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Predictive mapping of intertidal and shallow subtidal habitats using ALOS imagery and LiDAR bathymetry
Citation
Monk, J and Pope, A and Ierodiaconou, D and Otera, K and Mount, RE, Predictive mapping of intertidal and shallow subtidal habitats using ALOS imagery and LiDAR bathymetry, AMSA-NZMSS 2012 Program and Abstract book, 01-05 July 2012, Hobart, Tasmania, pp. 147. (2012) [Conference Extract]
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Abstract
The Corner Inlet-Nooramunga marine embayment and barrier island complex in eastern Victoria includes extensive sand
and mud flats with a dendritic network of tidal channels in the west in Corner Inlet and a more complex arrangement of
channels and islands to the east in Nooramunga. Maps of the predicted distribution of shallow subtidal and intertidal
habitats in two separate areas of the region covering a total of 34,000 ha) were developed from satellite spectral and
high resolution bathymetry data via an automated classification tree (Quick Unbiased Efficient Statistical Tree) approach.
Spectral data from ALOS (Advanced Land Observing Satellite) imagery, corrected for atmospheric effects using ground based
spectral samples and CSIROs AtCor process were combined with bathymetric data from airborne LiDAR (Light Detection and
Ranging) surveys at a 10m resolution. The main habitats identified in both areas were seagrass beds of either Zosteraceae
species or Posidonia australis, bare sand and mud and areas dominated by the filter feeder Pyura stolonifera. Small areas
of fringing reef were also identified in Corner Inlet. A total of 791 stratified ground-truthing points were used to train
and assess the automated classification which resulted in overall classification accuracies of 73% for Corner Inlet and 85%
for Nooramunga study areas. Advantages of this approach, compared to previous habitat mapping exercises, include the
ability to accurately and independently assess errors in habitat mapping, improved atmospheric correction of imagery
and repeatability for use in future assessments of change. Comparisons with prior mapping of these areas were limited
by differences in methodologies and were sensitive to the level of resolution in habitat categorization. Effects of and
approaches to dealing with this unquantifiable uncertainty in long-term monitoring and management of shallow water
habitats are explored using examples from this project.
Item Details
Item Type: | Conference Extract |
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Keywords: | GIS, mapping, marine habitat, Victoria |
Research Division: | Agricultural, Veterinary and Food Sciences |
Research Group: | Fisheries sciences |
Research Field: | Aquaculture and fisheries stock assessment |
Objective Division: | Environmental Management |
Objective Group: | Marine systems and management |
Objective Field: | Marine biodiversity |
UTAS Author: | Monk, J (Dr Jacquomo Monk) |
UTAS Author: | Otera, K (Mr Kan Otera) |
UTAS Author: | Mount, RE (Dr Richard Mount) |
ID Code: | 126681 |
Year Published: | 2012 |
Deposited By: | Ecology and Biodiversity |
Deposited On: | 2018-06-20 |
Last Modified: | 2018-06-21 |
Downloads: | 0 |
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