Data reduction of hyperspectral remote sensing data for crop stress detection using different band selection methods

International Geoscience and Remote Sensing Symposium (IGARSS)

Volumn 3, Issue , 2009, Pages

  Mewes, Thorsten ^a   Franke, Jonas ^a   Menz, Gunter ^a  

^a UNIVERSITY OF BONN   (Germany)

Author keywords

AISA; Band selection; Bhattacharyya distance; Decision tree analysis; Stress detection

Indexed keywords

AGRICULTURAL MANAGEMENT; BAND SELECTION; BHATTACHARYYA DISTANCE; DECISION SUPPORTS; DECISION TREE ANALYSIS; ELECTROMAGNETIC SPECTRA; FUNGAL INFECTION; FUNGAL PATHOGEN; FUNGICIDE APPLICATION; HYPERSPECTRAL DATA; HYPERSPECTRAL IMAGE DATAS; HYPERSPECTRAL REMOTE SENSING DATA; REDUNDANT INFORMATIONS; SITE-SPECIFIC; SPECTRAL INFORMATION; SPECTRAL REFLECTANCES; STRESS DETECTION; STRESS-DEPENDENT;

CROPS; DATA REDUCTION; DECISION SUPPORT SYSTEMS; DECISION TREES; GEOLOGY; REDUCTION; REMOTE SENSING; STATISTICS;

STRESSES;

EID: 77950932763     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IGARSS.2009.5418292     Document Type: Conference Paper

References (17)

1. European Commission, Agriculture in the European Union - Statistical and economic information 2008, European Union Directorate-General for Agriculture and Rural Development, Brussels, Belgium, 2009.
2. W. Kühbauch and S. Hawlitschka, "Remote sensing - a future technology in precision farming," Proceedings of the Workshop on POLinSAR - Applications of SAR Polarimetry and Polarimetric Interferometry, ESA SP-529, Italy, 2003.
3. M.S. Moran, Y. Inoue and E.M. Barnes, "Opportunities and limitations for image-based remote sensing in precision crop management," Remote Sensing of Environment, vol.61, pp. 319-346, 1997.
4. P.J. Curran, "Remote Sensing of Foliar Chemistry," Remote Sensing of Environment, vol.30, pp. 271-278, 1989.
5. B.J. Yoder and R.E. Pettigrew-Crosby, "Predicting Nitrogen and Chlorophyll Content and Concentrations from Reflectance Spectra (400-2500nm) at Leaf and Canopy Scales," Remote Sensing of Environment, vol.53, pp. 199-211, 1995.
6. B. Lorenzen and A. Jensen, "Changes in Leaf Spectral Properties Induced in Barley by Cereal Powdery Mildew," Remote Sensing of Environment, vol.27, pp. 201-209, 1989.
7. C. Bravo, D. Moshou, J.S. West, A. McCartney, and H. Ramon, "Early disease detection in wheat fields using spectral reflectance," J.Biosyst.Eng., vol.84, pp. 137-145, 2003. (Pubitemid 36247146)
8. A. Apan, A. Held, S. Phinn, and J. Markley, "Detecting sugarcane 'orange rust' disease using EO-1 Hyperion hyperspectral imagery," International Journal of Remote Sensing, vol.25, pp. 489-498, 2004.
9. J. Franke and G. Menz, "Multi-temporal wheat disease detection by multi-spectral remote sensing," Precision Agriculture, vol.8, pp. 161-172, 2007. (Pubitemid 47039080)
10. J. Franke, T. Mewes, and G. Menz, "Airborne hyperspectral imaging for the detection of powdery mildew in wheat," Proceedings SPIE Optics & Photonics, vol.7086, San Diego, USA, 2008.
11. T. Mewes, J. Franke, and G. Menz, "Multitemporal spectroscopy for crop stress detection using band selection methods," Proceedings SPIE Optics & Photonics, vol.7086, San Diego, USA, 2008.
12. A.F.H. Goetz, "Three decades of hyperspectral remote sensing of the Earth: A personal view," Remote Sensing of Environment, in press, 2009.
13. J.S. West, C. Bravo, R. Oberti, D. Lemaire, D. Moshou, and H.A. McCartney, "The potential of optical canopy measurement for targeted control of field crop diseases," Ann.Rev.Phytopathol., vol.41, pp. 593-614, 2003.
14. L.O. Jimenez and D.A. Landgrebe, "Hyperspectral data analysis and supervised feature reduction via projection pursuit," IEEE Transactions on Geoscience and Remote Sensing, vol.37, pp. 2653-2667, 1999.
15. X. Miao, P. Gong, S. Swope, R.L. Pu, R. Carruthers, and G.L. Anderson, "Detection of yellow starthistle through band selection and feature extraction from hyperspectral imagery," Photogrammetric Engineering and Remote Sensing, vol.73, pp. 1005-1015, 2007.
16. M. Herold, M.E. Gardner, and D.A. Roberts, "Spectral resolution requirements for mapping urban areas," IEEE Transactions on Geoscience and Remote Sensing, vol.41, pp. 1907-1919, 2003.
17. R.S. DeFries and J.C.W. Chan, "Multiple criteria for evaluating machine learning algorithms for land cover classification from satellite data," Remote Sensing of Environment, vol.74, pp. 503-515, 2000.