Abstract

The invasion of the exotic common reed ( Phragmites australis) is increasingly displacing local native species from northeastern coastal estuaries. This study evaluates the accuracy of a remote sensing technique to map the distribution of common reed, monitor the rate of invasion and determine areas of natural resistance to invasion. The current invasion footprint of Phragmites in the Hackensack Meadowlands District in Northern New Jersey was determined using high spectral and spatial resolution hyperspectral imagery. A tethered balloon-based imaging device with limited coverage area was used to assess the accuracy of the hyperspectral imagery classification. The accuracy assessment based on true color balloon images revealed that the hyperspectral classification technique from images covering hundreds of hectares was 90% accurate in separating the dominant common reed-invaded areas from the native vegetation. Furthermore, linear spectral un-mixing techniques for sub-pixel classification revealed that for mixed areas where Phragmites covered 75% or more of a pixel, the classification was correct 96% of the time. The accuracy dropped to 52% for pixels that contained 25% or less of Phragmites cover, and was only 4% for pixels where invasive and native species cover was the same (50–50%).

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