392224/​en/​
  • DOI:10.1029/​2005JG000122
Language
  • English
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