Regression Modeling Strategies
Regression Modeling Strategies
Remote Sensing and Image Interpretation
Remote Sensing and Image Interpretation
Computers and Electronics in Agriculture
Computers and Electronics in Agriculture
Computers and Electronics in Agriculture
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Novel and existing hyperspectral vegetation indices were evaluated in this study, with the aim of assessing their utility for accurate tracking of leaf spectral changes due to differences in biophysical indicators caused by apple scab. Novel indices were extracted from spectral profiles by means of narrow-waveband ratioing of all possible two-band combinations between 350 nm and 2500 nm at nanometer intervals (2 311 250 combinations) and all possible two-band derivative combinations. Narrow-waveband ratios consisting of wavelengths of approximately 1500 nm and 2250 nm, associated with water content, have proven to be the most appropriate for detecting apple scab at early developmental stages. Logistic regression c-values ranged from 0.80 to 0.88. At a more developed infection stage, vegetation indices such as R440/R690 and R695/R760 exhibited superior distinction between non-infected and infected leaves. Identified derivative indices were located in similar regions. It therefore was concluded that the most appropriate indices at early stages of infection are ratios of wavelengths situated at the water band slopes. The choice of appropriate indices and their discriminatory performances, however, depended on the phenological stage of the leaves. Hence, an undisturbed 20-day growth profile was examined to assess the effect of physiological changes on spectral variations at consecutive growth stages of leaves. Results suggested that an accurate distinction could be made between different leaf developmental stages using the 570 nm, 1460 nm, 1940 nm and 2400 nm wavelengths, and the red-edge inflection point. These results are useful to crop managers interested in an early warning system to aid proactive system management and steering.