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首页> 外文期刊>International journal of remote sensing >Sensitivity of vegetation indices to substrate brightness in hyper-arid environment: the Makhtesh Ramon Crater (Israel) case study
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Sensitivity of vegetation indices to substrate brightness in hyper-arid environment: the Makhtesh Ramon Crater (Israel) case study

机译:Sensitivity of vegetation indices to substrate brightness in hyper-arid environment: the Makhtesh Ramon Crater (Israel) case study

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摘要

The influence of soil background on most vegetation indices (VIs) derived from remotely sensed imagery is a well known phenomenon, and has generated interest in the development of indices that would be less sensitive to this influence. Several such indices have been developed thus far. This paper focuses on testing and comparing the sensitivity of seven intensively used, Landsat Thematic Mapper (TM) derived, VIs (NDVI, SAVI, MSAVI, PVL WDVI, SAVI(2). and TSAVI) to bare Surface variation with almost no vegetation signal. The study was conducted on a terrain composed of a high variety of bare surface materials of which basalt and gypsum are two extremely dark and bright substrates respectively. It was found that SAVI and MSAVI respond to bare surface material very similarly. Such close similarity was also found between PVI and WDVI, and between SAVI(2) and TSAVI. NDVI tends to be overestimated on dark surfaces, while SAVI, PVI and TSAVI show more sensitivity to bright surfaces. Comparison between Delta (VI) (the difference between pairs of VIs) and the brightness of the different surface materials showed a high correlation in each case, which underlines the Fact that the response of different VIs to bare surface variation is mainly related to the surface brightness. References: 41

著录项

  • 来源
    《International journal of remote sensing》 |2001年第17期|3503-3520|共18页
  • 作者

    Schmidt H.; Karnieli A.;

  • 作者单位

    Ben Gurion Univ Negev, Jacob Blaustein Inst Desert Res, Remote Sensing Lab, Sede Boker Campus, IL-84990 Sede Boqer, Israel.;

  • 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 英语
  • 中图分类 遥感技术;
  • 关键词

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