@misc{10481/90589,
year = {2023},
url = {https://hdl.handle.net/10481/90589},
abstract = {The fundamental role of water for life and the threats to water bodies around the world have highlighted the
need for their conservation. Remote sensing is a tool that allows us to monitor water bodies in a rapid, systematic,
accurate and economical way, being complementary to traditional field sampling methods. The main
aim of this review is to synthesise the use of the Sentinel-2 satellite for chlorophyll-a monitoring, an indicator of
the trophic state of aquatic ecosystems, and assess the role of each parameter on chlorophyll-a retrieval. To this
end, indices, models, atmospheric corrections and field sampling details used so far in chlorophyll-a monitoring
of aquatic ecosystems using Sentinel-2 imagery were analysed. Sentinel-2 was chosen because it has suitable
features for monitoring water bodies (spatial, temporal and spectral resolution), despite not having been specifically
designed for that purpose. The indices aphy(B4)/a*phy(B4), B7(1/B4-1/B5), B5-(B6 + B4)/2 and B3/B4
performed best in lakes and B2 + B3 + B4 + B5, B3/B6 and (B5-B4)/(B5 + B4) in reservoirs. The atmospheric
correction ELM performed worse than Sen2Cor and ATCOR in lakes. In reservoirs, ATCOR performed best and
C2XC and Dark Object Subtraction performed worse. Finally, classical machine learning and deep learning
models outperformed traditional linear and non-linear models. An integrated vision of remote sensing with
Ecology could improve some weaknesses found in the reviewed articles, such as the lack of methodological
details in field sampling or knowledge of the dynamics and functioning of the ecosystem to achieve the most
optimal sampling of the system. By doing so the field of remote sensing would have a higher aplicability. Some
further investigations are needed on small water bodies (area < 0.1 km2), which have been scarcely studied by
remote sensing, although accounting for >90% of the water bodies worldwide.},
organization = {European Union’s Horizon 2020 research and innovation
programme under grant agreement No 641762},
organization = {"Convenio de Colaboración entre la Consejería de Medio Ambiente y Ordenación del Territorio y la Universidad de Granada para el desarrollo de actividades vinculadas al Observatorio de Cambio Global de Sierra Nevada, en el marco de la Red de Observatorios de Cambio Global de Andalucía"},
organization = {eLTER H2020
project “European Long-Term Ecosystem and Socio-Ecological Research
Infrastructure” funded by the European Union’s Horizon 2020 programme
under grant agreement No 654359},
organization = {Project LACEN (OAPN 2403-S/2017)
which has been co-funded by the Ministry of Ecological transition in
their National Park Autonomous Agency action line.},
organization = {Project “Thematic Center on Mountain
Ecosystem & Remote sensing, Deep learning-AI e-Services University of
Granada-Sierra Nevada” (LifeWatch-2019-10-UGR-01), which has been
co-funded by the Ministry of Science and Innovation through the FEDER
funds from the Spanish Pluriregional Operational Program 2014-2020
(POPE), LifeWatch-ERIC action line},
organization = {Aid For University Teacher Training FPU 2019
(FPU19/04878) by the Spanish Ministry of Universities},
organization = {María Zambrano postdoctoral grant by the
Spanish Ministry of Universities and Next Generation European Union
funds},
publisher = {Elsevier},
keywords = {Remote sensing},
keywords = {Inland aquatic ecosystems},
keywords = {Water quality},
title = {Retrieving water chlorophyll-a concentration in inland waters from Sentinel-2 imagery: Review of operability, performance and ways forward},
doi = {10.1016/j.jag.2023.103605},
author = {Llodrà Llabrés, Joana María and López Martínez, Francisco Javier and Postma, Thedmer and Pérez Martínez, María del Carmen and Alcaraz Segura, Domingo},
}