Generation of robust 10-m Sentinel-2/3 synthetic aquatic reflectance bands over inland waters

IF 11.1 1区 地球科学 Q1 ENVIRONMENTAL SCIENCES Remote Sensing of Environment Pub Date : 2025-01-03 DOI:10.1016/j.rse.2024.114593
Rejane S. Paulino, Vitor S. Martins, Evlyn M.L.M. Novo, Claudio C.F. Barbosa, Daniel A. Maciel, Raianny L. do N. Wanderley, Carina I. Portela, Cassia B. Caballero, Thainara M.A. Lima
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Abstract

Inland waters comprise various aquatic systems, including rivers, lakes, lagoons, reservoirs, and others, and satellite data play a crucial role in providing holistic and dynamic observations of these complex ecosystems. However, available medium-spatial resolution satellite sensors, such as Sentinel-2 Multi-Spectral Instrument (MSI), are typically designed for land monitoring and lack suitable spectral bands and radiometric quality for water applications. This study developed a novel synthetic band generation method, called Sentinel-2/3 Synthetic Aquatic Reflectance Bands (S2/3Aqua), for computing eight 10-m synthetic spectral bands from multivariate regression analysis between Sentinel-2 MSI and Sentinel-3 OLCI image pair. Three multivariate regressor models, Multivariate Linear Regressor (MLR), Multivariate Quadratic Regressor (MQR), and Random Forest Regressor (RFR), were applied and assessed to replicate the Sentinel-3 spectral consistency on 10-m Sentinel-2 images. A cyanobacteria modeling was developed based on in-situ observations (n = 54), and we demonstrated, for the first time, the application of 10-m harmful algal bloom mapping over two eutrophic tropical urban reservoirs (Promissão and Billings, Brazil). Additionally, the generalization of S2/3Aqua was assessed by comparing its spectral signatures across different water optical types. Overall, the comparison between S2/3Aqua and Sentinel-3 bands achieved a mean absolute error of 6 % and a mean difference close to zero. We found that MLR exhibited a higher accuracy with in-situ observations (with a 28 % bias) and was more suitable than other tested models. S2/3Aqua also performed satisfactorily across all eight spectral bands, including at 620 and 681 nm, with a mean difference of less than 0.003 reflectance units. The cyanobacteria mapping showed a high level of agreement between S2/3Aqua and Sentinel-3 for low concentrations of Phycocyanin (less than 50 mg m−3), and S2/3Aqua effectively captured the spatial variability of narrower and smaller blooms. Finally, S2/3Aqua provides reliable synthetic spectral bands that can effectively be used in several aquatic system studies, including monitoring potentially harmful algal blooms.
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来源期刊
Remote Sensing of Environment
Remote Sensing of Environment 环境科学-成像科学与照相技术
CiteScore
25.10
自引率
8.90%
发文量
455
审稿时长
53 days
期刊介绍: Remote Sensing of Environment (RSE) serves the Earth observation community by disseminating results on the theory, science, applications, and technology that contribute to advancing the field of remote sensing. With a thoroughly interdisciplinary approach, RSE encompasses terrestrial, oceanic, and atmospheric sensing. The journal emphasizes biophysical and quantitative approaches to remote sensing at local to global scales, covering a diverse range of applications and techniques. RSE serves as a vital platform for the exchange of knowledge and advancements in the dynamic field of remote sensing.
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