Please Note:

The Open Access Repository will be moving to a new authentication system on the 1st of November.

From this date onwards, account holders will be required to login using their University of Tasmania credentials.
If your current repository username differs from your University username, please email E.Prints@utas.edu.au so we can update these details on your behalf.

Due to the change, there will be a short outage of the repository from 9am on the morning of the 1st of November

Open Access Repository

Predicting Mycosphaerella leaf disease severity in a Eucalyptus globulus plantation using digital multi-spectral imagery

Downloads

Downloads per month over past year

Pietrzykowski, E and Sims, N and Stone, C and Pinkard, EA and Mohammed, CL (2007) Predicting Mycosphaerella leaf disease severity in a Eucalyptus globulus plantation using digital multi-spectral imagery. Southern Hemisphere Forestry Journal, 69 (3). pp. 175-182. ISSN 1991-9328

[img] PDF
3701.pdf | Request a copy
Full text restricted

Abstract

Digital remote sensing is rapidly developing into an operational tool for forest health assessment at a range of scales. Akey
aspect of this development is the derivation of models relating spectral data contained in the images to the extent and
severity of plant stress symptoms. This study assesses the utility of high spatial resolution (0.5m
X 0.5m pixel size) airborne
digital imagery to assess the presence and severity of defoliation and necrosis from Mycosphaerella leaf disease at the
crown scale across a small plantation in north-western Tasmania, Australia. The best model of defoliation included the
2
variance of reflectance at 780nm within the crown (r
= 0.5; p < 0.0001) and the best model of necrosis included the ratio of
2
reflectance at 680nm/550nm (r
= 0.3; p < 0.0001). Maps derived from these linear models clearly illustrate the distribution
and gradient of disease severity observed in the field. Error matrix analysis indicates moderate map accuracy for classified
versions of both defoliation (OA= 71%; Kappa = 0.63) and necrosis (OA= 67%; Kappa = 0.54) but the maps reveal
additional information about the distribution and severity of symptoms throughout the plantation. Methods such as those
described in this paper may enable managers to more accurately target remedial actions. The transfer of this technology to
space-borne platforms will potentially improve map accuracy and image availability, and reduce the cost of image collec-
tion. Together, these improvements increase the likelihood of remote sensing being incorporated into forest management
strategies in future.

Item Type: Article
Keywords: disease severity, Eucalyptus globulus, Mycosphaerella, remote sensing
Journal or Publication Title: Southern Hemisphere Forestry Journal
Publisher: Southern African Institute of Forestry
Page Range: pp. 175-182
ISSN: 1991-9328
Identification Number - DOI: 10.2989/SHFJ.2007.69.3.7.357
Date Deposited: 07 Apr 2008 14:02
Last Modified: 18 Nov 2014 03:32
Item Statistics: View statistics for this item

Actions (login required)

Item Control Page Item Control Page
TOP