Improved estimates of bio-optical parameters in optically complex water using hyperspectral remote sensing data

ABSTRACT

In this study, bio-optical parameters were derived from hyperspectral data of optically complex waters using spectrum matching technique (SMT). Models for inherent optical properties (IOPs) of the water column were tuned using in-situ dataset from the study area (i.e., Chilika lagoon). Constructed IOPs were used to simulate remote sensing reflectance ($R_{\mathrm{r}\mathrm{s}}$) spectra at 60 wavelengths (equally spaced between 400 and 700 nm) using radiative transfer solution provided by Hydrolight-Ecolight software (HE53). Results of the simulation were stored as a $R_{\mathrm{r}\mathrm{s}}$ – IOP look up table (LUT). To check the accuracy, in-situ measured $R_{\mathrm{r}\mathrm{s}}$ were compared with those from the LUT. Retrieved values of two bio-optical parameters i.e., chlorophyll-a concentration (Chl-a) and coloured dissolved organic matter (CDOM)+Detritus absorption coefficient at 440 nm ($a_{\mathrm{d}\mathrm{g}}(440)$) were compared with corresponding in-situ measurements to get good statistical match. Coefficient of determination ($R^2$) and root mean squared error (RMSE) were 0.80 and 2.66 mg m${ }^{-3}$ respectively for Chl-a, whereas 0.77 and 0.23 m${ }^{-1}$ respectively for $a_{\mathrm{d}\mathrm{g}}(440)$. These parameters were also retrieved using two commonly used semi-analytical inversion algorithms (SAA)- (a) Linear matrix inversion (LMI) and (b) Garver-Siegal Maritorena (GSM). Both the SAA showed poor performance. $R^2$ for Chl-a from GSM and LMI were 0.13 and 0.41, respectively, with RMSE of 6.85 mg m${ }^{-3}$ and 4.82 mg m${ }^{-3}$ respectively. For $a_{\mathrm{d}\mathrm{g}}(440)$, the value of $R^2$ from GSM and LMI were 0.87 and 0.71, respectively, but with a high RMSE of 0.91 m${ }^{-1}$ and 0.81 m${ }^{-1}$ respectively. SMT was applied to airborne hyperspectral AVIRIS-NG (Airborne Visible/Infrared Imaging Spectrometer Next Generation) dataset of Chilika lake to derive pixel-wise chlorophyll-a concentration and the magnitude of CDOM+Detritus absorption coefficient at 440 nm ($a_{\mathrm{d}\mathrm{g}}(440)$). Spatial variability of these parameters in its different domains (i.e. Northern-, Central- and Southern-region of the lake) have been addressed.

Acknowledgements

The authors are thankful to Chilika Development Authority (CDA) for providing necessary facilities & supporting data and CDA staffs including Mr. Bita Mohanty for the involvement in the field and laboratory works during the AVIRIS data collection campaign. Part of the research work was carried out using CDA wetland research and training centre (WRTC) laboratory facilities developed through World Bank funding (ICZMP, Odisha: Credit no. 4765-IN).

Data availability

Data that supports the findings of this study are not publicly available and can only be provided upon reasonable request through proper channel.

Disclosure statement

No potential conflict of interest was reported by the authors.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.