کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10249942 | 158951 | 2005 | 15 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Identification of red and NIR spectral regions and vegetative indices for discrimination of cotton nitrogen stress and growth stage
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Identification of red and NIR spectral regions and vegetative indices for discrimination of cotton nitrogen stress and growth stage Identification of red and NIR spectral regions and vegetative indices for discrimination of cotton nitrogen stress and growth stage](/preview/png/10249942.png)
چکیده انگلیسی
Studies have demonstrated the value of spectral vegetation indices (VIs) based on red and near-infrared (NIR) spectral reflectance in agriculture. The objective of this research was to analyze the effects of central wavelengths and bandwidths of red and NIR bands on VIs, and to evaluate the potential of red-NIR VIs in discriminating cotton canopies by nitrogen stress and growth stage. A completely randomized experiment was conducted in a cotton (Gossypium hirsutum L. cv. Sumian 3) field treated with four nitrogen application rates: 0%, 50%, 100% and 200% of the recommended rate. Hyperspectral reflectance was measured at 2.3 m above the cotton canopy on July 15, August 14 and October 1 using a FieldSpec® FR spectroradiometer. Using one-way analysis of variance (ANOVA) for 150 Ã 150 = 22,500 combinations of wavelengths and bandwidths in the normalized difference vegetation index (λ2 â λ1)/(λ1 + λ2), results suggested that the proper central wavelengths of λ1 and λ2 were at 680-730 nm (not 640-660 nm, the central wavelengths of the red channels of most multi-spectral sensors on the current generation satellites) and 750-850 nm, respectively. However, the effect of bandwidth on VIs was complicated. A single VI was not enough for nitrogen stress and growth stage detection. A single VI, in the 96 VIs used in this paper, was able to correctly classify 30-45% of the samples by nitrogen rate and growth stage. Using the 96 VIs as independent variables, a canonical discriminant analysis resulted in an accuracy of 62.4% with a six-VI model by the stepwise procedure.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers and Electronics in Agriculture - Volume 48, Issue 2, August 2005, Pages 155-169
Journal: Computers and Electronics in Agriculture - Volume 48, Issue 2, August 2005, Pages 155-169
نویسندگان
D.H. Zhao, J.L. Li, J.G. Qi,