Research Papers

Analyzing the spectral variability of tropical tree species using hyperspectral feature selection and leaf optical modeling

[+] Author Affiliations
Matheus Pinheiro Ferreira

National Institute for Space Research, Remote Sensing Division, Av. dos Astronautas 1758, 12227-010 São José dos Campos, SP, Brazil

Federal University of Rio Grande do Sul, Center for Remote Sensing, Av. Bento Gonçalves, 9500 91501-970 Porto Alegre, RS, Brazil

Atilio Efrain Bica Grondona

Federal University of Rio Grande do Sul, Center for Remote Sensing, Av. Bento Gonçalves, 9500 91501-970 Porto Alegre, RS, Brazil

Silvia Beatriz Alves Rolim

Federal University of Rio Grande do Sul, Center for Remote Sensing, Av. Bento Gonçalves, 9500 91501-970 Porto Alegre, RS, Brazil

Yosio Edemir Shimabukuro

National Institute for Space Research, Remote Sensing Division, Av. dos Astronautas 1758, 12227-010 São José dos Campos, SP, Brazil

J. Appl. Remote Sens. 7(1), 073502 (Oct 04, 2013). doi:10.1117/1.JRS.7.073502
History: Received June 25, 2013; Revised August 27, 2013; Accepted September 10, 2013
Text Size: A A A

Abstract.  Hyperspectral remote sensing can provide information about species richness over large areas and may be useful for species discrimination in tropical environments. Here, we analyze the main sources of variability in leaf spectral signatures of tropical trees and examine the potential of spectroscopic reflectance measurements (450 to 2450 nm) for tree species discrimination. We assess within- and among-species spectral variability and perform a feature selection procedure to identify wavebands in which the species most differ from each other. We assess the discriminative power of these wavebands by calculating a separability index and then classifying the species. Finally, leaf chemical and structural parameters of each species are retrieved by inversion of the leaf optical model PROSPECT-5. Among-species spectral variability is almost five times greater than within-species spectral variability. The feature selection procedure reveals that wavebands, where species most differ, are located at the visible, red edge, and shortwave infrared regions. Classification of the species using these wavebands reaches 96% overall accuracy. Leaf chemical and structural properties retrieve by model inversion show that differences in leaf pigment concentrations and leaf internal structure are the most important parameters controlling the spectral variability of species. These parameters also contribute to the variation in red edge position among species.

Figures in this Article
© 2013 Society of Photo-Optical Instrumentation Engineers

Citation

Matheus Pinheiro Ferreira ; Atilio Efrain Bica Grondona ; Silvia Beatriz Alves Rolim and Yosio Edemir Shimabukuro
"Analyzing the spectral variability of tropical tree species using hyperspectral feature selection and leaf optical modeling", J. Appl. Remote Sens. 7(1), 073502 (Oct 04, 2013). ; http://dx.doi.org/10.1117/1.JRS.7.073502


Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

Advertisement
  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.