title: Estimation of suspended sediment concentrations using Terra MODIS: an example from the Lower Yangtze River, China.
abstract: Traditional measurements of suspended sediment concentrations (SSC) through in-situ sampling in rivers are expensive and time-consuming to perform. Thus, these methods cannot provide continuous SSC records. Although remote sensing has been used for SSC estimation, little research has been undertaken on inland rivers, especially for highly turbid rivers like the Yangtze. Previous studies have proposed Landsat TM/ETM+ Band 4 as a spectral SSC indicator for the Yangtze, but its limitation on temporal resolution is insufficient for the study of dynamic changes of sediment. This paper presents a method of estimating SSC of the Yangtze at Jiujiang using time-series satellite data of high temporal resolution Terra MODIS. It was found that differences in water reflectance between Band 2 and Band 5 could provide relatively accurate SSC estimation even when in-situ atmospheric conditions were unknown. After cross-validation, mean absolute relative error (ARE) and relative root mean square error (RRMSE) were relatively low (i.e., 25.5% and 36.5%, respectively). This empirical relationship was successfully applied to the estimation of SSC at Datong in the Lower Yangtze River, although the SSC values were generally underestimated. This study suggests that Terra MODIS could be used to estimate SSC in large turbid rivers, although some influencing factors require further study to improve the accuracy of SSC estimation.
authors.affiliation: Department of Geography, National University of Singapore, 10 Kent Ridge Crescent 119260, Singapore.
authors.forename: J-J
authors.initials: JJ
authors.lastname: Wang
authors.forename: X X
authors.initials: XX
authors.lastname: Lu
mesh_terms: D002681:China; D004784:Environmental Monitoring / Q000379:methods*; D019015:Geologic Sediments / Q000737:chemistry*; D008962:Models, Theoretical; D045483:Rivers / Q000737:chemistry*; D013057:Spectrum Analysis / Q000379:methods