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Use of Field Spectroscopy for Exploring the Impact of Atmospheric Effects on Landsat 5 TM/7 ETM+ Satellite Images Intended for Hydrological Purposes in Cyprus

机译:利用现场光谱技术研究大气效应对塞浦路斯水文目的Landsat 5 TM / 7 ETM +卫星影像的影响

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摘要

The spectroradiometric retrieved reflectance of a local crop, namely, beans (Phaseolus vulgaris), is directly compared to the reflectance of Landsat 5TM and 7ETM+ atmospherically corrected and uncorrected satellite images. Also, vegetation indices from the same satellite images-atmospherically corrected and uncorrected-are compared with the corresponding vegetation indices produced from field measurements using a spectroradiometer. Vegetation Indices are vital in the estimation of crop evapotransiration under standard conditions (ET_c) because they are used in stochastic or empirical models for describing crop canopy parameters such as the Leaf Area Index (LAI) or crop height. ET. is finally determined using the FAO Penman-Monteith method adapted to satellite data, and is used to examine the impact of atmospheric effects. Regarding the reflectance comparison, the main problem was observed in Band 4 of Landsat 5TM and 7ETM+, where the difference, for uncorrected images, was more than 20% and statistically significant. Results regarding ET. show that omission or ineffective atmospheric corrections in Landsat 5TM/7ETM+ satellite images always results in a water deficit when estimating crop water demand. Diminished estimated crop water requirements can result in a reduction in output or, if critical, crop failure. The paper seeks to illustrate the importance of removing atmospheric effects from satellite images designated for hydrological purposes.
机译:将本地作物即豆类(菜豆)的分光光度法得出的反射率直接与Landsat 5TM和7ETM +大气校正和未校正卫星图像的反射率进行比较。同样,将来自同一卫星图像的植被指数(大气校正和未校正)与使用分光辐射计从现场测量中产生的相应植被指数进行比较。植被指数在估计标准条件下的作物蒸散量方面非常重要,因为它们用于描述作物冠层参数(例如叶面积指数(LAI)或作物高度)的随机或经验模型中。 ET。最后使用适合于卫星数据的FAO Penman-Monteith方法确定该值,并将其用于检查大气影响。关于反射率比较,主要问题是在Landsat 5TM和7ETM +的波段4中观察到的,对于未经校正的图像,其差异超过20%,并且具有统计学意义。关于ET的结果。表明在估算农作物需水量时,Landsat 5TM / 7ETM +卫星图像中的遗漏或无效的大气校正总是导致缺水。估计的作物需水量减少会导致产量减少,或者如果严重的话还会导致作物歉收。本文试图说明从指定用于水文目的的卫星图像中消除大气影响的重要性。

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  • 来源
    《GIScience & remote sensing》 |2011年第2期|p.280-298|共19页
  • 作者单位

    Department of Civil Engineering and Geomatics, Remote Sensing Laboratory, Cyprus University of Technology, 50329, 3603 Lemesos, Cyprus and Cyprus Agricultural Research Institute, Athalassa 1516, Nicosia, Cyprus;

    Department of Civil Engineering and Geomatics, Remote Sensing Laboratory, Cyprus University of Technology, 50329, 3603 Lemesos, Cyprus;

    Frederick University of Cyprus, Nicosia, Cyprus;

    Cyprus Meteorological Service, Nicosia, Cyprus;

    National Agricultural Research Foundation, Larissa, Greece;

    Cyprus Agricultural Research Institute, Athalassa 1516, Nicosia, Cyprus;

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