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Optimizing spectral indices and chemometric analysis of leaf chemical properties
Citation
Feret, J-B and Francois, C and Gitelson, A and Asner, GP and Barry, KM and Panigada, C and Richardson, AD and Jacquemoud, S, Optimizing spectral indices and chemometric analysis of leaf chemical properties, Remote Sensing of Environment, 115, (10) pp. 2742-2750. ISSN 0034-4257 (2011) [Refereed Article]
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Copyright Statement
Copyright © 2011 The definitive version is available at http://www.sciencedirect.com
DOI: doi:10.1016/j.rse.2011.06.016
Abstract
We used synthetic reflectance spectra generated by a radiative transfer model, PROSPECT-5, to develop statistical relationships between leaf optical and chemical properties, which were applied to experimental data without any readjustment. Four distinct synthetic datasets were tested: two unrealistic, uniform distributions and two normal distributions based on statistical properties drawn from a comprehensive experimental database. Two methods used in remote sensing to retrieve vegetation chemical composition, spectral indices and Partial Least Squares (PLS) regression, were trained both on the synthetic and experimental datasets, and validated against observations. Results are compared to a cross-validation process and model inversion applied to the same observations. They show that synthetic datasets based on normal distributions of actual leaf chemical and structural properties can be used to optimize remotely sensed spectral indices or other retrieval methods for analysis of leaf chemical constituents. This study concludes with the definition of several polynomial relationships to retrieve leaf chlorophyll content, carotenoid
content, equivalent water thickness and leaf mass per area using spectral indices, derived from synthetic data and validated on a large variety of leaf types. The straightforward method described here brings the possibility
to apply or adapt statistical relationships to any type of leaf.
Item Details
Item Type: | Refereed Article |
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Research Division: | Agricultural, Veterinary and Food Sciences |
Research Group: | Forestry sciences |
Research Field: | Tree nutrition and physiology |
Objective Division: | Plant Production and Plant Primary Products |
Objective Group: | Forestry |
Objective Field: | Hardwood plantations |
UTAS Author: | Barry, KM (Associate Professor Kara Barry) |
ID Code: | 65974 |
Year Published: | 2011 |
Web of Science® Times Cited: | 157 |
Deposited By: | Agricultural Science |
Deposited On: | 2010-12-14 |
Last Modified: | 2012-05-23 |
Downloads: | 0 |
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