Measuring crop status using multivariate analysis of hyperspectral field reflectance with application to disease severity and plant density

Precision Agriculture

Volumn 8, Issue 1-2, 2007, Pages 37-47

  Larsolle, A ^a   Hamid Muhammed, H ^b  

^a SWEDISH UNIVERSITY OF AGRICULTURAL SCIENCES   (Sweden)

^b Uppdaga HB   (Sweden)

Author keywords

Hyperspectral reflectance analysis; Plant density; Plant disease

Indexed keywords

CLASSIFICATION; DISEASE SEVERITY; FUNGAL DISEASE; IMAGE PROCESSING; MULTIVARIATE ANALYSIS; NEAR INFRARED; PLANT COMMUNITY; POPULATION DENSITY; SPECTRAL ANALYSIS; SPECTRAL REFLECTANCE;

TRITICUM AESTIVUM;

EID: 33947544369     PISSN: 13852256     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11119-006-9027-4     Document Type: Article

References (18)

1. Carter GA, Knapp AK (2001) Leaf optical properties in higher plants: linking spectral characteristics to stress and chlorophyll concentration. Am J Bot 88(4):677-684
2. Deering DW (1989) Field measurements of bidirectional reflectance. In: Asrar G (ed) Theory and applications of optical remote sensing. John Wiley & Sons, New York, pp 14-65
3. Hamid Muhammed H (2001) Feature vector based analysis: a unified concept for multivariate image analysis. Proceedings of IMVIP 2001 (Irish Machine Vision & Image Processing Conference, Maynooth, Ireland), pp 219-226
4. Hamid Muhammed H, Ammenberg P, Bengtsson E (2001) Using feature-vector based analysis, based on principal component analysis and independent component analysis, for analyzing hyperspectral images. Proceedings of ICIAP 2001 (11th International Conference on Image Analysis and Processing, Palermo, Italy), pp 309-315
5. Hamid Muhammed H, Larsolle A (2003) Feature vector based analysis of hyperspectral crop reflectance data for discrimination and quantification of fungal disease severity in wheat. Biosyst Eng 86:125-134
6. Hamid Muhammed H (2004) Characterizing and estimating fungal disease severity in wheat. In: Proceedings of Swedish society for automated image analysis symposium-SSBA (2004). Uppsala University, Sweden, 194-198
7. Hamid Muhammed H (2005) Hyperspectral crop reflectance data for characterising and estimating fungal disease severity in wheat. Biosyst Eng 91:9-20
8. Knipling EB (1970) Physical and physiological basis for the reflectance of visible and near-infrared radiation from vegetation. Rem Sens Environ 1:155-159
9. Kobayashi T, Kanda E, Kitada K, Ishiguro K, Torigoe Y (2001) Detection of rice panicle blast with multispectral radiometer and the potential of using airborne multispectral scanners. Phytopathology 91:316-323
10. Korobov RM, Railyan VYa (1993) Canonical correlation relationships among spectral and phytometric variables for twenty winter wheat fields. Rem Sens Environ 43:1-10
11. Kumar L, Schmidt KS, Dury S, Skidmore AK (2001) Review of hyperspectral remote sensing and vegetation science. In: Van der Meer FD, De Jong SM (eds) Imaging spectrometry: basic principles and prospective applications. Kluwer Academic Press, Dordrecht, The Netherlands, pp 111-155
12. Larsolle A (2003) A method for instantaneous measurement of reflectance spectra in open fields using diode array spectrometers. Biosyst Eng 86(1):1-8
13. Lelong CCD, Pinet PC, Poilve H (1998) Hyperspectral imaging and stress mapping in agriculture: a case study on wheat in Beauce (France). Rem Sens Environ 66:179-181
14. Malthus TJ, Madeira AC (1993) High resolution spectroradiometry: spectral reflectance of field bean leaves infected by Botrytis fabae. Rem Sens Environ 45:107-116
15. Nilsson HE (1985a) Remote sensing of oil seed rape infected by Sclerotinia stem rot and Verticillium wilt. Växtskyddsrapporter - jordbruk, 33, Uppsala, Sweden
16. Nilsson HE (1985b) Remote sensing of 2-row barley infected by net blotch disease. Växtskyddsrapporter - jordbruk, 34. Uppsala, Sweden
17. Nilsson HE (1985c) Remote sensing of 6-row barley infected by barley stripe disease. Växtskyddsrapporter - jordbruk, 36. Uppsala, Sweden
18. Steven MD, Malthus TJ, Demetriades-Shah TH, Danson FM, Clark JA. (1990) High resolution spectral indices for crop stress. In: Steven MD, Clark JA (eds) Applications of remote sensing in agriculture. Butterworth, London, UK, pp 209-227