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Estimating the suspended sediment concentration from TM/ Landsat-5 images for the Araguaia River - Brazil

机译:根据TM / Landsat-5图像估算阿拉瓜河的悬浮泥沙浓度-巴西

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摘要

In this study, 68 images from TM/Landsat-5 sensor were used to estimate Suspended Sediment Concentration (SSC) along of the Araguaia River, Brazil. These were combined with in-situ SSC, hydrosedimentometric station (categorical variable), and remote sensing reflectance. Top-of-Atmosphere (ToA) and surface reflectance data were evaluated. Multiple regression models with ToA reflectance using VNIR bands, band ratios, SWIR band 5 as input and station as categorical variable were more accurate with adjusted coefficient of determination (adjusted R-2) = 0.87 and normalized root mean square error (NRMSE) = 10.09% compared to the models with surface reflectance with adjusted R-2 = 0.60 and NRMSE = 15.43%. Results confirm the potential for estimation of SSC from TM/Landsat-5 historical series data between 1984 and 2012, for which in-situ database is rare. Based on this empirical model, future studies may provide better analysis of spatiotemporal variations of sediment transport along the Araguaia River with the SSC temporal series reconstitution.
机译:在这项研究中,来自TM / Landsat-5传感器的68张图像被用于估算巴西阿拉瓜河沿岸的悬浮泥沙浓度(SSC)。这些与原位SSC,水沉降测量站(分类变量)和遥感反射率结合在一起。评估了大气顶(ToA)和表面反射率数据。使用调整后的确定系数(调整后的R-2)= 0.87和归一化均方根误差(NRMSE)= 10.09,使用VNIR波段,波段比,SWIR波段5作为输入并将站点作为分类变量的具有ToA反射率的多元回归模型更为准确。与调整了R-2 = 0.60和NRMSE = 15.43%的表面反射率的模型相比,%。结果证实了从1984年到2012年之间通过TM / Landsat-5历史序列数据估算SSC的潜力,而原位数据库很少。基于这种经验模型,未来的研究可能会提供更好的分析,通过南南合作的时间序列重建,沿着阿拉瓜河的泥沙输送时空变化。

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  • 来源
    《Remote sensing letters》 |2020年第3期|47-56|共10页
  • 作者

  • 作者单位

    Fed Inst Goias Dept Geomat Goiania Go Brazil;

    Univ Estadual Maringa Dept Geog GEMA Maringa PR Brazil;

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  • 正文语种 eng
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