Root disease is a serious concern for the softwood timber industry. This thesis reports
on the development of a root disease detection procedure that applies lidar data integrated
with imaging spectrometer data. Photosynthetic pigments are frequently cited as one of
the most responsive indicators of vegetation stress. This study estimated pigment content
from needle and canopy reflectance and characterized the sensitivity of these pigments to
a fungal-mediated stress. Samples were collected from the Greater Victoria Watershed
District on Vancouver Island, BC, Canada. Lab reflectance measurements were made and
pigments were extracted. Reflectance spectra were transformed into derivative spectra
and a continuum removal band depth analysis was conducted. Reflectance metrics were
generated and used in modeling pigment content. Chlorophyll-a was found to be
significantly affected by the disease in the needle level portion of this study. The
predictive power of reflectance attributes were assessed and yielded strong coefficients of
determination (R2>0.80). Samples exhibiting stress responses affected by root disease
were discriminated. It was determined that younger trees were more severely affected by
the root pathogen than mature colonized trees. In the canopy level component of the
study, chlorophyll-a was estimated through the application of partial least squares
regression and achieved an R2 value of 0.82. Continuum removal metrics, which proved
to be good estimators at the needle level, were found to be insufficient at the canopy
level. Through the use of hyperspectral forest chemistry products, potential root disease
sites can be identified. / Graduate
| Identifer | oai:union.ndltd.org:uvic.ca/oai:dspace.library.uvic.ca:1828/3605 |
| Date | 17 October 2011 |
| Creators | Quinn, Geoffrey |
| Contributors | Niemann, K. O. |
| Source Sets | University of Victoria |
| Language | English, English |
| Detected Language | English |
| Type | Thesis |
| Rights | Available to the World Wide Web |
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