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Estimating the CDOM absorption coefficient in tropical inland waters using OLI/Landsat-8 images

机译:使用OLI / Landsat-8影像估算热带内陆水域的CDOM吸收系数

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Coloured dissolved organic matter (CDOM) is the most abundant dissolved organic matter (DOM) in many natural waters and can affect the water quality, such as the light penetration and the thermal properties of water system. So the objective of this letter was to estimate the CDOM absorption coefficient at 440 nm, a(CDOM)(440), in Barra Bonita Reservoir (Sao Paulo State, Brazil) using operational land imager (OLI)/Landsat-8 images. For this two field campaigns were conducted in May and October 2014. During the field campaigns remote sensing reflectance (R-rs) were measured using a TriOS hyperspectral radiometer. Water samples were collected and analysed to obtain the a(CDOM)(440). To predict the a(CDOM)(440) from R-rs at two key wavelengths (650 and 480 nm) were regressed against laboratory-derived a(CDOM)(440) values. The validation using in situ data of a(CDOM)(440) algorithm indicated a goodness of fit, R-2 = 0.70, with a root mean square error (RMSE) of 10.65%. The developed algorithm was applied to the OLI/Lansat-8 images. Distribution maps were created with OLI/Landsat-8 images based on the adjusted algorithm.
机译:有色溶解有机物(CDOM)是许多天然水中最丰富的溶解有机物(DOM),会影响水质,例如水的透光率和水系统的热性能。因此,这封信的目的是使用可操作的陆面成像仪(OLI)/ Landsat-8图像估算Barra Bonita水库(巴西圣保罗州)在440 nm处的CDOM吸收系数a(CDOM)(440)。为此,于2014年5月和2014年10月进行了两次野战。在野战期间,使用TriOS高光谱辐射计测量了遥感反射率(R-rs)。收集水样并进行分析以获得a(CDOM)(440)。为了从R-rs预测a(CDOM)(440)在两个关键波长(650和480 nm)相对于实验室衍生的a(CDOM)(440)值进行回归。使用(CDOM)(440)算法的原位数据进行验证表明拟合优度R-2 = 0.70,均方根误差(RMSE)为10.65%。将开发的算法应用于OLI / Lansat-8图像。根据调整后的算法,使用OLI / Landsat-8图像创建分布图。

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  • 来源
    《Remote sensing letters》 |2016年第9期|661-670|共10页
  • 作者单位

    Sao Paulo State Univ Unesp, Dept Cartog, Presidente Prudente, SP, Brazil;

    Sao Paulo State Univ Unesp, Dept Cartog, Presidente Prudente, SP, Brazil;

    Sao Paulo State Univ Unesp, Dept Cartog, Presidente Prudente, SP, Brazil;

    Sao Paulo State Univ Unesp, Dept Cartog, Presidente Prudente, SP, Brazil;

    Sao Paulo State Univ Unesp, Dept Cartog, Presidente Prudente, SP, Brazil;

    Sao Paulo State Univ Unesp, Dept Cartog, Presidente Prudente, SP, Brazil;

    Sao Paulo State Univ Unesp, Dept Math & Comp Sci, Presidente Prudente, SP, Brazil;

    Sao Paulo State Univ Unesp, Dept Cartog, Presidente Prudente, SP, Brazil;

    Sao Paulo State Univ Unesp, Dept Cartog, Presidente Prudente, SP, Brazil;

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