中文摘要：

成像高光谱的近地田间应用为农业定量遥感的发展提供了新的契机。如何发挥其图谱合一的数据优势，尤其在解析土壤、阴影等背景地物对作物养分反演模型的影响需要关注。该研究借助可见/近红外成像高光仪，在近地田间采集小麦群体的成像立方体，根据影像中光照裸土、阴影裸土、光照叶片和阴影叶片的反射光谱特征建立了归一化光谱分类指数，并应用该指数提取大豆影像中不同类型地物的光谱，分析了背景土壤剔除前后的大豆植被归一化光谱与叶绿素密度的决定系数变化情况。结果表明：土壤和阴影叶片光谱去除后，反演叶绿素密度的敏感波段由红-近红外区间（727 nm，922 nm）向蓝、绿，尤其是红波段（710 nm,711 nm）移动。对叶绿素密度敏感的波段区间表现为可见光增加,近红外减少，且红边波段决定系数最高。由此说明，基于归一化光谱指数的植被光谱提纯对定量遥感反演研究具有重要意义。

英文摘要：

Near-ground imaging spectroscopy applied in field provides new opportunity for development of quantitative remote sensing in agriculture. It deserves concern about how to exert its data advantage of integrating image and spectra into one, particularly in analyzing the influence of background targets, such as soil, shadow on crop nutrient inversion model. In this research, imaging cubes of wheat group in the field were collected by visible/near-infrared imaging spectrometer （VNIS）. A normalized spectral index was set up according to reflectance characteristics of illuminated soil, shadow soil, illuminated leaf and shadow leaf in the image. Furthermore, the index was used to extract spectra of different targets in soybean images and analyze the variation of determination coefficient R2 between normalized spectra of soybean group and chlorophyll density before and after removing background soil. The results showed that when spectra of soil and shadow leaf were removed, the sensitive bands of chlorophyll density shifted from red and near-infrared ranges （727 nm, 922 nm） to red ranges （710 nm, 711 nm）, meanwhile, the overall trend was that visible ranges increased, near-infrared regions decreased and red bands had the highest determination coefficient. Therefore, it can be concluded that spectral purification based on normalized spectral index has important significance for quantitative research in agricultural remote sensing.