Abstract

Currently, water monitoring programs are mainly based on in situ measurements; however, this approach is time-consuming, expensive, and may not reflect the status of the whole water body. The availability of Multispectral Imager (MSI) and Ocean and Land Colour Instrument (OLCI) free data with high spectral, spatial, and temporal resolution has increased the potential of adding remote sensing techniques into monitoring programs, leading to improvement of the quality of monitoring water. This study introduced an optical water type guided approach for boreal regions inland and coastal waters to estimate optical water quality parameters, such as the concentration of chlorophyll-a (Chl-a) and total suspended matter (TSM), the absorption coefficient of coloured dissolved organic matter at a wavelength of 442 nm (aCDOM(442)), and the Secchi disk depth, from hyperspectral, OLCI, and MSI reflectance data. This study was based on data from 51 Estonian and Finnish lakes and from the Baltic Sea coastal area, which altogether were used in 415 in situ measurement stations and covered a wide range of optical water quality parameters (Chl-a: 0.5–215.2 mg·m−3; TSM: 0.6–46.0 mg·L−1; aCDOM(442): 0.4–43.7 m−1; and Secchi disk depth: 0.2–12.2 m). For retrieving optical water quality parameters from reflectance spectra, we tested 132 empirical algorithms. The study results describe the best algorithm for each optical water type for each spectral range and for each optical water quality parameter. The correlation was high, from 0.87 up to 0.93, between the in situ measured optical water quality parameters and the parameters predicted by the optical water type guided approach.

Highlights

  • Remote sensing offers effective ways to observe spatial and/or temporal variations in water quality, which is vital for the comprehensive assessment and management of water bodies [1]

  • Water monitoring programs are mainly based on in situ measurements; considering that water bodies are dynamic in nature, this method may not reflect the status of the whole water body

  • Water monitoring programs are mainly based on in situ measurements; considering that water bodies are dynamic in nature, this method may not reflect the status of the entire water body

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Summary

Introduction

Remote sensing offers effective ways to observe spatial and/or temporal variations in water quality, which is vital for the comprehensive assessment and management of water bodies [1]. Remote sensing of inland and coastal waters can be challenging as they are independently influenced by different optically significant constituents (OSC)-coloured dissolved organic matter (CDOM), phytoplankton, and total suspended matter (TSM). All of these OSCs shape the spectral characteristics that are measured by the remote sensor. Remote sensing algorithms for the retrieval of Chl-a are based on the ratios of reflectance, such as the blue-green ratio [9], which are empirically related to the Chl-a concentration This is not valid for optically complex waters, where CDOM and TSM affect the optical properties of water. Several studies have suggested the use of various combinations of near-infrared (NIR) and red band combinations instead [10,11,12]

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