Regional algorithms for remote-sensing estimates of total suspended matter in the Beaufort Sea

• Published in: International journal of remote sensing Vol. 34; no. 19; pp. 6562 - 6576
• Main Authors: Tang, Shilin, Larouche, Pierre, Niemi, Andrea, Michel, Christine
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 2013
• Subjects: Algorithms; Animal, plant and microbial ecology; Applied geophysics; Arctic region; Beaufort Sea; Biological and medical sciences; Correlation; Earth sciences; Earth, ocean, space; ecosystems; Exact sciences and technology; Freshwater; Fundamental and applied biological sciences. Psychology; General aspects. Techniques; image analysis; Imaging spectrometers; Internal geophysics; Marine geology; Neural networks; Reflectance; Reflectivity; Regional; Remote sensing; river water; Shelves; summer; suspended sediment; Teledetection and vegetation maps; Northwest Territories; Canada; Western Canada; Mackenzie District Northwest Territories; Arctic region; Mackenzie River; Arctic Ocean; polar regions; Beaufort Sea; Canada, Northwest Terr., Mackenzie R; PNW, Beaufort Sea; PN, Arctic; Biological properties; algorithms; continental shelf; Variable; Spectral band; Estimation; Space remote sensing; streams; chemical properties; concentration; Inlet flow; North America; in situ; Suspended particle; suspended materials; optical properties; ecosystems; River water; seasonal variations; sediments; Reflectance
• ISSN: 1366-5901; 0143-1161; 1366-5901
• DOI: 10.1080/01431161.2013.804222

The large and variable riverine inflow to Arctic continental shelves strongly influences their chemical, biological, and optical properties. The Beaufort Sea receives the largest amount of suspended sediments amongst all Arctic shelves, with sediment-laden Mackenzie river waters strongly influencing bio-optical properties on the shelf. Here, we developed two regional algorithms for the estimation of total suspended matter (TSM) concentration using Medium Resolution Imaging Spectrometer (MERIS) spectral bands, based on in situ optical and suspended particulate data collected in the summer during the Canadian Arctic Shelf Exchange Study (CASES) in 2004 and during the Arctic Coastal Ecosystem Study (ACES) in 2010. The band ratio (where Rᵣₛ is remote-sensing reflectance) Rᵣₛ,₅₆₀/Rᵣₛ,₄₉₀ was best correlated with low TSM concentrations (less than 3.0 g m⁻³), while higher TSM concentrations were well correlated to Rᵣₛ,₆₈₁/Rᵣₛ,₅₆₀. An empirical piecewise algorithm is thus proposed with the switch between the ratios being triggered by Rᵣₛ,₆₈₁/Rᵣₛ,₅₆₀ at a threshold value of 0.6. The second algorithm made use of support vector machines (SVMs) as a nonlinear transfer function between TSM concentrations and remote-sensing reflectance ratios Rᵣₛ,₆₈₁/Rᵣₛ,₅₆₀, Rᵣₛ,₆₆₅/Rᵣₛ,₅₆₀, and Rᵣₛ,₅₆₀/Rᵣₛ,₄₉₀. Results show that both algorithms perform better (31% and 25%, respectively) than other published TSM algorithms including the MERIS Case 2 water processor (C2R) neural network algorithm in the study area.