Empirical models for estimating the suspended sediment concentration in Amazonian white water rivers using Landsat 5/TM |
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| Institution: | 1. State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai 200241, China;2. College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China;1. Institut de Recherche pour le Développement (IRD), Université de Toulouse, UPS (OMP), CNRS, UMR 5566 LEGOS, 14 av. Edouard Belin, 31400 Toulouse, France;2. Space Technology Institute (STI), Vietnam Academy of Science & Technology (VAST), 18 Hoang Quoc Viet, Cau Giay, Hanoi, Viet Nam;3. Laboratoire d''Océanologie et de Géosciences (LOG), Univ. du Littoral Cote d''Opale (ULCO), CNRS UMR 8187, 28 avenue Foch, BP 80, 62930 Wimereux, France;4. ACRI-ST, 260 Route du Pin Montard, 06904 Sophia-Antipolis, France;5. University of Science and Technology of Hanoi (USTH), 18 Hoang Quoc Viet, Cau Giay, Hanoi, Viet Nam;6. Institute of Oceanography, VAST, 1 Cau Da, Nha Trang, Viet Nam;1. Instituto de Astronomía y Física del Espacio (IAFE), CONICET/UBA, Argentina;2. Royal Belgian Institute for Natural Sciences (RBINS), Operational Directorate Natural Environment, Belgium;3. Laboratoire d''Océanographie de Villefranche (LOV), UMR 7093, CNRS/UPMC, France;4. Flemish Institute for Technological Research (VITO), Belgium;1. Spectral Lab, Department of Geography, University of Victoria, Victoria, BC, V8W 3R4, Canada;2. National Institute for Space Research (INPE), Remote Sensing Division, Av. dos Astronautas, 1758 - Jardim da Granja, São José dos Campos, SP-12227-010, Brazil;1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China;2. Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, 73 East Beijing Road, Nanjing 210008, China;3. School of Marine Sciences, Nanjing University of Information Science & Technology, Jiangsu, Nanjing 210044, China;4. State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, 73 East Beijing Road, Nanjing 210008, China |
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| Abstract: | Suspended sediment yield is a very important environmental indicator within Amazonian fluvial systems, especially for rivers dominated by inorganic particles, referred to as white water rivers. For vast portions of Amazonian rivers, suspended sediment concentration (SSC) is measured infrequently or not at all. However, remote sensing techniques have been used to estimate water quality parameters worldwide, from which data for suspended matter is the most successfully retrieved. This paper presents empirical models for SSC retrieval in Amazonian white water rivers using reflectance data derived from Landsat 5/TM. The models use multiple regression for both the entire dataset (global model, N = 504) and for five segmented datasets (regional models) defined by general geological features of drainage basins. The models use VNIR bands, band ratios, and the SWIR band 5 as input. For the global model, the adjusted R2 is 0.76, while the adjusted R2 values for regional models vary from 0.77 to 0.89, all significant (p-value < 0.0001). The regional models are subject to the leave-one-out cross validation technique, which presents robust results. The findings show that both the average error of estimation and the standard deviation increase as the SSC range increases. Regional models were more accurate when compared with the global model, suggesting changes in optical proprieties of water sampled at different sampling stations. Results confirm the potential for the estimation of SSC from Landsat/TM historical series data for the 1980s and 1990s, for which the in situ database is scarce. Such estimates supplement the SSC temporal series, providing a more comprehensive SSC temporal series which may show environmental dynamics yet unknown. |
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| Keywords: | Top of atmosphere reflectance Multiple regressions Geology of the Amazon Fluvial sediments Spectral bands Band ratios |
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