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Mapping invasive Phragmites australis in the coastal Great Lakes with ALOS PALSAR satellite imagery for decision support

Journal of Great Lakes Research

By:
, , , , , , , , , , ,
DOI: 10.1016/j.jglr.2012.11.001

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Abstract

The invasive variety of Phragmites australis (common reed) forms dense stands that can cause negative impacts on coastal Great Lakes wetlands including habitat degradation and reduced biological diversity. Early treatment is key to controlling Phragmites, therefore a map of the current distribution is needed. ALOS PALSAR imagery was used to produce the first basin-wide distribution map showing the extent of large, dense invasive Phragmites-dominated habitats in wetlands and other coastal ecosystems along the U.S. shore of the Great Lakes. PALSAR is a satellite imaging radar sensor that is sensitive to differences in plant biomass and inundation patterns, allowing for the detection and delineation of these tall (up to 5 m), high density, high biomass invasive Phragmites stands. Classification was based on multi-season ALOS PALSAR L-band (23 cm wavelength) HH and HV polarization data. Seasonal (spring, summer, and fall) datasets were used to improve discrimination of Phragmites by taking advantage of phenological changes in vegetation and inundation patterns over the seasons. Extensive field collections of training and randomly selected validation data were conducted in 2010–2011 to aid in mapping and for accuracy assessments. Overall basin-wide map accuracy was 87%, with 86% producer's accuracy and 43% user's accuracy for invasive Phragmites. The invasive Phragmites maps are being used to identify major environmental drivers of this invader's distribution, to assess areas vulnerable to new invasion, and to provide information to regional stakeholders through a decision support tool.

Geospatial Extents

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Mapping invasive Phragmites australis in the coastal Great Lakes with ALOS PALSAR satellite imagery for decision support
Series title:
Journal of Great Lakes Research
DOI:
10.1016/j.jglr.2012.11.001
Volume
39
Issue:
Suppl. 1
Year Published:
2013
Language:
English
Publisher:
Elsevier
Contributing office(s):
Great Lakes Science Center
Description:
13 p.
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
First page:
65
Last page:
77
Number of Pages:
13
Country:
United States
Other Geospatial:
Lake Erie;Lake Huron;Lake Michigan;Lake Ontario;Lake Superior