李存军, 赵春江, 刘良云, 王纪华, 王人潮. 红外光谱指数反演大田冬小麦覆盖度及敏感性分析[J]. 农业工程学报, 2004, 20(5): 159-164.
    引用本文: 李存军, 赵春江, 刘良云, 王纪华, 王人潮. 红外光谱指数反演大田冬小麦覆盖度及敏感性分析[J]. 农业工程学报, 2004, 20(5): 159-164.
    Li Cunjun, Zhao Chunjiang, Liu Liangyun, Wang Jihua, Wang Renchao. Retrieval winter wheat ground cover by short-wave infrared spectral indices in field and sensitivity analysis[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2004, 20(5): 159-164.
    Citation: Li Cunjun, Zhao Chunjiang, Liu Liangyun, Wang Jihua, Wang Renchao. Retrieval winter wheat ground cover by short-wave infrared spectral indices in field and sensitivity analysis[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2004, 20(5): 159-164.

    红外光谱指数反演大田冬小麦覆盖度及敏感性分析

    Retrieval winter wheat ground cover by short-wave infrared spectral indices in field and sensitivity analysis

    • 摘要: 植被的覆盖度能反映植被对光的截获、指示植物的生物产量等。常用的红光/近红外构成的植被指数能指示作物覆盖度,但它们易受到不确定因素的影响,估测结果往往偏差较大。该文以冬小麦为例,研究了利用近红外和短波红外光谱指数估测覆盖度的可行性,并评价了这些指数对品种、肥水处理和叶色的敏感性。试验中对冬小麦用数码相机垂直成像获取照片,利用分类算法自动提取覆盖度。根据同步获取的冬小麦光谱特征,构造了56个红外比值和28个红外归一化光谱指数,并选取了8个基于红光近红外的植被指数,利用通用线性模型(GLM)评价它们对覆盖度的预测能力及敏感性分析。结果表明,短波红外光谱指数R1690/R1450,R1450/R1690及(R1450-R1690)/(R1450+R1690)等不易受品种,肥水管理及叶色的影响,能很好地预测大田冬小麦覆盖度。

       

      Abstract: The ground cover of vegetation indicated light interceptor of plant, and plant productivity. The red and near-infrared vegetation indices had been employed to predict the ground cover of crop, however these vegetation indices were affected by uncertainty factors such as leaf color, crop cultivar and others. This research focused on the feasibility of predicting ground cover by near infrared and mid-infrared spectral indices which were not sensitive to cultivar, fertilization treatment, irrigation treatment and leaf color. In field the digital photographs of wheat canopy were taken vertically 1.5 m aboveground and then spectra were measured by an ASD Fieldspec FR2500 spectrometer. The ground covers were automatically extracted by a novel image processing procedure based wheat and soil background features. The 8 diagnostic spectral bands in infrared and short-infrared region were selected to calculate 56 ratio indices and 28 normalized difference indices. Also 8 popular red and near-infrared vegetation indices were calculated. The general linear model(GLM) was applied to assess the relationship between ground coverage and spectral indices, and to evaluate whether they were sensitive to cultivar, fertilization treatment, irrigation treatment and leaf color. Results show that red and near infrared vegetation indices to predict ground cover were affected by at least one of the four factors mentioned above, however it is promising that some infrared indices, such as R1690/R1450, R1450/R1690, (R1450-R1690)/(R1450+R1690), predict ground cover of wheat well and they are not sensitive to cultivar, fertilization treatment, irrigation treatment and leaf color.

       

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