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Mapping Invasive Phragmites australi...

Anderson, Connor John.

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Mapping Invasive Phragmites australis Using Unmanned Aircraft System Imagery, Canopy Height Models, and Synthetic Aperture Radar.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Mapping Invasive Phragmites australis Using Unmanned Aircraft System Imagery, Canopy Height Models, and Synthetic Aperture Radar./
作者:	Anderson, Connor John.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
面頁冊數:	39 p.
附註:	Source: Masters Abstracts International, Volume: 82-07.
Contained By:	Masters Abstracts International82-07.
標題:	Remote sensing. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28155268
ISBN:	9798557039871

Mapping Invasive Phragmites australis Using Unmanned Aircraft System Imagery, Canopy Height Models, and Synthetic Aperture Radar.
Anderson, Connor John.

Mapping Invasive Phragmites australis Using Unmanned Aircraft System Imagery, Canopy Height Models, and Synthetic Aperture Radar. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 39 p.

Source: Masters Abstracts International, Volume: 82-07.

Thesis (M.S.)--University of Minnesota, 2020.

This item must not be sold to any third party vendors.

Invasive plant species are an increasing worldwide threat both financially and ecologically. Knowing the location of these invasive plant infestations is the first step in their control. Surveying for Phragmites australis is particularly challenging due to limited accessibility in wetland environments. Unmanned aircraft systems (UASs) 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 90.2% was achieved when pairing the UAS imagery with a UAS-derived CHM. Producer's accuracy for the Phragmites class ranged from 2.7 to 75.6%, 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 overall classification accuracy was seen when using only the RGB UAS imagery. UASs are promising for Phragmites identification, but the imagery should be used in conjunction with a CHM.

ISBN: 9798557039871Subjects--Topical Terms:

535394
Remote sensing.
Subjects--Index Terms:

Phragmites australis

Mapping Invasive Phragmites australis Using Unmanned Aircraft System Imagery, Canopy Height Models, and Synthetic Aperture Radar.
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520 $a Invasive plant species are an increasing worldwide threat both financially and ecologically. Knowing the location of these invasive plant infestations is the first step in their control. Surveying for Phragmites australis is particularly challenging due to limited accessibility in wetland environments. Unmanned aircraft systems (UASs) 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 90.2% was achieved when pairing the UAS imagery with a UAS-derived CHM. Producer's accuracy for the Phragmites class ranged from 2.7 to 75.6%, 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 overall classification accuracy was seen when using only the RGB UAS imagery. UASs are promising for Phragmites identification, but the imagery should be used in conjunction with a CHM.
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