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)

• Record Type: Journal Article
• Authors: Lu, Xiaoman; Situ, Chunyan; Ma, Weichun; Dai, Xiaoyan; He, Cheng; Li, Linna; Zhou, Liguo
• Is Part Of: International journal of remote sensing. Volume 41:Issue 2(2020)
• Page Start: 584
• Page End: 594
• Publication Date: 2020-01-17
• Subjects: Remote sensing -- Periodicals; Télédétection -- Périodiques; 621.3678
• DOI: 10.1080/2150704X.2019.1646934
• Languages: English
• ISSNs: 0143-1161

Abstract

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.