The Validation of InSAR Time Series for Landfill Characterization and Monitoring: A Geospatial Approach to Ecological Security and Land System Sustainability

[EN] This study applies InSAR time series analysis derived from Sentinel-1 satellite data (ascending and descending orbits) processed with ISCE2 and StaMPS (v.4.1) software to evaluate deformation dynamics in three landfill types near Gijón, Spain. Initially, the data were validated against the Euro...

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Autores: Allende-Prieto, Cristina, Rodríguez Gonzálvez, Pablo, Álvarez-Fuertes, David, Perdiguer-Lopez, Raquel
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2026
País:España
Institución:Universidad de León
Repositorio:BULERIA. Repositorio Institucional de la Universidad de León
OAI Identifier:oai:dnet:buleria_____::e1133331399eb90d1bdff75597d3d0ef
Acceso en línea:https://hdl.handle.net/10612/28184
Access Level:acceso abierto
Palabra clave:Ingeniería civil
Topografía
InSAR data validation
StaMPS software
Illegal landfill detection
EGMS
Ez-InSAR toolbox
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spelling The Validation of InSAR Time Series for Landfill Characterization and Monitoring: A Geospatial Approach to Ecological Security and Land System SustainabilityAllende-Prieto, CristinaRodríguez Gonzálvez, PabloÁlvarez-Fuertes, DavidPerdiguer-Lopez, RaquelIngeniería civilTopografíaInSAR data validationStaMPS softwareIllegal landfill detectionEGMSEz-InSAR toolbox[EN] This study applies InSAR time series analysis derived from Sentinel-1 satellite data (ascending and descending orbits) processed with ISCE2 and StaMPS (v.4.1) software to evaluate deformation dynamics in three landfill types near Gijón, Spain. Initially, the data were validated against the European Ground Motion Service (EGMS) dataset using a set of Persistent Scatterers (PS) in an urban control area through two analytical approaches (EGMS protocol and PSDefoPAT(2023)). The results showed high consistency, with 82–85% of points classified as highly reliable. Subsequently, this control group was compared with PS from each landfill type (active sanitary, operational inert, and closed inert). Significant deformation differences were found in each landfill type: the active sanitary landfill exhibited distinct anomalies depending on orbit, with strong residual variance instability detected (p < 0.003) in both. Operational inert landfills showed significant anomalies (p < 0.001) in both orbits with variable stability, while closed inert landfills displayed strong stability (p > 0.7) and variable anomalies. These results confirm the efficacy of InSAR approaches for detecting active landfill zones to aid in locating illegal or unauthorized dumping sites and to direct in situ inspection planning.SIThis work was supported by the Economic Development Institute of the Principality of Asturias under Grant IDE/2018/000400 and IDE/2022/000472, by the Ministry of Industry, Commerce and Tourism of the Government of Spain under grant AEI-010500-2023-72, and by the City Council of Gijón and the University Institute of Industrial Technology of Asturias, Spain (IUTA) under grant SV-22-GIJON-09.MDPIIngeniería Cartografica, Geodesica y FotogrametriaEscuela Superior y Tecnica de Ingenieros de Minas2026info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttps://hdl.handle.net/10612/28184reponame:BULERIA. Repositorio Institucional de la Universidad de Leóninstname:Universidad de LeónIngléshttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:dnet:buleria_____::e1133331399eb90d1bdff75597d3d0ef2026-06-24T12:43:27Z
dc.title.none.fl_str_mv The Validation of InSAR Time Series for Landfill Characterization and Monitoring: A Geospatial Approach to Ecological Security and Land System Sustainability
title The Validation of InSAR Time Series for Landfill Characterization and Monitoring: A Geospatial Approach to Ecological Security and Land System Sustainability
spellingShingle The Validation of InSAR Time Series for Landfill Characterization and Monitoring: A Geospatial Approach to Ecological Security and Land System Sustainability
Allende-Prieto, Cristina
Ingeniería civil
Topografía
InSAR data validation
StaMPS software
Illegal landfill detection
EGMS
Ez-InSAR toolbox
title_short The Validation of InSAR Time Series for Landfill Characterization and Monitoring: A Geospatial Approach to Ecological Security and Land System Sustainability
title_full The Validation of InSAR Time Series for Landfill Characterization and Monitoring: A Geospatial Approach to Ecological Security and Land System Sustainability
title_fullStr The Validation of InSAR Time Series for Landfill Characterization and Monitoring: A Geospatial Approach to Ecological Security and Land System Sustainability
title_full_unstemmed The Validation of InSAR Time Series for Landfill Characterization and Monitoring: A Geospatial Approach to Ecological Security and Land System Sustainability
title_sort The Validation of InSAR Time Series for Landfill Characterization and Monitoring: A Geospatial Approach to Ecological Security and Land System Sustainability
dc.creator.none.fl_str_mv Allende-Prieto, Cristina
Rodríguez Gonzálvez, Pablo
Álvarez-Fuertes, David
Perdiguer-Lopez, Raquel
author Allende-Prieto, Cristina
author_facet Allende-Prieto, Cristina
Rodríguez Gonzálvez, Pablo
Álvarez-Fuertes, David
Perdiguer-Lopez, Raquel
author_role author
author2 Rodríguez Gonzálvez, Pablo
Álvarez-Fuertes, David
Perdiguer-Lopez, Raquel
author2_role author
author
author
dc.contributor.none.fl_str_mv Ingeniería Cartografica, Geodesica y Fotogrametria
Escuela Superior y Tecnica de Ingenieros de Minas
dc.subject.none.fl_str_mv Ingeniería civil
Topografía
InSAR data validation
StaMPS software
Illegal landfill detection
EGMS
Ez-InSAR toolbox
topic Ingeniería civil
Topografía
InSAR data validation
StaMPS software
Illegal landfill detection
EGMS
Ez-InSAR toolbox
description [EN] This study applies InSAR time series analysis derived from Sentinel-1 satellite data (ascending and descending orbits) processed with ISCE2 and StaMPS (v.4.1) software to evaluate deformation dynamics in three landfill types near Gijón, Spain. Initially, the data were validated against the European Ground Motion Service (EGMS) dataset using a set of Persistent Scatterers (PS) in an urban control area through two analytical approaches (EGMS protocol and PSDefoPAT(2023)). The results showed high consistency, with 82–85% of points classified as highly reliable. Subsequently, this control group was compared with PS from each landfill type (active sanitary, operational inert, and closed inert). Significant deformation differences were found in each landfill type: the active sanitary landfill exhibited distinct anomalies depending on orbit, with strong residual variance instability detected (p < 0.003) in both. Operational inert landfills showed significant anomalies (p < 0.001) in both orbits with variable stability, while closed inert landfills displayed strong stability (p > 0.7) and variable anomalies. These results confirm the efficacy of InSAR approaches for detecting active landfill zones to aid in locating illegal or unauthorized dumping sites and to direct in situ inspection planning.
publishDate 2026
dc.date.none.fl_str_mv 2026
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/10612/28184
url https://hdl.handle.net/10612/28184
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:BULERIA. Repositorio Institucional de la Universidad de León
instname:Universidad de León
instname_str Universidad de León
reponame_str BULERIA. Repositorio Institucional de la Universidad de León
collection BULERIA. Repositorio Institucional de la Universidad de León
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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