Long-term information of phytoplankton bloom is critical for assessing the processes driving blooms in lakes. A three-decade survey of the phytoplankton blooms was completed for Erhai Lake from 1987 to 2016 with Landsat imagery. A modified three-band model using Landsat broad bands is developed by comparing reflectance data from Landsat imagery to two field datasets. The model is applied to the archived imagery to predict chlorophyll-a (Chl-a). Predicted ln(Chl-a) and observed ln(Chl-a) measurements are significantly correlated (R 2 = 0.70; RMSE = 0.13 µg/L). Bloom maps are generated by identifying Landsat pixels that have Chl-a concentrations larger than 20 µg/L as bloom area. Bloom extent and magnitude are estimated. Our study reveals that algal blooms first occurred in 1996 with a bloom area of 150 km 2 . Bloom occurred frequently from 2002 to 2016, with extreme blooms in 2003, 2013 and 2016. Algal blooms were mostly distributed in the northern and southern part of the lake. The proposed method uses one model for all Landsat images for Erhai Lake and can predict past blooms and extend the record to early years when field data is not available. The bloom extent and magnitude produced in this study can be used as the basis for the understanding of the processes that control the bloom outbreak.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.