Estimation biochemical components in vegetation based on statistical learning methods and remote sensing data

Abstract

An approach for vegetation state estimation is presented in the paper. It is based on the determination of the chlorophyll content in the plant leaves using spectral data and statistical learning methods. The problem of model identification is presented as dual optimization problem. Also the experimental data obtaining procedure, numerical results and comparative analysis are shown.

Keywords

• remote sensing
• estimation
• SVM
• vegetation state
• model identification