...
首页> 外文期刊>International journal of remote sensing >An evaluation of the effect of the spectral response function of satellite sensors on the precision of the universal pattern decomposition method
【24h】

An evaluation of the effect of the spectral response function of satellite sensors on the precision of the universal pattern decomposition method

机译:卫星传感器光谱响应函数对通用模式分解方法精度影响的评估

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

In previous studies of the universal pattern decomposition method (UPDM), the band width has been used to calculate standard spectral pattern vectors, without consideration of the effect of spectral response functions (SRFs). This study revised the UPDM to further reduce sensor dependence, by taking into account the effect of SRFs. Both the UPDM and the revised UPDM (RUPDM) were applied to MODIS and ETM+ data acquired over the Three Gorges region of China. The reconstruction accuracy was significantly greater when the RUPDM was used, with a relative decrease in the mean x~2 of more than 14%. Using the new method, the dependence of the decomposition coefficients and vegetation index (VIUPD) on the sensor also decreased, with their linear regression factors approximately equal to one. These increases in accuracy indicate that the RUPDM further reduces sensor dependence and hence can outperform the UPDM in data retrieval.
机译:在先前对通用模式分解方法(UPDM)的研究中,带宽已用于计算标准频谱模式矢量,而没有考虑频谱响应函数(SRF)的影响。这项研究考虑到SRF的影响,对UPDM进行了修改,以进一步降低传感器的依赖性。 UPDM和修订后的UPDM(RUPDM)均适用于在中国三峡地区采集的MODIS和ETM +数据。使用RUPDM时,重建精度显着提高,平均x〜2的相对下降超过14%。使用新方法,分解系数和植被指数(VIUPD)对传感器的依赖性也降低了,它们的线性回归因子大约等于1。这些准确性的提高表明,RUPDM进一步降低了传感器依赖性,因此在数据检索中可以胜过UPDM。

著录项

  • 来源
    《International journal of remote sensing》 |2010年第8期|P.2083-2090|共8页
  • 作者单位

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

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

    rnCenter for Earth Observation and Digital Earth, Chinese Academy of Sciences, Beijing, China;

    rnState 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
  • 中图分类
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号