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Multi-depth suspended sediment estimation using high-resolution remote-sensing UAV in Maumee River, Ohio

机译:使用高分辨率遥感无人机在俄亥俄州莫米河进行多深度悬浮泥沙估算

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摘要

Satellite remote-sensing has been widely used to map suspended sediment concentration (SSC) in waterbodies. Current development of the unmanned aerial vehicle (UAV) technology allows mapping of SSC at finer spatial resolution providing high flexibility in terms of cost and acquisition time. However, the technology is immature and transfer of empirical algorithms from existing remote-sensing technologies to UAV still has to be explored. This study uses the MicaSense Sequoia sensor with four bands (green, red, red edge, and near-infrared [NIR]) mounted on-board a fixed-wing UAV to map SSC within the Maumee River in Ohio, USA, at multiple depth intervals (15, 61, 91, and 182cm). The simple linear and stepwise regression models show the advantage of multiple bands and band ratios over single bands in mapping SSC. The findings show a limited performance of the Sequoia sensor when compared to field spectroradiometer measurements. In all cases but one, the adjusted coefficient of determination become constant at and below a depth of 0-91cm. While the spectroradiometer-related equations are sensitive to a wider spectral range (from green at the surface to NIR wavelength at 182cm depth), the UAV-related equations are insensitive to green spectrum and they include a narrower spectral range (from red to NIR) over all depth increments. Field spectroradiometer measurements exhibit a strong relationship with cumulative SSC at 182cm depth (0-182cm) suggesting that similar to 91cm may be an optimal depth for UAV under given conditions. The results show that UAVs can be a practical but somewhat limited tool to monitor SSC in small- to medium-sized rivers.
机译:卫星遥感已广泛用于绘制水体中的悬浮沉积物浓度(SSC)。无人机技术的最新发展允许以更精细的空间分辨率对SSC进行制图,从而在成本和获取时间方面提供了高度的灵活性。但是,该技术还不成熟,需要将经验算法从现有的遥感技术转移到无人机。这项研究使用安装在固定翼无人机上的具有四个频段(绿色,红色,红色边缘和近红外[NIR])的MicaSense红杉传感器在美国俄亥俄州的莫米河内绘制多个深度的SSC间隔(15、61、91和182厘米)。简单的线性和逐步回归模型显示出在映射SSC时多个频带和频带比率优于单个频带的优势。研究结果表明,与现场分光辐射计测量相比,红杉传感器的性能有限。在除一种情况以外的所有情况下,调整后的确定系数在0-91cm深度及以下均保持不变。虽然与光谱仪相关的方程对较宽的光谱范围(从表面的绿色到182cm深度的NIR波长)敏感,但与无人机相关的方程对绿色光谱不敏感,并且它们包括较窄的光谱范围(从红色到NIR)在所有深度增量上。现场光谱辐射仪的测量结果与182cm深度(0-182cm)处的累积SSC有很强的关系,这表明在给定条件下,与91cm相似可能是无人机的最佳深度。结果表明,无人机可以作为一种实用的工具,但在中小型河流中监测SSC时会受到一定限制。

著录项

  • 来源
    《International journal of remote sensing》 |2018年第16期|5472-5489|共18页
  • 作者单位

    Bowling Green State Univ, Dept Geol, 190 Overman Hall, Bowling Green, OH 43403 USA;

    Bowling Green State Univ, Dept Geol, 190 Overman Hall, Bowling Green, OH 43403 USA;

    Bowling Green State Univ, Dept Geol, 190 Overman Hall, Bowling Green, OH 43403 USA;

    Bowling Green State Univ, Dept Geol, 190 Overman Hall, Bowling Green, OH 43403 USA;

  • 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 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-18 04:03:56

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