Because of the high logistical and financial costs of direct measurements of riverine suspended sediment, remote sensing is increasingly used to supplement the direct‐observation record. The accuracy of this method is poorly constrained, and its potential as a tool for understanding river sediment transport is thus limited. We introduce and apply global‐scale methods for estimating depth‐integrated suspended‐sediment concentrations (SSCs) using Landsat 5 and 7 satellite imagery calibrated with 134,697 in situ SSC measurements. We account for river‐to‐river variability in the relationship between water optical properties and SSC by (a) categorizing rivers using unsupervised K‐means clustering and/or (b) correcting calibration estimates for individual rivers using local in situ measurements of SSC, suspended‐sediment grain size, and percent organic carbon (POC). In the absence of site‐specific in situ SSC measurements, clustering rivers reduces the average relative error of SSC estimates from 97% to 73%. We show that as few as five site‐specific in situ measurements combined with our algorithm further reduces average relative error to 49% and average relative at‐a‐station bias in SSC to 7%. Little additional improvement in accuracy or bias is gained by including measurements of percent sand or POC of the suspended sediment. Since only modest additional accuracy is gained after ~5–10 paired in situ SSC measurements and satellite observations, sampling campaigns should prioritize limited sampling at diverse locations rather than intensive sampling at a limited number of sites. In addition, we publish standalone calibrations for 151 rivers made solely with in situ SSC measurements local to those sites.

中文翻译：

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致力于提高遥感方法定量泥沙的准确性：对泥沙监测的意义

由于直接测量河流悬浮沉积物的物流和财务成本很高，因此越来越多地使用遥感来补充直接观测记录。该方法的准确性受到严格限制，因此其作为了解河流沉积物运输工具的潜力受到限制。我们引入并应用全球尺度的方法，使用Landsat 5和7卫星图像并用134,697原位SSC测量值进行校准，以估算深度综合悬浮物浓度（SSC）。通过（a）使用无监督K均值聚类对河流进行分类和/或（b）使用SSC的本地原位测量来校正个别河流的标定估计值，我们考虑了河流光学特性与SSC之间的关系中的河流之间的差异性，悬浮沉积物粒度 和有机碳百分比（POC）。在没有特定地点的原位SSC测量的情况下，集束河流将SSC估计值的平均相对误差从97％降低到73％。我们显示，与我们的算法相结合，仅进行了五次特定于现场的现场测量，即可进一步将SSC中的平均相对误差降低到49％，并将平均相对站点偏差降低到7％。通过包括测量悬浮泥沙或POC的百分比，几乎没有其他准确性或偏差的改善。由于在约5-10次成对的SSC原位测量和卫星观测之后只能获得适度的附加精度，因此采样活动应优先考虑在不同位置进行有限采样，而不是在有限数量的站点进行密集采样。此外，