Exploring Hyperspectral and Very High Spatial Resolution Imagery in Vegetation Characterization

Abstract

This dissertation describes three contributions in the characterization of vegetation canopies using remote sensing data, with a focus on hyperspectral and very high spatial resolution imagery. The new and innovative methods developed are: 1) integration of contribution theory into a model inversion approach to obtain high accuracy in canopy biophysical parameter estimation; 2) exploration and adoption of tree crown longitudinal profiles to achieve high accuracy in tree species classification; and 3) evaluation of canopy health state for Emerald Ash Borer (EAB) infestation assessment by intelligent combination of multi-sourced data.