The optical properties of river and floodplain waters in the Amazon River Basin: Implications for satellite‐based measurements of suspended particulate matter

Abstract

Satellite images can now be used to assess river sediment discharge, and systematic studies over rivers and lakes are required to support such applications and document the variability of inland water optical properties at the watershed scale. The optical properties of the Amazon Basin waters were analyzed from in situ measurements of the remote sensing reflectance (R rs ) at 279 stations and downwelling diffuse attenuation coefficients (K d ) at 133 stations. Measurements of the apparent optical properties, suspended particulate matter (SPM) contents, and characteristics and colored dissolved organic matter (CDOM) absorption spectra were performed during 16 cruises along the main Amazonian Rivers draining the Andes and for some tributaries. Surface-suspended sediment granulometry and mineralogy showed a stable distribution at the catchment scale, even over large distances and between tributaries. The particle number-size distribution was best described using a segmented distribution with a slope of 2.2 for the fine range (1-15 μm), and the CDOM absorption coefficient at 440 nm varied from 1.8 to 7.9 m À1 . Overall, both R rs and K d were strongly correlated with SPM, although strong CDOM absorption limited the use of the blue spectrum. Reflectance saturation from blue to red was observed at approximately 100 g m À3 , whereas the near-infrared (NIR) wavelength enabled the monitoring of the full SPM range (5-620 g m À3 ). In contrast, K d showed no saturation for SPM from green to NIR, and a linear model was calculated. The use of the reflectance ratio was investigated and shown to improve the suspended sediment concentration retrieval performance.

Analysis of Suspended Particulate Matter and Its Drivers in Sahelian Ponds and Lakes by Remote Sensing (Landsat and MODIS): Gourma Region, Mali

“…In-situ turbidity and SPM measurements were used to evaluate different indexes proposed in the literature to derive these parameters from the visible and infrared bands [25,28]. These indexes were applied to the MODIS series (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016) and Landsat 7 & 8 series (2013Landsat 7 & 8 series ( -2016.…”

“…However, satellite data has proved useful to track SPM and turbidity variability in inland water in different tropical areas. Martinez et al [24,25], for instance, used MODIS images to monitor rivers in Latin America. Feng et al [26] also used MODIS data to study SPM dynamics in the Poyang Lake in China.…”

Suspended Sediment Variability at the Solimões and Negro Confluence between May 2013 and February 2014

“…This observation is valid to MODIS' reflectance ( Figure 3A,C). In this case, others studies [14,15,17,22,26] suggest using the infrared band, SSC exceeding 100 mg·L −1 , in the confluence area, would be for the period from January to February (Figure 3E,G). Estimates of SSC from MODIS images were made using the equation generated from the correlation of SSC values and reflectance measured by both spectroradiometer and MODIS.…”

Assessment of Chlorophyll-a Remote Sensing Algorithms in a Productive Tropical Estuarine-Lagoon System

“…Regarding the evaluated models for classified waters, the inversion algorithms applied to homogeneous groups generally did not improve the chlorophyll-a retrieval in comparison with the band models using the non-classified dataset; this may be associated with the following: (a) the derivation of models from a reduced number of water samples in each class; (b) the classification method chosen (e.g., unsupervised classification clustering, fuzzy logic classification and reflectance shape characteristics calculation approach), which may control the number and optical characteristics of each class [38,54,55]; and (c) a higher uniformity of both optical characteristics and concentration values of the water constituents in each class, which may result in a lower performance of the models, mainly for classes with higher concentrations of suspended matter and lower concentrations of chlorophyll-a. However, the pre-classification of the reflectance spectra dataset into homogeneous groups has shown to be satisfactory to validate the band models using a different handheld dataset without repositioning of optimal wavelength values for each model [38,48].…”

“…Each R rs (λ) spectrum was previously normalized by its integral, calculated over the entire spectrum [54], in order to enhance the spectral shape of the R rs (λ) spectra in the classification. This classification may support the use of multiple retrieval algorithms for each lagoon, homogeneous regions or a global retrieval algorithm for a whole system [55].…”