Library Open Repository
Optimising spectral indices and chemometric analysis of leaf chemical properties using radiative transfer modeling
Feret, JB and Francois, C and Gitelson, A and Barry, KM and Panigada, C and Richardson, AD and Jacquemoud, S (2011) Optimising spectral indices and chemometric analysis of leaf chemical properties using radiative transfer modeling. Remote Sensing of Environment, 115. pp. 2742-2750. ISSN 0034-4257
Feret_et_al_RSE...pdf | Request a copy
Full text restricted
Available under University of Tasmania Standard License.
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.
|Journal or Publication Title:||Remote Sensing of Environment|
|Page Range:||pp. 2742-2750|
|Identification Number - DOI:||10.1016/j.rse.2011.06.016|
|Additional Information:||The definitive version is available at http://www.sciencedirect.com|
|Date Deposited:||10 Feb 2012 05:22|
|Last Modified:||18 Nov 2014 04:27|
|Item Statistics:||View statistics for this item|
Actions (login required)
|Item Control Page|