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首页> 外文期刊>International journal of remote sensing >Retrieval of leaf water content from remotely sensed data using a vegetation index model constructed with shortwave infrared reflectances
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Retrieval of leaf water content from remotely sensed data using a vegetation index model constructed with shortwave infrared reflectances

机译：使用短波红外反射率构建的植被指数模型从遥感数据中检索叶片含水量

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摘要

The timely and accurate estimation of leaf water content (LWC) is of great practical significance for monitoring the state of vegetation growth and forecasting crop yield. As the spectral capabilities of terrestrial spectroscopy instruments and high-spatial-resolution satellite sensors steadily increase, people pay more and more attentions to the application potential for the spectral characteristics of the plant in shortwave infrared (SWIR) domain. The major purpose of this article was to investigate the relationship between leaf spectral reflectance and LWC in SWIR. A normalized vegetation index model constructed with SWIR reflectances centred at 1725 and 2200nm yielded a high overall performance compared to the previous normalized difference water index (NDWI). The Leaf Optical Properties Experiment 1993 data set was introduced to validate the LWC estimated with the proposed model. The results showed that the accuracy of LWC estimation from this index can reach 0.0046gcm(-2), which is better than that from traditional NDWI with root mean square error equalled to 0.0104gcm(-2). The effects of band width and random noise on the LWC estimation from these two indices were also analysed and the results showed that LWC retrieved from both indices were insensitive to band width choices and random noise variations.
机译：及时准确地估计叶片含水量（LWC）对于监测植被生长状况和预测作物产量具有重要的现实意义。随着陆地光谱仪器和高空间分辨率卫星传感器的光谱能力稳步提高，人们越来越关注植物在短波红外（SWIR）光谱特性中的应用潜力。本文的主要目的是研究SWIR中叶片光谱反射率与LWC之间的关系。与以前的归一化差异水指数（NDWI）相比，以1725和2200nm为中心的SWIR反射率构建的归一化植被指数模型具有较高的总体性能。引入了“叶片光学特性实验1993”数据集，以验证所提出模型估计的LWC。结果表明，根据该指标估算的LWC的精度可以达到0.0046gcm（-2），优于传统NDWI的均方根误差等于0.0104gcm（-2）。还分析了带宽和随机噪声对这两个指标对LWC估计的影响，结果表明，从两个指标中检索到的LWC对带宽选择和随机噪声变化均不敏感。

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  • 来源
    《International journal of remote sensing》 |2019年第6期|2313-2323|共11页
  • 作者

    Zhang Ziyang; Tang Bo-Hui; Li Zhao-Liang;

  • 作者单位

    Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China|Univ Chinese Acad Sci, Beijing, Peoples R China;

    Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China|Univ Chinese Acad Sci, Beijing, Peoples R China;

    Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China|Univ Chinese Acad Sci, Beijing, Peoples R China|Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, Key Lab Agr Remote Sensing, Minist Agr, Beijing, Peoples R China;

  • 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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