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Detecting and Mapping Four Invasive Species along the Floodplain of North Platte River, Nebraska

Published online by Cambridge University Press:  20 January 2017

Sunil Narumalani ,
Deepak R. Mishra ,
Robert Wilson ,
Patrick Reece  and
Ann Kohler
Sunil Narumalani*
Affiliation:
School of Natural Resources, 302 Hardin Hall, University of Nebraska, Lincoln, NE 68583
Deepak R. Mishra
Affiliation:
Pontchartrain Institute for Environmental Sciences, Earth and Environmental Sciences, 1065 Geology and Psychology, University of New Orleans, New Orleans, LA 70148
Robert Wilson
Affiliation:
UNL Panhandle Research and Extension Center, 4502 Avenue I, Scottsbluff, NE, 69361
Patrick Reece
Affiliation:
UNL Panhandle Research and Extension Center, 4502 Avenue I, Scottsbluff, NE, 69361
Ann Kohler
Affiliation:
UNL Panhandle Research and Extension Center, 4502 Avenue I, Scottsbluff, NE, 69361
*
Corresponding author's E-mail: [email protected].
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Abstract

Geospatial technologies are increasingly important tools used to assess the spatial distributions and predict the spread of invasive species. The objective of our research was to quantify and map four dominant invasive plant species, including saltcedar, Russian olive, Canada thistle, and musk thistle, along the flood plain of the North Platte River corridor within a 1-mile (1.6-km) buffer. Using the Airborne Imaging Spectroradiometer for Applications (AISA) hyperspectral imager (from visible to near infrared), we evaluated an image processing technique known as spectral angle mapping for mapping the invasive species distribution. A minimum noise fraction algorithm was used to remove the inherent noise and redundancy within the dataset during the classification. The classification algorithm applied on the AISA image revealed five categories of invasive species distribution including (1) saltcedar; (2) Russian olive; and a mix of (3) Canada and musk thistle, (4) Canada/musk thistle and reed canary grass, or (5) Canada/musk thistle, saltcedar, and reed canary grass. Validation procedures confirmed an overall map accuracy of 74%. Saltcedar and Russian olive classes showed producer and user accuracies of greater than 90%, whereas the mixed categories revealed accuracy values of between 35 and 74%. The immediate benefit of this research has been to provide information on the spatial distribution of invasive species to land managers for implementation of management programs. In addition, these data can be used to establish a baseline of the species distributions for future monitoring and control efforts.

Keywords

Canada thistle, Cirsium arvense L. Scop.musk thistle, Carduus nutans L.reed canary grass, Phalaris arundinacea L.Russian olive, Elaeagnus angustifolia L.saltcedar, Tamarix sp. LourHyperspectralminimum noise fractionremote sensingspectral angle mapping
Type
Weed Management—Techniques
Information
Weed Technology , Volume 23 , Issue 1 , March 2009 , pp. 99 - 107
Copyright
Copyright © Weed Science Society of America 

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References

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