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Estimating leaf area index in spring wheat using alternative remote sensing approaches.

机译:使用替代遥感方法估算春小麦的叶面积指数。

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摘要

The reflectance based vegetation indices commonly used to infer leaf area index (LAI) are affected by external factors such as soil background, and view and illumination angles. Simulation of a modified SUITS directional reflectance model, MODSUITS, showed that there are some combinations of near infrared and red reflectance that correlate with LAI while minimizing the effects of these factors. We proposed the MSAVI3 (Modified Soil Adjusted Vegetation Index) that is suited in minimizing soil brightness effect particularly for soils with soil line slope greater than unity. This index decreases the residual soil effect caused by the multiple scattering between the soil background and the plant at intermediate LAI values. The MODSUITS model predicts that soil brightness affects less canopy transmittance than reflectance. Hence in determining LAI, transmittance based indices should be less dependent on soil brightness.; We assumed that the transmission coefficient is linearly related to the logarithm of LAI. Therefore, the extinction coefficient for diffuse visible radiation varied between 0.70 and 0.75 for the 42 genotypes. Similarly, from the ratio of near infrared to red transmittance, the difference in spectral extinction coefficient under total incidence oscillated between 0.40 and 0.52. The consistency in the extinction coefficients among the 42 genotypes and across geographical locations suggest that LAI of spring wheat can only be inferred from the diffuse transmission coefficient. Moreover, we found that the normalized transmittance vegetation index (NTVI), which is conceptually similar to the common normalized difference vegetation index (NDVI), is linearly related to the LAI up to a value of 6.; Leaf area index was also assessed from the analysis of digitized infrared color films. While the difference vegetation index (DVI) is related to growth or LAI, the low spectral sensitivity of the CIR film, particularly in the red band, limits its ability to resolve differences among the 42 spring wheat genotypes. The DVI integrated from emergence up to the onset of senescence showed slightly positive and moderately negative relationship with final grain yield at Pullman and Mayview, respectively.
机译:通常用于推断叶面积指数(LAI)的基于反射率的植被指数受外部因素的影响,例如土壤背景,视角和照明角度。修改后的SUITS定向反射模型MODSUITS的仿真表明,存在一些与LAI相关的近红外和红色反射率组合,同时将这些因素的影响降至最低。我们提出了MSAVI3(改良的土壤调整植被指数),它特别适合于土壤线坡度大于1的土壤,以最大程度地降低土壤的亮度影响。该指数降低了在中等LAI值下土壤背景与植物之间多重散射所引起的残留土壤效应。 MODSUITS模型预测,土壤亮度对冠层透射率的影响小于反射率。因此,在确定LAI时,基于透射率的指标应较少依赖于土壤亮度。我们假设传输系数与LAI的对数线性相关。因此,对于42种基因型,可见光漫射的消光系数在0.70和0.75之间变化。类似地,从近红外与红色透射率的比率来看,总入射下的光谱消光系数差异在0.40至0.52之间波动。 42个基因型之间以及不同地理位置的消光系数的一致性表明,只能从弥散传播系数推断春小麦的LAI。此外,我们发现归一化透光率植被指数(NTVI)在概念上与常见归一化差异植被指数(NDVI)相似,与LAI线性相关,最高值为6。还通过对数字化红外彩色胶片的分析来评估叶面积指数。虽然植被指数差异(DVI)与生长或LAI有关,但CIR薄膜的光谱灵敏度低,特别是在红波段,限制了其解决42种春小麦基因型差异的能力。从出苗到衰老开始的DVI积分分别与Pullman和Mayview的最终籽粒产量呈正相关和中等负相关。

著录项

  • 作者

    Ouattara, Adama.;

  • 作者单位

    Washington State University.;

  • 授予单位 Washington State University.;
  • 学科 Agriculture Agronomy.; Remote Sensing.
  • 学位 Ph.D.
  • 年度 1997
  • 页码 141 p.
  • 总页数 141
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 农学(农艺学);遥感技术;
  • 关键词

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