A method to map riparian exotic vegetation (Salix spp.) area to inform water resource management
Article first published online: 9 JUL 2013
Copyright © 2013 John Wiley & Sons, Ltd.
Volume 28, Issue 11, pages 3809–3823, 30 May 2014
How to Cite
Doody, T. M., Lewis, M., Benyon, R. G. and Byrne, G. (2014), A method to map riparian exotic vegetation (Salix spp.) area to inform water resource management. Hydrol. Process., 28: 3809–3823. doi: 10.1002/hyp.9916
- Issue published online: 19 MAY 2014
- Article first published online: 9 JUL 2013
- Accepted manuscript online: 22 MAY 2013 09:42PM EST
- Manuscript Accepted: 20 MAY 2013
- Manuscript Received: 29 JAN 2013
- water salvage;
- water savings;
- remote sensing
Hydrological processes within riparian environments worldwide are impacted when introduced species invade. Monitoring and management at substantial expense, are subsequently required to combat deleterious effects on the environment and stream hydrology. Willow species (Salicaceae: Salix spp.) introduced into Australia have spread throughout many riparian systems causing adverse environmental impacts, with high rates of water extraction when located within stream beds (in-stream willows) thus altering hydrology. Strategies exist to manage willows; however, simpler, more cost-effective methods are required to map and monitor spatial and temporal distributions. A method is presented to discriminate willow stands from surrounding native riparian vegetation using a single, very high 2 m resolution multispectral WorldView-2 satellite image. A combination of spectral bands ‘coastal blue’ (400–450 nm), ‘red’ (630–690 nm), ‘red edge’ (705–745 nm) and ‘near infrared2’ (860–1040 nm), minimum noise fraction transformation, median filtering and maximum likelihood supervised classification provided the highest discriminatory power within a 25 km2 study area. Of the spectral bands, coastal blue, red edge and near infrared2 are new bands that are not available in other multispectral sensors. These bands proved critical to the success of discriminating willows from other land cover categories (overall accuracy of 97%). Stream channels were defined by incorporating a LiDAR-derived digital elevation model to discriminate between willows on stream banks and within stream beds. Canopy area estimates of in-stream willows, coupled with water savings estimates from willow removal, suggest removal of 10.4 ha of Salix fragilis canopy from within river channels in the study area will potentially return 41 ML year−1 to the environment. The method presented improves our understanding of willow impacts on hydrology and aids decisions regarding willow removal for water resource management. Copyright © 2013 John Wiley & Sons, Ltd.