Exploring Hyperspectral and Very High Spatial Resolution Imagery in Vegetation Characterization
dc.contributor.advisor | Hu, Baoxin | |
dc.creator | Zhang, Kongwen | |
dc.date.accessioned | 2015-08-28T15:01:22Z | |
dc.date.available | 2015-08-28T15:01:22Z | |
dc.date.copyright | 2014-08-22 | |
dc.date.issued | 2015-08-28 | |
dc.date.updated | 2015-08-28T15:01:22Z | |
dc.degree.discipline | Earth & Space Science | |
dc.degree.level | Doctoral | |
dc.degree.name | PhD - Doctor of Philosophy | |
dc.description.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. | |
dc.identifier.uri | http://hdl.handle.net/10315/29915 | |
dc.language.iso | en | |
dc.rights | Author owns copyright, except where explicitly noted. Please contact the author directly with licensing requests. | |
dc.subject | Remote sensing | |
dc.subject | Forestry | |
dc.subject.keywords | Remote Sensing | |
dc.subject.keywords | Hyperspectral | |
dc.subject.keywords | High spatial resolution imagery | |
dc.title | Exploring Hyperspectral and Very High Spatial Resolution Imagery in Vegetation Characterization | |
dc.type | Electronic Thesis or Dissertation | en_US |
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