Monitoring intertidal ecosystems: Assessing spatio–temporal variability with Sentinel-2 and Landsat 8

This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by- nc-nd/4.0/ ).

Detalles Bibliográficos
Autores: Zarzuelo Romero, Carmen, López-Ruiz, Alejandro, Bermúdez, María, Ortega-Sánchez, Miguel, Caballero, Isabel
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2025
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/175979
Acceso en línea:https://hdl.handle.net/11441/175979
https://doi.org/10.1016/j.jag.2025.104676
Access Level:acceso abierto
Palabra clave:Intertidal zones
Remote sensing
Spectral index
Transitional ecosystems
Tidal dynamics
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spelling Monitoring intertidal ecosystems: Assessing spatio–temporal variability with Sentinel-2 and Landsat 8Zarzuelo Romero, CarmenLópez-Ruiz, AlejandroBermúdez, MaríaOrtega-Sánchez, MiguelCaballero, IsabelIntertidal zonesRemote sensingSpectral indexTransitional ecosystemsTidal dynamicsThis is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by- nc-nd/4.0/ ).Intertidal zones are home to critical ecosystems that provide a wide range of ecological, social and economic benefits, but are increasingly vulnerable to climate change and anthropogenic pressures. This study aims to develop a robust methodology for mapping and analysing these areas using satellite imagery, focusing on the creation of a new spectral index specifically designed for zoning marsh ecosystems. The methodology involves selecting optimal satellite data, correcting for solar reflectance, identifying intertidal pixels using the Normalised Difference Water Index (NDWI) and classifying these zones into categories such as seagrass beds, mudflats, low marsh and high marsh. By comparing the effectiveness of Sentinel-2 and Landsat 8 datasets, the research addresses common challenges in land cover mapping of intertidal environments — such as cloud cover, reflectance variability and tidal influences. The Bay of Cádiz (south-west Spain), with its extensive intertidal areas characterised by diverse habitats such as mudflats, marshes and seagrass beds, serves as an ideal case study for understanding coastal dynamics driven by tidal cycles. The results highlight the usefulness of the proposed spectral index in assessing changes in intertidal habitats over time, achieving classification accuracies of up to 93.6%, and supporting long-term monitoring efforts that are crucial for coastal conservation strategies. By refining intertidal mapping techniques and improving the detection of specific land cover classes, this research addresses existing methodological gaps and provides valuable insights for local coastal management. In future work, the methodology could be adapted to other intertidal systems and integrated with additional data sources to simulate future scenarios under sea level rise or extreme events. These improvements will help guide effective, data-driven strategies for conserving intertidal ecosystems in the face of accelerating environmental change.ElsevierIngeniería Aeroespacial y Mecánica de FluidosMinisterio de Ciencia, Innovación y Universidades (MICIU). EspañaEuropean Union (UE)2025info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttps://hdl.handle.net/11441/175979https://doi.org/10.1016/j.jag.2025.104676reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésInternational Journal of Applied Earth Observation and Geoinformation, 142, 104676.CNS2023-143630PID2021-125895OA-I00PLEC2022-009362101060874https://www.sciencedirect.com/science/article/pii/S1569843225003231info:eu-repo/semantics/openAccessoai:idus.us.es:11441/1759792026-06-17T12:51:07Z
dc.title.none.fl_str_mv Monitoring intertidal ecosystems: Assessing spatio–temporal variability with Sentinel-2 and Landsat 8
title Monitoring intertidal ecosystems: Assessing spatio–temporal variability with Sentinel-2 and Landsat 8
spellingShingle Monitoring intertidal ecosystems: Assessing spatio–temporal variability with Sentinel-2 and Landsat 8
Zarzuelo Romero, Carmen
Intertidal zones
Remote sensing
Spectral index
Transitional ecosystems
Tidal dynamics
title_short Monitoring intertidal ecosystems: Assessing spatio–temporal variability with Sentinel-2 and Landsat 8
title_full Monitoring intertidal ecosystems: Assessing spatio–temporal variability with Sentinel-2 and Landsat 8
title_fullStr Monitoring intertidal ecosystems: Assessing spatio–temporal variability with Sentinel-2 and Landsat 8
title_full_unstemmed Monitoring intertidal ecosystems: Assessing spatio–temporal variability with Sentinel-2 and Landsat 8
title_sort Monitoring intertidal ecosystems: Assessing spatio–temporal variability with Sentinel-2 and Landsat 8
dc.creator.none.fl_str_mv Zarzuelo Romero, Carmen
López-Ruiz, Alejandro
Bermúdez, María
Ortega-Sánchez, Miguel
Caballero, Isabel
author Zarzuelo Romero, Carmen
author_facet Zarzuelo Romero, Carmen
López-Ruiz, Alejandro
Bermúdez, María
Ortega-Sánchez, Miguel
Caballero, Isabel
author_role author
author2 López-Ruiz, Alejandro
Bermúdez, María
Ortega-Sánchez, Miguel
Caballero, Isabel
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Ingeniería Aeroespacial y Mecánica de Fluidos
Ministerio de Ciencia, Innovación y Universidades (MICIU). España
European Union (UE)
dc.subject.none.fl_str_mv Intertidal zones
Remote sensing
Spectral index
Transitional ecosystems
Tidal dynamics
topic Intertidal zones
Remote sensing
Spectral index
Transitional ecosystems
Tidal dynamics
description This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by- nc-nd/4.0/ ).
publishDate 2025
dc.date.none.fl_str_mv 2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/11441/175979
https://doi.org/10.1016/j.jag.2025.104676
url https://hdl.handle.net/11441/175979
https://doi.org/10.1016/j.jag.2025.104676
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv International Journal of Applied Earth Observation and Geoinformation, 142, 104676.
CNS2023-143630
PID2021-125895OA-I00
PLEC2022-009362
101060874
https://www.sciencedirect.com/science/article/pii/S1569843225003231
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:idUS. Depósito de Investigación de la Universidad de Sevilla
instname:Universidad de Sevilla (US)
instname_str Universidad de Sevilla (US)
reponame_str idUS. Depósito de Investigación de la Universidad de Sevilla
collection idUS. Depósito de Investigación de la Universidad de Sevilla
repository.name.fl_str_mv
repository.mail.fl_str_mv
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