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Retrieving total suspended solids (TSS) concentration accurately is essential\udfor sustainable management of estuaries and coasts,\udwhich plays a key role in the interaction between hydrosphere, pedosphere and atmosphere. Although many TSS retrieval models have been\udpublished, the general inversion method that is applicable to different field conditions is still under research. In order to obtain\uda TSS remote sensing model that is suitable for estimating TSS concentrations with wide range in estuaries and coasts by Landsat\udimagery, after reviewing a number of Landsat-based TSS retrieval models and improving a comparatively better one among them, this\udstudy developed a quadratic model using the ratio of logarithmic transformation of red band and near-infrared band and logarithmic\udtransformation of TSS concentration (QRLTSS) based on 119 in situ samples collected in 2006–2013 from five regions of China. It was\udfound that the QRLTSS model works well and shows a satisfactory performance. The QRLTSS model based on Landsat TM (Thematic Mapper), ETM+ (Enhanced Thematic Mapper Plus) and OLI (Operational Land Imager)\udsensors explained about 72 % of the TSS concentration variation (TSS: 4.3–577.2 mg L−1, N = 84, P value  < 0.001) and had an acceptable validation accuracy (TSS: 4.5–474 mg L−1, root mean squared error (RMSE)  ≤ 25 mg L−1, N = 35). In\udaddition, a threshold method of red-band reflectance (OLI: 0.032, ETM+ and TM: 0.031) was proposed to solve the two-valued issue of\udthe QRLTSS model and to retrieve TSS concentration from Landsat imagery. After a 6S model-based atmospheric correction of Landsat OLI\udand ETM+ imagery, the TSS concentrations of three regions (Moyangjiang River estuary, Pearl River estuary and Hanjiang River estuary) in Guangdong Province in China were mapped by the QRLTSS model. The results indicated that TSS concentrations in the three\udestuaries showed large variation ranging from 0.295 to 370.4 mg L−1. Meanwhile we found that TSS concentrations retrieved\udfrom Landsat imagery showed good validation accuracies with the synchronous water samples (TSS: 7–160 mg L−1, RMSE:\ud11.06 mg L−1, N = 22). The further validation from EO-1 Hyperion imagery also showed good performance (in situ\udsynchronous measurement of TSS: 106–220.7 mg L−1, RMSE: 26.66 mg L−1, N = 13) of the QRLTSS model for the\udarea of high TSS concentrations in the Lingding Bay of the Pearl River estuary. Evidently, the QRLTSS model is potentially applied to\udsimulate high-dynamic TSS concentrations of other estuaries and coasts by Landsat imagery, improving the understanding of the\udspatial and temporal variation of TSS concentrations on regional and global scales. Furthermore, the QRLTSS model can be optimized to\udestablish a regional or unified TSS retrieval model of estuaries and coasts in the world for different satellite sensors with medium-\udand high-resolution similar to Landsat TM, ETM+ and OLI sensors or with similar red bands and near-infrared bands, such as ALI, HJ-1 A and B,\udLISS, CBERS, ASTER, ALOS, RapidEye, Kanopus-V, and GF

A Landsat-based model for retrieving total suspended solids concentration of estuaries and coasts in China