首页> 外文期刊>International journal of remote sensing >Retrieval of forest chlorophyll content using canopy structure parameters derived from multi-angle data: the measurement concept of combining nadir hyperspectral and off-nadir multispectral data
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Retrieval of forest chlorophyll content using canopy structure parameters derived from multi-angle data: the measurement concept of combining nadir hyperspectral and off-nadir multispectral data

机译:利用多角度数据的冠层结构参数反演森林叶绿素含量:天底高光谱和天底外多光谱数据相结合的测量概念

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摘要

The retrieval of total chlorophyll content (chl_(a + b)) per unit leaf area and unit ground area was investigated for a boreal forest near Sudbury in northern Ontario, Canada. The retrieval was based on inversions of the 5-Scale and PROSPECT models using canopy structure parameters, leaf area index (LAI) and clumping index, generated from off-nadir (multi-angle) multispectral data. Findings support the validity of combining nadir hyperspectral and multi-angle multispectral remote sensing in simultaneous retrieval of structural and biochemical vegetation parameters. Chlorophyll retrievals are improved once the improved structural parameters are obtained from multispectral data at two optimal off-nadir angles, the hotspot and darkspot. The estimated leaf chlorophyll contents agree well with the field measured values (R~2 = 0.89 and root mean square error (RMSE) = 8.1 μg cm~(-2)). When the clumping index is excluded from the inversion, the coefficient of determination, R~2, decreases to 0.53 and the RMSE, increases to 13.4 μg cm~(-2).
机译:在加拿大安大略省北部萨德伯里附近的北方森林中,调查了每单位叶面积和单位地面面积的总叶绿素含量(chl_(a + b))的取回。该检索基于使用离地(多角度)多光谱数据生成的冠层结构参数,叶面积指数(LAI)和聚集指数对5-Scale和PROSPECT模型的反演。研究结果支持将天底高光谱和多角度多光谱遥感相结合在同时检索结构和生化植被参数方面的有效性。一旦在两个最佳偏离天底角(热点和暗点)处从多光谱数据获得了改善的结构参数,叶绿素的检索就会得到改善。估计的叶绿素含量与田间测量值非常吻合(R〜2 = 0.89,均方根误差(RMSE)= 8.1μgcm〜(-2))。当从反演中排除聚集指数时,测定系数R〜2降低至0.53,RMSE升高至13.4μgcm〜(-2)。

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  • 来源
    《International journal of remote sensing》 |2011年第20期|p.5621-5644|共24页
  • 作者单位

    Department of Geography, University of Toronto, 100 St. George Street, Toronto, ON, M5S 3G3, Canada;

    Department of Geography, University of Toronto, 100 St. George Street, Toronto, ON, M5S 3G3, Canada;

    Ontario Ministry of Natural Resources, Ontario Forest Research Institute, 1235 Queen St. East, Sault Ste. Marie, ON, P6A 2E5, Canada;

  • 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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