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A modified vegetation backscattering model for leaf area index retrieval from SAR time series

机译:基于SAR时间序列的叶面积指数修正植被反向散射模型。

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摘要

In this study, a semi-empirical modified vegetation backscattering model was developed to retrieve leaf area index (LAI) based on multi-temporal Radarsat-2 data and ground observations collected in China. This model combined the contribution of the vegetation and bare soil at the pixel level by adding vegetation coverage and the influence of bare soil on the total backscatter coefficients. Then, a lookup table algorithm was applied to calculate the value of vegetation water content and retrieve the LAI based on the linear relationship between the vegetation water content and LAI. The results indicated that the modified model was effective in evaluating and reproducing the total backscatter coefficients. Meanwhile, the LAI retrieval was well conducted with coefficient of determination (R-2) and root mean square error (RMSE) of 89% and 0.19 m(2) m(-2), respectively. Additionally, this method offers insight into the required application accuracy of LAI retrieval in the agricultural regions.
机译:在这项研究中,基于多时相Radarsat-2数据和在中国收集的地面观测数据,开发了一种半经验的改良植被反向散射模型来检索叶面积指数(LAI)。该模型通过增加植被覆盖率和裸露土壤对总反向散射系数的影响,在像素水平上结合了植被和裸露土壤的贡献。然后,应用查找表算法计算植被含水量的值,并根据植被含水量与LAI之间的线性关系检索LAI。结果表明,改进后的模型可以有效地评估和再现总的后向散射系数。同时,LAI检索的确定系数(R-2)和均方根误差(RMSE)分别为89%和0.19 m(2)m(-2),可以很好地进行检索。此外,该方法还可以深入了解农业地区LAI检索所需的应用精度。

著录项

  • 来源
    《International journal of remote sensing》 |2016年第24期|5884-5901|共18页
  • 作者单位

    Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China|Beijing Normal Univ, Key Lab Environm Change & Nat Disaster, Beijing, Peoples R China;

    Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China|Beijing Normal Univ, Key Lab Environm Change & Nat Disaster, Beijing, Peoples R China;

    China Univ Min & Technol, Coll Geosci & Surveying Engn, Beijing, Peoples R China;

    Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China|Beijing Normal Univ, Key Lab Environm Change & Nat Disaster, Beijing, Peoples R China;

    Henan Inst Engn, Inst Civil Engn, Zhengzhou, 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
  • 中图分类
  • 关键词

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