NDLI: Requirements on spectral resolution of remote sensing data for crop stress detection

Content Provider	IEEE Xplore Digital Library
Author	Franke, J. Mewes, T. Menz, G.
Copyright Year	2009
Description	Author affiliation: University of Bonn, Center for Remote Sensing of Land Surfaces (ZFL), Walter-Flex-Strasse 3, 53113 Bonn, Germany (Franke, J.; Mewes, T.; Menz, G.)
Abstract	Hyperspectral data proved to be highly suitable to identify areas of crop growth anomalies resulting from stress impact (e.g., nitrogen deficiency, fungal infections etc.). Stress symptoms are changes in plant physiology, whose characteristics affect the spectral signature of crop canopies that are consequently detectable via spectral measurements. Typical stress-related spectral changes in plant canopy signatures do not cause narrow spectral features, but rather influence certain wavelength ranges in the VIS and NIR. Sensor-based crop stress detection has certain requirements on the minimum spectral resolution of sensor systems. However, the question of whether the plentitude of narrow spectral bands of hyperspectral sensors is needed for crop stress detection arises. To analyze on which spectral scales stress symptoms can be detected, HyMap data was stepwise spectrally resampled and used for spectral mixture analyses to estimate powdery mildew severity of wheat. Results from 7 spectrally resampled data sets were compared to in-field sampled stress severity data. Results showed that the highest spectral resolution is actually not necessary to detect stressed wheat areas. Even with spectral resolutions 3 times lower than the original data set, regression analysis of endmember fractions and disease severities showed a satisfying coefficient of determination of $R^{2}=3D0.55.$
File Size	459839
File Format	PDF
ISBN	9781424433940
DOI	10.1109/IGARSS.2009.5416884
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-07-12
Publisher Place	South Africa
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Remote sensing Crops Hyperspectral sensors Spectral analysis Hyperspectral imaging Nitrogen Physiology Stress measurement Wavelength measurement Sensor systems spectral mixture analysis Crop stress detection endmember modeling HyMap Precision Agriculture
Content Type	Text
Resource Type	Article

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