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Detection of Leafy Spurge (Euphorbia esula) Using Multidate High-Resolution Satellite Imagery

Published online by Cambridge University Press:  20 January 2017

Grant M. Casady ,
Rodney S. Hanley  and
Santhosh K. Seelan
Grant M. Casady
Affiliation:
Arizona Remote Sensing Laboratory, Office of Arid Lands Studies, University of Arizona, Tucson, AZ 85719-0184
Rodney S. Hanley
Affiliation:
Upper Midwest Aerospace Consortium, University of North Dakota, Grand Forks, ND 58202-9007
Santhosh K. Seelan
Affiliation:
Upper Midwest Aerospace Consortium, University of North Dakota, Grand Forks, ND 58202-9007
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Abstract

Leafy spurge is a deep-rooted perennial weed that displaces native rangeland vegetation and replaces forage for cattle and other forages used by vertebrate herbivores. Strategic planning to control this weed requires monitoring its distribution and spread. Classical monitoring techniques, which often involve extensive ground survey efforts, can be aided by the synoptic nature of remotely sensed imagery. This research addresses the use of Space Imaging's 4-m multispectral Ikonos imagery for the survey and detection of leafy spurge infestations. Survey data were collected at a site in western North Dakota and used to produce supervised classifications of leafy surge infestations with Ikonos imagery. Multiple image dates per year were combined with each other to assess the added accuracy afforded by multitemporal imagery. Finally, individual patches of leafy spurge were analyzed to determine the minimum patch size and percent cover that were detectable with supervised classification of Ikonos imagery. Under some circumstances, the imagery was effective at detecting leafy spurge, but in areas with a higher forb component, the classification was not as effective. Multidate imagery provided increased accuracy, but improvements were not consistently significant. Leafy spurge infestations of <30% cover and 200 m2 were not reliably detected.

Keywords

Leafy spurge, Euphorbia esula L. # EPHESAccuracy assessmentdigital photographyEPHESglobal positioning systemIkonosimage analysisGPS, global positioning systemRMS, root-mean-square
Type
Research Article
Information
Weed Technology , Volume 19 , Issue 2 , June 2005 , pp. 462 - 467
Copyright
Copyright © Weed Science Society of America 

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