Use of remote sensing to map occurrence and spread of Phytophthora cinnamomi in Banksia woodlands on the Gnangara Groundwater System, Western Australia
Barbara A. Wilson A D , Katherine Zdunic B , Janine Kinloch A B and Graeme Behn C
+ Author Affiliations
- Author Affiliations
A Gnangara Sustainability Strategy, Department of Environment and Conservation, PO Box 1167, Bentley Delivery Centre, WA 6983, Australia.
B Geographic Information Services, Department of Environment and Conservation, 17 Dick Perry Drive, Kensington, WA 6151, Australia.
C Leeuwin Centre for Earth Sensing Technologies, 65 Brookway Road, Floreat, WA 6014, Australia.
D Corresponding author. Email: barbara.wilson@dec.wa.gov.au
Australian Journal of Botany 60(6) 495-505 https://doi.org/10.1071/BT11305
Submitted: 5 December 2011 Accepted: 6 June 2012 Published: 20 August 2012
Abstract
The soilborne plant pathogen Phytophthora cinnamomi is listed as one of the world’s 100 worst invasive alien species by the International Union for Conservation of Nature (IUCN). The impacts on native flora and fauna habitats have been identified as a key threatening process in Australia. Identifying and mapping diseased vegetation and the rate of spread of the disease is required for management; however, this is often difficult and costly. This study investigated the ability of using a time series of orthophotos (1953–2008) in combination with Landsat satellite imagery, including trend analysis, and GIS to identify the presence of vegetation impacted by P. cinnamomi at four sites in Banksia woodlands in Western Australia. Further, the historical extent and rate of spread of P. cinnamomi was assessed at one site between 1953 and 2008. Our assessment identified that three of the four sites were affected by P. cinnamomi, results that are consistent with on-ground surveys. Investigation of disease progression at one site found a large increase in the area impacted between 1974 and 1988 and the rate of spread was highest between 1953 and 1963 (1.286 m year−1) and lowest between 1997 and 2008 (0.526 m year−1). The techniques presented provide a cost-effective tool to monitor broad-scale vegetation dynamics over time for management of this plant pathogen.
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