Remote sensing estimation of chlorophyll-a concentration in Taihu Lake considering spatial and temporal variations.

The estimation of chlorophyll-a concentrations (Chla) in lakes using remote sensing is convenient, but its use remains challenging in large eutrophic water bodies due to the great spatial and temporal variations of its optical properties. Combining the sampling location and date information with Chla data, this study divided the lake water into three types, I, II and III, and then built an optimal Chla estimation model for each type based on 11 datasets collected from 2004 to 2012 in Taihu Lake, China. The resultant model expression is Chla = exp (ax + bx + c), where x is R701/R677, (1/R686-1/R695) × R710 and (R690/R550-R675/R700) / (R690/R550 + R675/R700).