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8/2/2019 201239 Walden, Dave Monitoring Wetland Weeds Using Remotely Sensed Data in Kakadu National Park, Northern Territory, Australia
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Supervising Scientist - working to protect the environment from the impacts of uranium mining
www.environment.gov.au/ssd
Monitoring the wetland weed paragrass (Urochloa mutica) using
remotely sensed data in KakaduNational Park, Northern Territory
Dave Walden, James Boyden & Renee Bartolo
Environmental Research Institute of the Supervising Scientist
8/2/2019 201239 Walden, Dave Monitoring Wetland Weeds Using Remotely Sensed Data in Kakadu National Park, Northern Territory, Australia
2/18
2Supervising Scientist Division
Project Overview
July 2004 a multispectral QuickBird satellite captureof 64 km2 of the central region (highest density ofpara grass) of the Magela floodplain in KNP
Airboat and helicopter field validation surveys inMarch 2003 and June 2004
Able to estimate the cover of para grass within the
image boundary and the rate of spread usinghistorical data
Data also incorporated into cost-of-control and
Bayesian habitat suitability models
8/2/2019 201239 Walden, Dave Monitoring Wetland Weeds Using Remotely Sensed Data in Kakadu National Park, Northern Territory, Australia
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3Supervising Scientist Division
Para grass as a weed
A trailing perennial grass with long, robust creeping culms(stolons or stems) that sprout new roots at the nodes whereverthey contact the ground
Also colonises floating vegetation mats that can break apart
and float downstream, thus increasing spread
Fast growing with no pests/diseases and a very broadenvironmental niche tolerant of inundation at a wide range ofwater depth from moist ground to 200 cm
Widespread distribution as it is valued by pastoralists as idealbuffalo/cattle fodder and actively planted in the region as earlyas 1922 and right up to the KNP declaration in 1979
8/2/2019 201239 Walden, Dave Monitoring Wetland Weeds Using Remotely Sensed Data in Kakadu National Park, Northern Territory, Australia
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Key impacts of para grass
Can modify landscapes by forming monocultures overlarge areas thus reducing biodiversity
Para grass readily outcompetes (amongst other flora)
wild rice (Oryza spp.) and sedges (Eleocharis spp.).Species that are essential food and nesting resources formagpie geese and some other waterbirds
The denser structure and higher biomass reduces waterflows thus increasing sediment deposition. Greater fuelloads increase intensity and extent of floodplain fireswhich can kill fringing paperbarks and other species
8/2/2019 201239 Walden, Dave Monitoring Wetland Weeds Using Remotely Sensed Data in Kakadu National Park, Northern Territory, Australia
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5Supervising Scientist Division
Kakadu NationalPark, the Magelafloodplain & theextent of theQuickBird image
8/2/2019 201239 Walden, Dave Monitoring Wetland Weeds Using Remotely Sensed Data in Kakadu National Park, Northern Territory, Australia
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6Supervising Scientist Division
Raw 2004
QuickBirdimage
Woodland
Wetland
8/2/2019 201239 Walden, Dave Monitoring Wetland Weeds Using Remotely Sensed Data in Kakadu National Park, Northern Territory, Australia
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Image analyses vegetation map
Supervised classification using six training classes para
grass (2 forms), dominant native vegetation types, and openwater
Training areas for classification were selected using the
spatially referenced ground and low-level helicopter surveydata. Wherever possible, training sites were selected fromwithin discreet homogeneous patches of a particular class
Map class Producer accuracy User accuracy
Para grass (high greenness) 90 % 96 %
Para grass (low greenness) 96 % 92 %
Overall (all classes) 86 %
8/2/2019 201239 Walden, Dave Monitoring Wetland Weeds Using Remotely Sensed Data in Kakadu National Park, Northern Territory, Australia
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Vegetation
class map fromsupervisedclassification
8/2/2019 201239 Walden, Dave Monitoring Wetland Weeds Using Remotely Sensed Data in Kakadu National Park, Northern Territory, Australia
