A Hybrid Chlorophyll A Estimation Method for Oligotrophic and Mesotrophic Reservoirs Based on Optical Water Classification

Low- and medium-resolution satellites have been a relatively mature platform for inland eutrophic water classification chlorophyll concentration (Chl-a) retrieval algorithms. However, oligotrophic mesotrophic waters in small- medium-sized reservoirs, problems of low satellite resolution, insufficient sampling, higher uncertainty accuracy exist. In this paper, hybrid Chl-a estimation method based on spectral characteristics (i.e., remote sensing reflectance (Rrs)) was developed using high-resolution Sentinel-2 (A B) data. First, 99 samples quasi-synchronous data were collected from four reservoirs central China, the usability Rrs verified by accurate atmospheric correction. Second, new optical constructed different to classify into clear water, phytoplankton-dominated dominated phytoplankton suspended matter together thresholds Rrs490/Rrs560 Rrs665/Rrs560. The proposed has compared other methods, band-ratio algorithm is simpler more effective sensors without NIR bands. Third, given sensitivity empirical variability ease development implementation, nonlinear least squares fitted one-dimensional function established selection best-fitting indices types (OWTs) with validation results showed that two-band had highest squared correlation coefficient, root mean difference, absolute percentage error, bias 0.85, 2.93, 32.42%, −0.75 mg/m³, respectively, residual values further validated applicability reliability model. Finally, performance algorithms evaluated obtain images mapping reservoirs. conclusion, study improves combining model, which an important contribution solving problem resolution high potential be applied optically similar lakes spectrally sensors.