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Effect of relative spectral response on multi-spectral measurements and NDVI from different remote sensing systems.

机译：相对光谱响应对来自不同遥感系统的多光谱测量和NDVI的影响。

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摘要

Spectrally derived metrics from remotely sensed data measurements have been developed to improve understanding of land cover and its dynamics. Today there are an increasing number of remote sensing systems with varying characteristics that provide a wide range of data that can be synthesized for Earth system science. A more detailed understanding is needed on how to correlate measurements between sensors. One factor that is often overlooked is the effect of a sensor's relative spectral response (RSR) on broadband spectral measurements.; This study examined the variability in spectral measurements due to RSR differences between different remote sensing systems and the implications of these variations on the accuracy and consistency of the normalized difference vegetation index (NDVI). A theoretical model study and a sensor simulation study of laboratory and remotely sensed hyper-spectral data of known land cover types was developed to provide insight into the effect on NDVI due to differences in RSR measurements of various land cover signatures.; This research has shown that the convolution of RSR, signature reflectance and solar irradiance in land cover measurements leads to complex interactions and generally small differences between sensor measurements. Error associated with cross-senor calibration of signature measurements and the method of band radiance conversion to reflectance also contributed to measurement discrepancies. The effect of measurement discrepancies between sensors on the accuracy and consistency of NDVI measurements of vegetation was found to be dependent on the increasing sensitivity of NDVI to decreasing band measurements. A concept of isolines of NDVI error was developed as a construct for understanding and predicting the effect of differences in band measurements between sensors on NDVI. NDVI difference of less than 0.05 can be expected for many sensor comparisons of vegetation, however, some cases will lead to higher differences. For vegetation signatures used in this study, maximum effect on NDVI from measurement differences was 0.063 with an average of 0.023. For sensors with well aligned RSRs such as Landsat 7 ETM+ and MODIS, NDVI differences in the range of 0.01 are possible.
机译：已经开发了从遥感数据测量中得出的光谱度量，以增进对土地覆盖及其动态的理解。如今，越来越多的具有不同特性的遥感系统提供了可以为地球系统科学合成的各种数据。需要对如何关联传感器之间的测量值有更详细的了解。通常被忽略的一个因素是传感器的相对光谱响应（RSR）对宽带光谱测量的影响。这项研究检查了由于不同遥感系统之间的RSR差异引起的光谱测量变化，以及这些变化对归一化差异植被指数（NDVI）的准确性和一致性的影响。进行了理论模型研究和传感器模拟研究，研究了已知土地覆盖类型的实验室数据和遥感高光谱数据，以洞察由于各种土地覆盖特征的RSR测量值的差异而对NDVI产生的影响。这项研究表明，在土地覆盖测量中，RSR，特征反射率和太阳辐照度的卷积会导致复杂的相互作用，并且通常导致传感器测量之间的差异很小。与特征测量的跨传感器校准相关的误差以及将波段辐射率转换为反射率的方法也导致了测量差异。发现传感器之间的测量差异对植被的NDVI测量的准确性和一致性的影响取决于NDVI对减小的波段测量的敏感性增加。开发了NDVI误差等值线的概念，作为了解和预测NDVI传感器之间的频段测量差异的影响的构造。对于植被的许多传感器比较，可以预期NDVI差异小于0.05，但是，某些情况下会导致更高的差异。对于本研究中使用的植被特征，测量差异对NDVI的最大影响为0.063，平均值为0.023。对于具有良好RSR对齐的传感器，例如Landsat 7 ETM +和MODIS，NDVI的差异可能在0.01的范围内。

著录项

  • 作者

    Fleming, David James.;

  • 作者单位

    University of Maryland, College Park.;

  • 授予单位 University of Maryland, College Park.;
  • 学科 Physical Geography.; Remote Sensing.
  • 学位 Ph.D.
  • 年度 2006
  • 页码 150 p.
  • 总页数 150
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自然地理学;遥感技术;
  • 关键词

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