Kakadu National Park and its wetlands are World Heritage and Ramsar listed and are at risk from invasive grasses. However, it appears that not all habitats and native vegetation are equally at risk. We conduct a spatial risk assessment for para grass (Urochloa mutica) invasion across seasonally inundated habitats of the 258 km2 Magela Creek floodplain within Kakadu National Park using Landsat 5 TM time-series imagery. Two maps, representing water depth and fire history, were derived from the imagery using object-based image analyses. Depth was modelled using a linear regression relationship established between 254 known water depth locations and the multi-date spectral index values of segmented image objects at corresponding locations (R2 = 0.67; p < 0.0001). Binary fire-scar maps were then produced for each year of a 10-year period using visual interpretation and nearest neighbour classification. A map of the incidence of annual fire over this period was then calculated from the sum of the maps, overlaid. The maps were integrated in a GIS with an existing Landsat vegetation map to measure spatial inter-relationships between para grass, native vegetation, depth and fire. With a highly clustered distribution pattern, para grass occupied 1388 ha or 6% of the total floodplain area. However, its optimal depth habitat, estimated to be from 1.1 to 1.4 m, occurred over a much larger area (7180 ha) or 30% of the floodplain. Only 2% of this optimal area was actually occupied by para grass. Together the low occupancy of ‘optimal-depth’ habitat and a highly clustered distribution of para grass strongly suggested that, if left uncontrolled, it has capacity to spread further and eventually occupy much larger areas of this floodplain at high density. Landsat provided spatial information of suitable scale and accuracy to understand the landscape ecology of para grass; and from which to design and conduct further research, or trial management interventions to protect wetland vegetation at risk to weed invasion.
|Number of pages
|International Journal of Applied Earth Observation and Geoinformation
|Early online date
|19 May 2018
|Published - Sept 2018