Empowering intermediate cities: cost-effective heritage preservation through satellite remote sensing and deep learning

In the capitalist rush to attract more visitors, cities are committing significant resources to heritage conservation, driven by the substantial economic benefits generated by the tourism industry. However, less famous or less well-resourced cities, often with smaller populations, also known as inte...

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Autores: Rodríguez-Antuñano, Ignacio, Sousa, Joaquim João, Bakoň, Matus, Ruiz-Armenteros, Antonio Miguel, Martínez-Sánchez, Joaquín, Riveiro, Belén
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:España
Institución:Universidad de Jaén
Repositorio:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
OAI Identifier:oai:ruja.ujaen.es:10953/3901
Acceso en línea:https://www.tandfonline.com/doi/full/10.1080/01431161.2024.2358544
https://doi.org/10.1080/01431161.2024.2358544
https://hdl.handle.net/10953/3901
Access Level:acceso abierto
Palabra clave:Heritage Conservation
PAZ satellite
Multi-temporal Interferometric Synthetic Aperture Radar
Deep Convolutional Neural Network
Sentinel satellite
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spelling Empowering intermediate cities: cost-effective heritage preservation through satellite remote sensing and deep learningRodríguez-Antuñano, IgnacioSousa, Joaquim JoãoBakoň, MatusRuiz-Armenteros, Antonio MiguelMartínez-Sánchez, JoaquínRiveiro, BelénHeritage ConservationPAZ satelliteMulti-temporal Interferometric Synthetic Aperture RadarDeep Convolutional Neural NetworkSentinel satelliteIn the capitalist rush to attract more visitors, cities are committing significant resources to heritage conservation, driven by the substantial economic benefits generated by the tourism industry. However, less famous or less well-resourced cities, often with smaller populations, also known as intermediary cities, find it difficult to allocate funds to protect their most significant heritage sites. In this conservation context, intermediary cities, often on the periphery or ‘at the margins’, can fill the gaps and needs of urbanism through a better strategic understanding of the challenges of global touristification, thus this research provides urban planning tools for local governments with limited resources to preserve their architectural heritage through remote sensing, for its advantages in terms of lower economic cost, as a valuable monitoring tool to effectively identify high-vulnerability sites that require priority attention in the conservation of architectural heritage. In other words, it allows for a reduction in the territory of those areas located ‘at the margins’ in terms of urban planning and management, by approaching the territorial, urban, architectural and tourism problems from a transdisciplinary perspective in the preservation of the architectural heritage. This study explores the application of optical (Sentinel-2) using neural networks for classifying the land cover and radar (Sentinel-1 and PAZ) satellite images to obtain the ground motion as a geotechnical risk study, together with geospatial data, for the monitoring of architectural heritage in intermediate cities. Focusing on the districts of Bragança and Guarda in Portugal, the approach allows the direct identification of vulnerable architectural heritage, identifying 9 highly-vulnerable areas using PAZ data and 7 areas using Sentinel-1 data. Furthermore, this work provides an understanding of the potential and limitations of these technologies in heritage preservation because compares the processing results of freely accessible medium-resolution Sentinel-1 radar imagery with the high-resolution radar images from the innovative PAZ satellite.Taylor & Francis202520252024info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://www.tandfonline.com/doi/full/10.1080/01431161.2024.2358544https://doi.org/10.1080/01431161.2024.2358544https://www.tandfonline.com/doi/full/10.1080/01431161.2024.2358544https://hdl.handle.net/10953/3901reponame:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaéninstname:Universidad de JaénInglésInternational Journal of Remote Sensing, 45:12, 4046-4074CC0 1.0 Universalhttp://creativecommons.org/publicdomain/zero/1.0/info:eu-repo/semantics/openAccessoai:ruja.ujaen.es:10953/39012026-06-24T12:41:07Z
dc.title.none.fl_str_mv Empowering intermediate cities: cost-effective heritage preservation through satellite remote sensing and deep learning
title Empowering intermediate cities: cost-effective heritage preservation through satellite remote sensing and deep learning
spellingShingle Empowering intermediate cities: cost-effective heritage preservation through satellite remote sensing and deep learning
Rodríguez-Antuñano, Ignacio
Heritage Conservation
PAZ satellite
Multi-temporal Interferometric Synthetic Aperture Radar
Deep Convolutional Neural Network
