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Proceedings Paper

Airborne hyperspectral imaging for the detection of powdery mildew in wheat
Author(s): Jonas Franke; Thorsten Mewes; Gunter Menz
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Paper Abstract

Plant stresses, in particular fungal diseases, show a high variability in spatial and temporal dimension with respect to their impact on the host. Recent "Precision Agriculture"-techniques allow for a spatially and temporally adjusted pest control that might reduce the amount of cost-intensive and ecologically harmful agrochemicals. Conventional stressdetection techniques such as random monitoring do not meet demands of such optimally placed management actions. The prerequisite is an accurate sensor-based detection of stress symptoms. The present study focuses on a remotely sensed detection of the fungal disease powdery mildew (Blumeria graminis) in wheat, Europe's main crop. In a field experiment, the potential of hyperspectral data for an early detection of stress symptoms was tested. A sophisticated endmember selection procedure was used and, additionally, a linear spectral mixture model was applied to a pixel spectrum with known characteristics, in order to derive an endmember representing 100% powdery mildew-infected wheat. Regression analyses of matched fraction estimates of this endmember and in-field-observed powdery mildew severities showed promising results (r=0.82 and r2=0.67).

Paper Details

Date Published: 27 August 2008
PDF: 10 pages
Proc. SPIE 7086, Imaging Spectrometry XIII, 708609 (27 August 2008); doi: 10.1117/12.795040
Show Author Affiliations
Jonas Franke, Ctr. for Remote Sensing of Land Surfaces (Germany)
Thorsten Mewes, Ctr. for Remote Sensing of Land Surfaces (Germany)
Gunter Menz, Ctr. for Remote Sensing of Land Surfaces (Germany)
Univ. of Bonn (Germany)


Published in SPIE Proceedings Vol. 7086:
Imaging Spectrometry XIII
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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