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Atmospheric correction issues for retrieving total suspended matter concentrations in inland waters using OLI/Landsat-8 image

机译:使用OLI / Landsat-8影像检索内陆水中总悬浮物浓度的大气校正问题

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摘要

The atmospheric effects that influence on the signal registered by remote sensors might be minimized in order to provide reliable spectral information. In aquatic systems, the application of atmospheric correction aims to minimize such effects and avoid the under or over-estimation of remote sensing reflectance (R_(rs)). Accurately R_(rs) provides better information about the state of aquatic system, it means, establishing the concentration of aquatic compounds more precisely. The aim of this study is to evaluate the outputs from several atmospheric correction methods (Dark Object Subtraction - DOS; Quick Atmospheric Correction - QUAC; Fast Line-of-sight Atmospheric Analysis of Hypercubes - FLAASH; Atmospheric Correction for OLI 'lite' - ACOLITE, and Provisional Landsat-8 Surface Reflectance Algorithm - L8SR) in order to investigate the suitability of R_(rs) for estimating total suspended matter concentrations (TSM) in the Barra Bonita Hydroelectrical Reservoir. To establish TSM concentrations via atmospherically corrected Operational Land Imager (OLI) scene, the TSM retrieval model was calibrated and validated with in situ data. Thereby, the achieved results from TSM retrieval model application demonstrated that L8SR is able to provide the most suitable R_(rs) values for green and red spectral bands, and consequently, the lowest TSM retrieval errors (Mean Absolute Percentage Error about 10% and 12%, respectively). Retrieved R_(rs) from near infrared band is still a challenge for all the tested algorithms.
机译:为了提供可靠的光谱信息,可以将影响遥感器记录的信号的大气影响降至最低。在水生系统中,大气校正的应用旨在最大程度地减少此类影响,并避免对遥感反射率(R_(rs))进行过低或过高的估计。准确地,R_(rs)提供了有关水生系统状态的更好信息,这意味着可以更精确地确定水生化合物的浓度。这项研究的目的是评估几种大气校正方法的输出(暗物扣除-DOS;快速大气校正-QUAC;超立方体的快速视线大气分析-FLAASH; OLI'lite'的大气校正-ACOLITE以及临时Landsat-8表面反射算法-L8SR),以研究R_(rs)用于估算巴拉博尼塔水电站总悬浮物浓度(TSM)的适用性。为了通过大气校正的操作陆地成像仪(OLI)场景确定TSM浓度,对TSM取回模型进行了校准和现场数据验证。因此,从TSM检索模型应用获得的结果表明,L8SR能够为绿色和红色光谱带提供最合适的R_(rs)值,因此,最低的TSM检索误差(平均绝对百分比误差约为10%和12 %, 分别)。对于所有测试算法而言,从近红外波段检索R_(rs)仍然是一个挑战。

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  • 来源
    《Advances in space research》 |2017年第9期|2335-2348|共14页
  • 作者单位

    Sao Paulo State University, Department of Cartography, Roberto Simonsen Street, 305, Presidente Prudente, Sao Paulo 19060-900, Brazil;

    Sao Paulo State University, Department of Cartography, Roberto Simonsen Street, 305, Presidente Prudente, Sao Paulo 19060-900, Brazil;

    Sao Paulo State University, Department of Cartography, Roberto Simonsen Street, 305, Presidente Prudente, Sao Paulo 19060-900, Brazil;

    Sao Paulo State University, Department of Cartography, Roberto Simonsen Street, 305, Presidente Prudente, Sao Paulo 19060-900, Brazil;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Atmospheric correction; Inland water; Water quality; Eutrophic environment;

    机译:大气校正;内陆水;水质;富营养化的环境;
  • 入库时间 2022-08-17 13:18:54

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