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Hyperspectral indices to diagnose leaf biotic stress of apple plants, considering leaf phenology

机译:考虑叶片物候特性的高光谱指数可诊断苹果植物的叶片生物胁迫

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摘要

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 e-values ranged from 0.80 to 0.88. At a more developed infection stage, vegetation indices such as R_(440)/R_(690) and R_(695)/R_(760) 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.
机译:在这项研究中,对新的和现有的高光谱植被指数进行了评估,目的是评估它们的效用,以准确跟踪由于苹果sc引起的生物物理指标差异而引起的叶片光谱变化。通过以纳米间隔(2 311 250组合)和所有可能的两波段导数组合对所有介于350 nm和2500 nm之间的可能的两波段组合(窄带比例)进行窄带比例分配,从光谱轮廓中提取新的指数。事实证明,由约1500 nm和2250 nm的波长组成的窄带比率与水分含量相关,是最适合早期发育阶段检测苹果黑星病的方法。 Logistic回归e值的范围从0.80到0.88。在更发达的感染阶段,诸如R_(440)/ R_(690)和R_(695)/ R_(760)的植被指数在未感染和感染叶片之间表现出更好的区别。识别出的衍生指数位于相似的区域。因此可以得出结论,感染初期最合适的指标是位于水带坡度处的波长比。然而,合适的指标的选择及其区分性能取决于叶片的物候阶段。因此,检查了一个不受干扰的20天生长曲线,以评估生理变化对叶片连续生长阶段光谱变化的影响。结果表明,使用570 nm,1460 nm,1940 nm和2400 nm波长以及红边拐点可以在不同叶片发育阶段之间进行准确区分。这些结果对于对预警系统感兴趣的作物管理者很有用,以帮助他们进行主动的系统管理和指导。

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  • 来源
    《International journal of remote sensing》 |2009年第8期|1887-1912|共26页
  • 作者单位

    M3-BIORES, Katholieke Universiteit Leuven, Celestijnenlaan 200 E, BE-3001 Leuven,Belgium;

    M3-BIORES, Katholieke Universiteit Leuven, Celestijnenlaan 200 E, BE-3001 Leuven,Belgium;

    M3-BIORES, Katholieke Universiteit Leuven, Celestijnenlaan 200 E, BE-3001 Leuven,Belgium;

    CSIR Natural Resources and the Environment, Ecosystems -Earth Observation, PO Box 395, Pretoria, 0001, South Africa;

    Crop Bio-engineering, Katholieke Universiteit Leuven, W. de Croylaan 42, BE-3001 Heverlee, Belgium;

    M3-BIORES, Katholieke Universiteit Leuven, Celestijnenlaan 200 E, BE-3001 Leuven,Belgium;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
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