Exploring Hyperspectral and Very High Spatial Resolution Imagery in Vegetation Characterization

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.

Author dc:creator

• Zhang, Kongwen

Advisor dc:contributor.advisor

• Hu, Baoxin

• Remote sensing
• Forestry

Statement dc:rights

• Author owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.

Language dc:language.iso

en

Handle dc:identifier.uri

http://hdl.handle.net/10315/29915

OAI identifier oai:identifier

oai:yorkspace.library.yorku.ca:10315/29915