Mapping invasive phragmites australis using unoccupied aircraft system imagery, canopy height models, and synthetic aperture radar

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Abstract

Invasive plant species are an increasing worldwide threat both ecologically and finan-cially. Knowing the location of these invasive plant infestations is the first step in their control. Surveying for invasive Phragmites australis is particularly challenging due to limited accessibility in wetland environments. Unoccupied aircraft systems (UAS) are a popular choice for invasive species management due to their ability to survey challenging environments and their high spatial and temporal resolution. This study tested the utility of three-band (i.e., red, green, and blue; RGB) UAS imagery for mapping Phragmites in the St. Louis River Estuary in Minnesota, U.S.A. and Saginaw Bay in Michigan, U.S.A. Iterative object-based image analysis techniques were used to identify two classes, Phragmites and Not Phragmites. Additionally, the effectiveness of canopy height models (CHMs) created from two data types, UAS imagery and commercial satellite stereo retrievals, and the RADARSAT-2 horizontal-horizontal (HH) polarization were tested for Phragmites identification. The highest overall classification accuracy of 90% was achieved when pairing the UAS imagery with a UAS-derived CHM. Producer’s accuracy for the Phragmites class ranged from 3 to 76%, and the user’s accuracies were above 90%. The Not Phragmites class had user’s and producer’s accuracies above 88%. Inclusion of the RADARSAT-2 HH polarization caused a slight reduction in classification accuracy. Commercial satellite stereo retrievals increased commission errors due to decreased spatial resolution and vertical accuracy. The lowest classification accuracy was seen when using only the RGB UAS imagery. UAS are promising for Phragmites identification, but the imagery should be used in conjunction with a CHM.

Original languageEnglish (US)
Article number3303
JournalRemote Sensing
Volume13
Issue number16
DOIs
StatePublished - Aug 20 2021

Bibliographical note

Funding Information:
This work was funded by the Legislative and Citizen Commission for Minnesota Resources through Minnesota’s Environment and Natural Resources Trust Fund (ENRTF) via the Minnesota Invasive Terrestrial Plant and Pest Center (MITPPC) grant number ML2018 Ch214 Art.4 Sec.2 Sub.06a E818ITP. Acknowledgments: Data for two of the UAS acquisitions were provided by the University of Minnesota Duluth NRRI GIS Lab and the Michigan Technological Research Institute. Satellite-derived DSMs were created by the University of Minnesota Polar Geospatial Center from DigitalGlobe, Inc. imagery.

Funding Information:
Funding: This work was funded by the Legislative and Citizen Commission for Minnesota Resources through Minnesota’s Environment and Natural Resources Trust Fund (ENRTF) via the Minnesota Invasive Terrestrial Plant and Pest Center (MITPPC) grant number ML2018 Ch214 Art.4 Sec.2 Sub.06a E818ITP.

Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Keywords

  • Invasive species
  • OBIA
  • Object-based classification
  • Phragmites australis
  • UAS

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