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United States Department of Agriculture

Agricultural Research Service

Title: Proceedings of the 13th Jpl Airborne Earth Science Workshop

Authors
item Hunt, Earle
item Parker-Williams, Amy - UNIV OF WYOMING

Submitted to: Jet Propulsion Laboratory Airborne Earth Science Workshop
Publication Type: Proceedings
Publication Acceptance Date: March 24, 2005
Publication Date: May 23, 2005
Citation: Hunt, E.R., Parker, A.E. 2005. Comparison of Aviris and multispectral remote sensing for detection of leafy spurge. In: Proceedings of the 13th Jet Propulsion Lab Airborne Earth Science Workshop, March 31-April 2, 2004, Pasadena, California. MS:1-8 CDROM.

Technical Abstract: The distribution and abundance of leafy spurge (Euphorbia esula L.) can be determined with hyperspectral remote sensing, but the availability of hyperspectral sensors is limited. Hence, the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and System Pour d'Observation de la Terre (SPOT) 4 imagery were acquired to test the ability of these sensors to detect leafy spurge. The green:red reflectance ratio was the vegetation index with the highest correlations to leafy spurge cover, but the correlations were weak and not useful for predictions. With Airborne Visible Infrared Imaging Spectrometer (AVIRIS) data, the green:red reflectance ratio was also very weakly correlated to spurge cover. Canopy reflectance modeling using the Scattering by Arbitrarily Inclined Leaves (SAIL) model suggests the poor correlations were caused by variations in leaf area index. Classification of flowering leafy spurge in the Landsat 7 ETM+, SPOT 4 and AVIRIS images with minimum distance supervised classification had statistically equal accuracies. Classification of flowering leafy spurge with the hyperspectral technique, the Spectral Angle Mapper, had a significantly higher accuracy for the AVIRIS image. Thus, use of multispectral techniques (supervised classification, indices) with hyperspectral data did not improve detection of leafy spurge compared to multispectral data (ETM+, SPOT).

Last Modified: 8/2/2014
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