Sentinel satellite
title_short Empowering intermediate cities: cost-effective heritage preservation through satellite remote sensing and deep learning
title_full Empowering intermediate cities: cost-effective heritage preservation through satellite remote sensing and deep learning
title_fullStr Empowering intermediate cities: cost-effective heritage preservation through satellite remote sensing and deep learning
title_full_unstemmed Empowering intermediate cities: cost-effective heritage preservation through satellite remote sensing and deep learning
title_sort Empowering intermediate cities: cost-effective heritage preservation through satellite remote sensing and deep learning
dc.creator.none.fl_str_mv Rodríguez-Antuñano, Ignacio
Sousa, Joaquim João
Bakoň, Matus
Ruiz-Armenteros, Antonio Miguel
Martínez-Sánchez, Joaquín
Riveiro, Belén
author Rodríguez-Antuñano, Ignacio
author_facet Rodríguez-Antuñano, Ignacio
Sousa, Joaquim João
Bakoň, Matus
Ruiz-Armenteros, Antonio Miguel
Martínez-Sánchez, Joaquín
Riveiro, Belén
author_role author
author2 Sousa, Joaquim João
Bakoň, Matus
Ruiz-Armenteros, Antonio Miguel
Martínez-Sánchez, Joaquín
Riveiro, Belén
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Heritage Conservation
PAZ satellite
Multi-temporal Interferometric Synthetic Aperture Radar
Deep Convolutional Neural Network
Sentinel satellite
topic Heritage Conservation
PAZ satellite
Multi-temporal Interferometric Synthetic Aperture Radar
Deep Convolutional Neural Network
Sentinel satellite
description In the capitalist rush to attract more visitors, cities are committing significant resources to heritage conservation, driven by the substantial economic benefits generated by the tourism industry. However, less famous or less well-resourced cities, often with smaller populations, also known as intermediary cities, find it difficult to allocate funds to protect their most significant heritage sites. In this conservation context, intermediary cities, often on the periphery or ‘at the margins’, can fill the gaps and needs of urbanism through a better strategic understanding of the challenges of global touristification, thus this research provides urban planning tools for local governments with limited resources to preserve their architectural heritage through remote sensing, for its advantages in terms of lower economic cost, as a valuable monitoring tool to effectively identify high-vulnerability sites that require priority attention in the conservation of architectural heritage. In other words, it allows for a reduction in the territory of those areas located ‘at the margins’ in terms of urban planning and management, by approaching the territorial, urban, architectural and tourism problems from a transdisciplinary perspective in the preservation of the architectural heritage. This study explores the application of optical (Sentinel-2) using neural networks for classifying the land cover and radar (Sentinel-1 and PAZ) satellite images to obtain the ground motion as a geotechnical risk study, together with geospatial data, for the monitoring of architectural heritage in intermediate cities. Focusing on the districts of Bragança and Guarda in Portugal, the approach allows the direct identification of vulnerable architectural heritage, identifying 9 highly-vulnerable areas using PAZ data and 7 areas using Sentinel-1 data. Furthermore, this work provides an understanding of the potential and limitations of these technologies in heritage preservation because compares the processing results of freely accessible medium-resolution Sentinel-1 radar imagery with the high-resolution radar images from the innovative PAZ satellite.
publishDate 2024
dc.date.none.fl_str_mv 2024
2025
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://www.tandfonline.com/doi/full/10.1080/01431161.2024.2358544
https://doi.org/10.1080/01431161.2024.2358544
https://www.tandfonline.com/doi/full/10.1080/01431161.2024.2358544
https://hdl.handle.net/10953/3901
url https://www.tandfonline.com/doi/full/10.1080/01431161.2024.2358544
https://doi.org/10.1080/01431161.2024.2358544
https://hdl.handle.net/10953/3901
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv International Journal of Remote Sensing, 45:12, 4046-4074
dc.rights.none.fl_str_mv CC0 1.0 Universal
http://creativecommons.org/publicdomain/zero/1.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv CC0 1.0 Universal
http://creativecommons.org/publicdomain/zero/1.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Taylor & Francis
publisher.none.fl_str_mv Taylor & Francis
dc.source.none.fl_str_mv reponame:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
instname:Universidad de Jaén
instname_str Universidad de Jaén
reponame_str RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
collection RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,812429

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