Comparative analysis of four semi-analytical models for estimating chlorophyll-a concentration in case-2 waters using field hyperspectral reflectance. Issue 2 (17th January 2020) - Lu, Xiaoman; Situ, Chunyan; Ma, Weichun; Dai, Xiaoyan; He, Cheng; Li, Linna; Zhou, Liguo
ABSTRACT: Hyperspectral remote sensing can capture the complicated and variable characteristics of inland waters; thus, it is suited for the water quality assessment of Case-2 waters, and it has the potential to attain high estimation accuracy. In the present study, four improved models adapted from published approaches (three-band index, ΔΦ, BNDBI and TCARI) were investigated to estimate chlorophyll- a (chl- a ) for the case of Dianshan Lake, China. Calibration and validation were provided from in situ measured chl- a and field hyperspectral measurements. The improved three-band (ITB) model, ΔΦ model, and BNDBI model yielded satisfactory results and enabled the estimation of chl- a for inland Case-2 waters with coefficients of determination ( R 2 ) reaching 0.75, 0.76, and 0.86, respectively. In particular, the TCARI/OSAVI model presented the highest accuracy ( R 2  = 0.94) compared to the other models. All of the results provide strong evidence that the hyperspectral models presented in this paper are promising and applicable to estimate chl- a in eutrophic inland Case-2 waters.