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Nondestructive estimation of canopy chlorophyll content using Hyperion and Landsat/TM images

机译:使用Hyperion和Landsat / TM图像对冠层叶绿素含量进行无损估计

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摘要

Remote sensing offers a nondestructive tool for the quick and precise estimation of canopy chlorophyll content that serves as an important indicator of the plant ecosystem. In this study, the canopy chlorophyll content of 26 samples in 2007 and 40 samples in 2008 of maize were nondestructively estimated by a set of vegetation indices (VIs; Normalized Difference Vegetation Index, NDVI; Green Chlorophyll Index, CI_(green); modified soil adjust vegetation index, MSAVI; and Enhanced Vegetation Index, EVI) derived from the hyperspectral Hyperion and Thematic Mapper (TM) images. The PROSPECT model was used for sensitivity analysis among the indices and results indicated that CI_(green) had a large linear correlation with chlorophyll content ranging from 100-1000 mg m~(-2) . EVI showed a moderate ability in avoiding saturation and reached a saturation of chlorophyll content above 600 mg m~(-2). Both of the other two indices, MSAVI and NDVI, showed a clear saturation at chlorophyll content of 400 mg m , which demonstrated they may be inappropriate for chlorophyll interpretation at high values. A validation study was also conducted with satellite observations (Hyperion and TM) and in-situ measurements of chlorophyll content in maize. Results indicated that canopy chlorophyll content can be remotely evaluated by VIs with r~2 ranging from the lowest of 0.73 for NDVI to the highest of 0.86 for CI_(green). EVI had a greater precision (r~2=0.81) than MASVI (r~2=0.75) in canopy chlorophyll content estimation. The results agreed well with the sensitivity study and will be helpful in developing future models for canopy chlorophyll evaluation.
机译:遥感提供了一种快速,精确地估算冠层叶绿素含量的非破坏性工具,可作为植物生态系统的重要指标。在这项研究中,通过一组植被指数(VI;归一化植被指数,NDVI;绿色叶绿素指数,CI_(绿色);改良土壤)对玉米中2007年的26个样品和2008年的40个样品的冠层叶绿素含量进行了无损估计。调整从高光谱Hyperion和主题映射器(TM)图像得出的植被指数MSAVI和增强植被指数EVI)。用PROSPECT模型对各项指标进行敏感性分析,结果表明,CI_(绿色)与叶绿素含量在100-1000 mg m〜(-2)之间具有较大的线性相关性。 EVI表现出适度的避免饱和能力,并在600 mg m〜(-2)以上达到叶绿素含量饱和。另外两个指标MSAVI和NDVI在400 mg m的叶绿素含量下均显示出明显的饱和度,这表明它们可能不适用于高值的叶绿素解释。还通过卫星观测(Hyperion和TM)以及玉米中叶绿素含量的现场测量进行了验证研究。结果表明,可以通过VI远程评估冠层的叶绿素含量,r〜2范围从NDVI的最低0.73到CI_(绿色)的最高0.86。在冠层叶绿素含量估算中,EVI具有比MASVI(r〜2 = 0.75)更高的精度(r〜2 = 0.81)。结果与敏感性研究吻合得很好,将有助于开发将来的冠层叶绿素评估模型。

著录项

  • 来源
    《International journal of remote sensing》 |2010年第8期|P.2159-2167|共9页
  • 作者单位

    The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing, China Graduate University of Chinese Academy of Science, Beijing, China;

    rnThe State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing, China;

    rnThe State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing, China;

    rnThe State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing, China Graduate University of Chinese Academy of Science, Beijing, China;

    rnThe State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing, 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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