DocumentCode :
2140513
Title :
Spectral analysis of tomato late blight infections for remote sensing of tomato disease stress in California
Author :
Zhang, Minghua ; Qin, Zhihao
Author_Institution :
Dept. of Land, Air & Water Resources, California Univ., Davis, CA
Volume :
6
fYear :
2004
fDate :
20-24 Sept. 2004
Firstpage :
4091
Abstract :
California growers produce more than 86% of tomatoes in the United States. Late blight is one of the diseases threatening tomato crop productivity due to the aggressive nature of the disease. Monitoring crop growth and disease infections can be economically viable and ecologically sound. This study explores spectral analysis to identify the spectral relationships of the disease infections on tomatoes. Preliminary results indicated that there is a strong relationship between disease infection stages and the spectra reflectance at specific wavelength intervals. These spectral intervals include wavelength intervals of 600-690, 750-930, 950-1030, 1040-1130, 1450-1850, and 2000-2400. The relationship of the disease and spectral reflectance was developed using field spectra data and validated using hyperspectral image data with known disease infection locations and stages. On the basis of spectral analysis, 6 healthy indices has been proposed in the study for approach development and 3 of them have great potential to be applied in image analysis to identify the infected plants using hyperspectral remote sensing images. The results indicated that the DI 1, DI3, and DI4 are effective in identifying diseased plants; and when DI1 is above 13, the canopy contained healthy plants, when DI1 is between 2 and 13, they may contain the diseased plants with various infection stages. Specifically, the plants can be identified as infected at stage 3 when DI1 is around 6 and stage 4 when DI1 is ~5.2. The developed relationship can further be used in mapping the disease for monitoring crop growth and precision disease management
Keywords :
agriculture; crops; diseases; geophysical techniques; remote sensing; spectral analysis; California; United States; crop growth monitoring; disease infection locations; disease infections; disease mapping; field spectra data; hyperspectral image data; hyperspectral remote sensing images; image analysis; precision disease management; spectra reflectance; spectral analysis; spectral relationships; tomato crop productivity; tomato disease stress; tomato late blight infections; Crops; Diseases; Hyperspectral imaging; Hyperspectral sensors; Productivity; Reflectivity; Remote monitoring; Remote sensing; Spectral analysis; Stress;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004 IEEE International
Conference_Location :
Anchorage, AK
Print_ISBN :
0-7803-8742-2
Type :
conf
DOI :
10.1109/IGARSS.2004.1370031
Filename :
1370031
Link To Document :
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