9/189Supervising Scientist Division
Image analyses para grass cover
The vegetation class map was resampled to 5 mpixels. From this map a raster layer was producedfor para grass only (other map classes removed)
Using this data (and a 250 m zone-grid overlay),the percentage cover of para grass within each250 m grid cell was estimated i.e. dividing thetotal number of 5 m para grass classed pixels
falling within each 250 m grid cell, by the totalarea of each grid cell
8/2/2019 201239 Walden, Dave Monitoring Wetland Weeds Using Remotely Sensed Data in Kakadu National Park, Northern Territory, Australia
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Para grass cover
map derived fromthe vegetation map
8/2/2019 201239 Walden, Dave Monitoring Wetland Weeds Using Remotely Sensed Data in Kakadu National Park, Northern Territory, Australia
11/1811Supervising Scientist Division
Early para grass spread on the Magela
Small patches observed amongst the nativeHymenachne acutigluma on the Western Plains of theMagela floodplain KNP in 1982-83
An eriss project (Knerr 1998) based on aerialphotography and ground mapping of the same regionshowed that para grass cover in 1991 was 132 ha andby 1996 had spread to 422 ha (more than tripled in 5-6years)
This initial spread increased rapidly as the grazing andtrampling impacts of buffalo were reduced during the1980s early 1990s
8/2/2019 201239 Walden, Dave Monitoring Wetland Weeds Using Remotely Sensed Data in Kakadu National Park, Northern Territory, Australia
12/1812Supervising Scientist Division
More recent para grass spread
In 2004 the total area of para grass cover in this central
floodplain region as derived from the cover map was 1250ha
Para grass was distributed over 35% of the floodplain with
10% displacement of the native vegetation being largelywild rice mixed with sedges. Many satellite infestationsparticularly to the north (ie downstream)
Average spread rate calculated at 14% p.a. or a doubling in
extent every 5 years
Comprehensive helicopter surveys (Parks, NT WeedsBranch and CDU) in 2009 calculated 3513 ha of para grassover the central region
8/2/2019 201239 Walden, Dave Monitoring Wetland Weeds Using Remotely Sensed Data in Kakadu National Park, Northern Territory, Australia
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Para grass spread (not including 2009 data)
Linear regression between Loge extent (km2) of para grass and time (yrs)
(R2=69%, n=5, P
8/2/2019 201239 Walden, Dave Monitoring Wetland Weeds Using Remotely Sensed Data in Kakadu National Park, Northern Territory, Australia
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Future work
The Spatial Sciences and Data Integration group at eriss now
acquires an annual (VHSR) WorldView-2 image capture of theMagela floodplain and Ranger minesite
Using the GEOBIA approach it should be possible to continuemonitoring and detect more subtle changes (including any control
efforts) in para grass cover compared to previous mapping efforts
In addition, SSDI will soon acquire a LiDAR 30cm DEM of theMagela floodplain. This will yield valuable hydrological/inundationdata, factors which are critical in determining the distribution of
floodplain flora
Such information should further our knowledge of spread rates andhabitat suitability, information that can be used to develop andimprove management strategies
8/2/2019 201239 Walden, Dave Monitoring Wetland Weeds Using Remotely Sensed Data in Kakadu National Park, Northern Territory, Australia
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WV-2 image May 2010
Para grass
8/2/2019 201239 Walden, Dave Monitoring Wetland Weeds Using Remotely Sensed Data in Kakadu National Park, Northern Territory, Australia
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WV-2 image May 2010QuickBird July 2004
8/2/2019 201239 Walden, Dave Monitoring Wetland Weeds Using Remotely Sensed Data in Kakadu National Park, Northern Territory, Australia
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Bayesian HabitatSuitability Model byKeith Ferdinands
8/2/2019 201239 Walden, Dave Monitoring Wetland Weeds Using Remotely Sensed Data in Kakadu National Park, Northern Territory, Australia
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WV-2 image May 2010
Gratuitous crocodile photo
Thank you