Abstract
Abstract. Retrieving total suspended solids (TSS) concentration accurately is essential for sustainable management of estuaries and coasts, which plays a key role in the interaction between hydrosphere, pedosphere and atmosphere. Although many TSS retrieval models have been published, the general inversion method that is applicable to different field conditions is still under research. In order to obtain a TSS remote sensing model that is suitable for estimating TSS concentrations with wide range in estuaries and coasts by Landsat imagery, after reviewing a number of Landsat-based TSS retrieval models and improving a comparatively better one among them, this study developed a quadratic model using the ratio of logarithmic transformation of red band and near-infrared band and logarithmic transformation of TSS concentration (QRLTSS) based on 119 in situ samples collected in 2006–2013 from five regions of China. It was found 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) sensors 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 addition, a threshold method of red-band reflectance (OLI: 0.032, ETM+ and TM: 0.031) was proposed to solve the two-valued issue of the QRLTSS model and to retrieve TSS concentration from Landsat imagery. After a 6S model-based atmospheric correction of Landsat OLI and 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 estuaries showed large variation ranging from 0.295 to 370.4 mg L−1. Meanwhile we found that TSS concentrations retrieved from Landsat imagery showed good validation accuracies with the synchronous water samples (TSS: 7–160 mg L−1, RMSE: 11.06 mg L−1, N = 22). The further validation from EO-1 Hyperion imagery also showed good performance (in situ synchronous measurement of TSS: 106–220.7 mg L−1, RMSE: 26.66 mg L−1, N = 13) of the QRLTSS model for the area of high TSS concentrations in the Lingding Bay of the Pearl River estuary. Evidently, the QRLTSS model is potentially applied to simulate high-dynamic TSS concentrations of other estuaries and coasts by Landsat imagery, improving the understanding of the spatial and temporal variation of TSS concentrations on regional and global scales. Furthermore, the QRLTSS model can be optimized to establish a regional or unified TSS retrieval model of estuaries and coasts in the world for different satellite sensors with medium- and 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, LISS, CBERS, ASTER, ALOS, RapidEye, Kanopus-V, and GF.
Highlights
The amount of total suspended solids (TSS) is a critical factor of the ecological environment of water bodies, which directly and deeply affects their optical properties through absorbing and scattering of the sunlight (Chen et al, 2015b; Pozdnyakov et al, 2005; Wang et al, 2016; Wu et al, 2013), leading to impacts on the primary production of the water areas (May et al, 2003)
Compared to other remote sensing data, the Land Observation Satellite (Landsat) series of imagery has an advantage in spatiotemporal dynamics analysis of TSS concentrations (Wu et al, 2013) due to the additional good quality, high spatial resolution and inheritance, especially long-term historical data since 1972
For the QRLTSS model based on an OLI sensor, we found that the values of OLI red-band weighted reflectance of all validation data are lower than 0.032 when TSS concentrations are less than 36.1 mg L−1 (Fig. 5a, blue dots) apart from one exceptional datum (Fig. 5a, black dot)
Summary
The amount of total suspended solids (TSS) is a critical factor of the ecological environment of water bodies, which directly and deeply affects their optical properties through absorbing and scattering of the sunlight (Chen et al, 2015b; Pozdnyakov et al, 2005; Wang et al, 2016; Wu et al, 2013), leading to impacts on the primary production of the water areas (May et al, 2003). Many methods can be used to estimate TSS concentrations of water bodies, including hydrologicalsite monitoring, in situ investigation, physical models, numerical simulation, remote sensing and so on (Chen et al, 2015a). Compared to other remote sensing data, the Landsat series of imagery has an advantage in spatiotemporal dynamics analysis of TSS concentrations (Wu et al, 2013) due to the additional good quality, high spatial resolution and inheritance, especially long-term historical data since 1972
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