reflectance. This suggests that vegetation cover has a strong
influence on the ability of band 5 to identify inundated areas.
The inability to identify vegetated areas that are also inundated
means that the derived inundation maps and hydroperiod
classification will only work reliably in areas of low vegetation
cover. This supports the step in the methodology to remove
areas of perennial vegetation from the analysis.
Results from the field plot provide a clear picture of the
physical attributes being mapped. This aspect is missing in
many other remote sensing studies that analyze wetland
dynamics (Kleinod et al., 2005; Lacaux et al., 2007; Rover
2010; Zhao et al., 2011). The reported mapping accuracy is
high, at 87%. However, as many sample plots were located in
the transition zone, where errors are most likely to occur, this
may understate the true accuracy. A large number of randomly
located sample points would provide a more robust assessment
of overall mapping accuracy. Due to the limited time in this
study and difficulties in accessing many of the sites this was not
possible.
5. CONCLUSION
The application of the inundation mapping to a calibrated series
of Landsat imagery allows the dynamics of individual wetlands
and wetlands spread across broad region to be assessed. In this
study the hydroperiod of 263 wetlands across an 80 by 15 km
area was assessed.
The field data collected in this study demonstrated that
inundation can be mapped to a high degree of accuracy in open
wetlands with low vegetation cover. However, when vegetation
cover increases the ability to detect inundation is lost.
Inundated areas were mapped to an overall accuracy of 87.5%.
The resulting hydroperiod datasets provides an accurate record
of inundation frequency which can be used to aid classification
of wetlands and also allows changes to inundation frequency
over time to be assessed.
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