ADAtools: Automatic Detection and Classification of Active Deformation Areas from PSI Displacement Maps
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http://hdl.handle.net/10045/109607
Títol: | ADAtools: Automatic Detection and Classification of Active Deformation Areas from PSI Displacement Maps |
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Autors: | Navarro, José A. | Tomás, Roberto | Barra, Anna | Pagán, José Ignacio | Reyes-Carmona, Cristina | Solari, Lorenzo | López-Vinielles, Juan | Falco, Salvatore | Crosetto, Michele |
Grups d'investigació o GITE: | Ingeniería del Terreno y sus Estructuras (InTerEs) | Ingeniería del Transporte, Territorio y Medio Litoral (AORTA) |
Centre, Departament o Servei: | Universidad de Alicante. Departamento de Ingeniería Civil |
Paraules clau: | Software Tools | Process Automation | Ground Deformation Analysis | Ground Deformation Classification | InSAR |
Àrees de coneixement: | Ingeniería del Terreno | Ingeniería e Infraestructura de los Transportes |
Data de publicació: | 6-d’octubre-2020 |
Editor: | MDPI |
Citació bibliogràfica: | Navarro JA, Tomás R, Barra A, Pagán J, Reyes-Carmona C, Solari L, Vinielles J, Falco S, Crosetto M. ADAtools: Automatic Detection and Classification of Active Deformation Areas from PSI Displacement Maps. ISPRS International Journal of Geo-Information. 2020; 9(10):584. https://doi.org/10.3390/ijgi9100584 |
Resum: | This work describes the set of tools developed, tested, and put into production in the context of the H2020 project Multi-scale Observation and Monitoring of Railway Infrastructure Threats (MOMIT). This project, which ended in 2019, aimed to show how the use of various remote sensing techniques could help to improve the monitoring of railway infrastructures, such as tracks or bridges, and thus, consequently, improve the detection of ground instabilities and facilitate their management. Several lines of work were opened by MOMIT, but the authors of this work concentrated their efforts in the design of tools to help the detection and identification of ground movements using synthetic aperture radar interferometry (InSAR) data. The main output of this activity was a set of tools able to detect the areas labelled active deformation areas (ADA), with the highest deformation rates and to connect them to a geological or anthropogenic process. ADAtools is the name given to the aforementioned set of tools. The description of these tools includes the definition of their targets, inputs, and outputs, as well as details on how the correctness of the applications was checked and on the benchmarks showing their performance. The ADAtools include the following applications: ADAfinder, los2hv, ADAclassifier, and THEXfinder. The toolset is targeted at the analysis and interpretation of InSAR results. Ancillary information supports the semi-automatic interpretation and classification process. Two real use-cases illustrating this statement are included at the end of this paper to show the kind of results that may be obtained with the ADAtools. |
Patrocinadors: | This work has received funding from the Shift2Rail Joint Undertaking under the European Union's Horizon 2020 research and innovation programme, with grant agreement No 777630, project MOMIT, “Multi-scale Observation and Monitoring of railway Infrastructure Threats”. It has been also partially funded by Interreg-Sudoe program of the EU, through the project RISKCOAST (Ref: SOE3/P4/E0868). |
URI: | http://hdl.handle.net/10045/109607 |
ISSN: | 2220-9964 |
DOI: | 10.3390/ijgi9100584 |
Idioma: | eng |
Tipus: | info:eu-repo/semantics/article |
Drets: | © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
Revisió científica: | si |
Versió de l'editor: | https://doi.org/10.3390/ijgi9100584 |
Apareix a la col·lecció: | INV - AORTA - Artículos de Revistas INV - INTERES - Artículos de Revistas Investigacions finançades per la UE |
Arxius per aquest ítem:
Arxiu | Descripció | Tamany | Format | |
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Navarro_etal_2020_ISPRSIntJGeo-Inf.pdf | 1,75 MB | Adobe PDF | Obrir Vista prèvia | |
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