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Proceedings Paper

Comparisons among normalized vegetation indices for the determination of LAI
Author(s): Luca Bernasconi; Ivan Pippi; Sabrina Raddi
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Paper Abstract

Airborne hyperspectral images collected over San Rossore Natural Park (Pisa, Italy) by the Multispectral Infrared and Visible Imaging Spectrometer (MIVIS) on June 21st, 2000 were analyzed in order to assess the best indices for forest LAI estimation. Hemispherical photography was used for ground truth measurements, simultaneously with the overflights, in hardwood and conifer stands characterized by a LAI ranging between 1.2 and 4.5. All band combinations expressed as simple ratios and normalized indices (a total of 89 single bands, and 7832 and 3916 indices, respectively) were linearly correlated to LAI in order to detect the best correlations. Determination coefficients were analyzed by means of a graphical matrix to highlight relevant spectral regions. Normalized indices composed by the red chlorophyll absorption wavelength (680 nm) and the wavelengths after the green reflectance peak (580-640 nm) in the orange region were strongly correlated to LAI. Best results were obtained with the newly proposed Orange Slope Vegetation Index [OSVI=(ρ620680)/(ρ620680), R2=0.88, RMSE=0.5). The index performed better than the normalized difference vegetation index (NDVI=(ρ780680)/(ρ780680), R2=0.47) Using SAIL radiative transfer model, canopy reflectance at different viewing angles and a wide range of LAI was simulated in order to verify the sensitivity of OSVI and NDVI. For LAI between 0.25 and 8 both indices resulted stable for viewing zenith angles between -60° and +60°. OSVI, being saturated with values greater than 4, could be used to estimate a wider range of LAI than NDVI. Application of GeoSail model resulted in a good agreement between simulated and measured OSVI.

Paper Details

Date Published: 17 March 2003
PDF: 9 pages
Proc. SPIE 4879, Remote Sensing for Agriculture, Ecosystems, and Hydrology IV, (17 March 2003); doi: 10.1117/12.462471
Show Author Affiliations
Luca Bernasconi, Univ. degli Studi di Firenze (Italy)
Ivan Pippi, CNR-IFAC (Italy)
Sabrina Raddi, Univ. degli Studi di Firenze (Italy)

Published in SPIE Proceedings Vol. 4879:
Remote Sensing for Agriculture, Ecosystems, and Hydrology IV
Manfred Owe; Guido D'Urso; Leonidas Toulios, Editor(s)

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