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Arabi, Behnaz ; Moradi, Masoud ; Zandler, Harald ; Samimi, Cyrus ; Verhoef, Wouter:
Developing a novel index for detection of optically shallow waters using multispectral satellite imagery and radiative transfer modelling.
In: International Journal of Remote Sensing.
Bd. 45
(2024)
Heft 14
.
- S. 4788-4819.
ISSN 0143-1161
DOI: https://doi.org/10.1080/01431161.2024.2368931
Abstract
Optical remote sensing of water quality has been problematic due to contamination of remote sensing observations by the sea-bottom effect over complex shallow or very clear waters. This has resulted in providing misleading information on the estimation of Water Constituent Concentrations (WCCs) retrieved from satellite images. In this research, we used Radiative Transfer (RT) Modelling to develop a simple and innovative index named the Sea-Bottom Effect Index (SEBEI) to readily determine water pixels contaminated by the sea-bottom effect, (hereafter named Optically Shallow Waters, (OSWs)) from remote sensing observations. To define the SEBEI, we initially assessed the influence of the sea-bottom on simulated water-leaving reflectance (Rrs) using RT Water-Sea-Bottom (WSB) modelling. This evaluation encompassed a range of water depths, seabed albedos, and WCCs (i.e. Chlorophyll-a (Chla) and Suspended Particulate Matter (SPM)). Next, we detected the most sensitive wavelengths (i.e. 750 nm, 810 nm, and 900 nm) to the seabed contribution on the simulated Rrs spectra at the water surface level and developed the SEBEI. We validated the accuracy of the proposed SEBEI over a time series of MEdium Resolution Imaging Spectrometer (MERIS) and Ocean and Land Colour Instrument (OLCI) images captured during low and high tidal phases over shallow waters of the Dutch Wadden Sea, the Netherlands. The results indicate that the SEBEI effectively distinguishes between OSWs and Optically Deep Waters (ODWs) using satellite images (with an R2 value of ≥ 0.97 and a Root Mean Square Error (RMSE) of ≤ 0.65). The SEBEI can serve as an intermediate solution for detecting OSWs in multispectral and hyperspectral satellite images worldwide. It eliminates the need for ancillary datasets like bathymetry maps and significantly enhances the reliability of WCC maps produced over complex shallow coastal waters.
Acknowledgements
We express our gratitude to the European Space Agency (ESA) for the provision of the OLCI and MERIS images used in this study. We extend our heartfelt appreciation to Professor Daphne van der Wal, from Department of Water Resources, the ITC Faculty Geo-Information Science and Earth Observation at the University of Twente, the Netherlands, and the Royal Netherlands Institute for Sea Research (NIOZ), for their invaluable assistance and unwavering support throughout the course of this research.