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Detecting Spotted Knapweed (Centaurea maculosa) with Hyperspectral Remote Sensing Technology

Published online by Cambridge University Press:  20 January 2017

Lawrence W. Lass ,
Donald C. Thill ,
Bahman Shafii  and
Timothy S. Prather
Lawrence W. Lass*
Affiliation:
Department of Plant, Soil, and Entomological Sciences
Donald C. Thill
Affiliation:
Department of Plant, Soil, and Entomological Sciences
Bahman Shafii
Affiliation:
College of Agriculture, University of Idaho, Moscow, ID 83844-2339
Timothy S. Prather
Affiliation:
Department of Plant, Soil, and Entomological Sciences
*
Corresponding author's E-mail: llass@uidaho.edu.
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Abstract

Failure to detect noxious weeds with current survey methods prevents their control and has contributed to their ability to establish and spread in remote range and forest sites. Techniques used in remote sensing can classify plant occurrence on maps, offering a method for surveying invasive species in remote locations and across extensive areas. An imaging hyperspectral spectrometer recorded images on July 19, 1998 in Farragut State Park near Bayview, ID, in the reflected solar region of the electromagnetic spectrum ranging from 440 to 2,543 nm to detect spotted knapweed. The sensor records 128 spectral bands in 12- to 16-nm intervals at a spatial resolution of 5 m. A spectral angle mapper (SAM) algorithm was used to classify the data. Infestations in Idaho with 70 to 100% spotted knapweed cover that were 0.1 ha were detected regardless of the classification angle. However, narrow angles (2 to 8°) did not completely define the extent of the infestation, and the widest angle tested (20°) falsely classified some areas as infested. The overall image error for all classes was lowest (3%) when SAM angles ranged from 10 to 11°. Specific errors for the spotted knapweed class for the 10 to 11° angles showed that omissional and commissional errors were less than 3%. Areas with as little as 1 to 40% spotted knapweed cover were detected with an omissional error of 1% and a commissional error of 6%. Further verification sites were established on August 11, 1998 near Bozeman, MT, using the algorithms developed for Idaho. The omissional error for the Montana sites was 0%, and the commissional error was 10%. The hyperspectral sensor, Probe 1, proved an effective detection tool with the ability to detect spotted knapweed infestations.

Keywords

Spotted knapweedCentaurea maculosa Lam. #3 CENMA syn C. stoebe L. and C. biebersteinii DCHyperspectral sensorimaging spectrometerweed detectionwhiskbroom scannerĈi, commissional errorDGPS, differentially corrected global positioning systemGPS, global positioning system without differential correctionL95, lower bounds expressed as 95% probability intervalÔi, omissional errorSAM, spectral angle mapperU95, upper bounds expressed as 95% probability interval
Type
Research
Information
Weed Technology , Volume 16 , Issue 2 , June 2002 , pp. 426 - 432
Copyright
Copyright © Weed Science Society of America 

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