Remote Sensing of Chlorophyll‐A in Case II Waters: A Novel Approach With Improved Accuracy Over Widely Implemented Turbid Water Indices
2018
Menon, Harilal B. | Adhikari, Arjun
A new semianalytical algorithm was formulated to retrieve chlorophyll‐a (CHL) in optically complex waters using in situ data set of coastal waters of eastern Arabian Sea. The algorithm was derived using CHL index of the form, x = (Rᵣₛ(λ₁)⁻¹−Rᵣₛ(λ₂)⁻¹) × Rᵣₛ(λ₃). The first wavelength (λ₁) represents the secondary peak of CHL, while the second wavelength (λ₂) and third wavelength (λ₃) were delineated using a radiative transfer model and partial derivative analysis of hyperspectral remote sensing reflectance, respectively. Further iteration of three wavelengths between 600 and 700 nm resulted in a two‐wavelength index, x = (Rᵣₛ(λ₁)⁻¹−Rᵣₛ(λ₂)⁻¹) × Rᵣₛ(λ₂). This was further regressed with CHL data initially used for three wavelength index. The final form of algorithm, Goa University Case II (GUC2), cMCHL=113.112x³−58.408x²+8.669x − 0.0384, was validated with in situ CHL ranging between 0.11 and 25.56 μg/L, resulted in a strong correlation r² = 0.99, RMSE = 0.30, and bias = 0.03. A comparison with NIR‐Red two‐band, three‐band, four‐band, synthetic chlorophyll index, and normalized difference chlorophyll index pointed to the nonsuitability of turbid water indices in different water types of the study area. For the first time, a CHL algorithm has been tested successfully in water types outside the region of its formulation. A pixel‐to‐pixel validation of GUC2‐derived MERIS CHL with NASA bio‐Optical Marine Algorithm Dataset and Satellite Coastal and Oceanography Research data set resulted in correlation, bias, and RMSE of 0.90, −0.0013, and 1.2499, respectively. Furthermore, GUC2 was successfully tested in Chesapeake Bay for accurate retrieval of CHL from stations with varying turbidity levels.
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