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首页> 外文期刊>Soil Science Society of America Journal >Sensitivity of Ground-Based Remote Sensing Estimates of Wheat Chlorophyll Content to Variation in Soil Reflectance
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Sensitivity of Ground-Based Remote Sensing Estimates of Wheat Chlorophyll Content to Variation in Soil Reflectance

机译：小麦叶绿素含量的地面遥感估算对土壤反射率变化的敏感性

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摘要

Spectral indices (SI) derived from crop reflectance data are sensitive to chlorophyll a and b content (Chl). However, the SI-Chl relationship might be confounded by variation in leaf area index (LAI) and soil background reflectance, especially in semiarid environments where water determines crop growth. This study evaluated the sensitivity of SI to variation in soil reflectance and how this may affect overall SI performance for ground-based sensing of Chl in dryland wheat (Triticum aestivum L.). Selected SI were computed from spectra simulated by the PROSPECT-SAIL radiative-transfer model for 5 LAI values, 7 Chl values, and 121 dry soil surface reflectance spectra. These spectra represented soils across major wheat growing areas in the United States. Soil properties and reflectance varied widely among the soils indicated by the high SI variation for LAI values < 1.5. Overall, soil background variation contributed less to the observed SI variability (<6%) than LAI (<97%). Combined indices [i.e., Normalized Difference Red Edge Index (NDRE)/Normalized Difference Vegetation Index (NDVI) and Modified Chlorophyll Absorption Ratio Index (MCARI)/Second Modified Triangular Vegetation Index (MTVI)] were least affected by soil background variation than single indices (i.e., NDVI). Results showed that ground sensing of Chl may be improved by means of combined indices that are resistant to soil background and LAI. Empirical measurements verified that the modeling results were a reliable representation of the influence of Chl, LAI, and soil on canopy reflectance. Further research is needed to evaluate the effect of soil moisture, surface roughness, residue, growth stage, and shadow on SI.
机译：从作物反射率数据得出的光谱指数（SI）对叶绿素a和b含量（Chl）敏感。但是，SI-Chl关系可能会因叶面积指数（LAI）和土壤背景反射率的变化而混淆，尤其是在半干旱环境中，水决定了作物的生长。这项研究评估了SI对土壤反射率变化的敏感性，以及这可能如何影响旱地小麦（Triticum aestivum L.）地面Chl感测的整体SI性能。从PROSPECT-SAIL辐射传递模型模拟的光谱中计算出选定的SI，以获得5个LAI值，7个Chl值和121个干土表面反射光谱。这些光谱代表了美国主要小麦产区的土壤。在LAI值<1.5的情况下，高SI差异表明土壤之间的土壤特性和反射率差异很大。总体而言，土壤背景变化对观测到的SI变异性的贡献（<6％）少于LAI（<97％）。组合指数[即，归一化差异红边指数（NDRE）/归一化差异植被指数（NDVI）和改良叶绿素吸收比指数（MCARI）/第二改良三角植被指数（MTVI）]受土壤背景变化的影响比单一指数最小（即NDVI）。结果表明，可以通过结合土壤背景和LAI的综合指标来改善Chl的地面感测。经验测量结果证明，建模结果是Chl，LAI和土壤对冠层反射率影响的可靠表示。需要进一步的研究来评估土壤水分，表面粗糙度，残留物，生长阶段和阴影对SI的影响。

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