Articles | Volume 15, issue 11
https://doi.org/10.5194/nhess-15-2439-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/nhess-15-2439-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
02 Nov 2015
Research article |
| 02 Nov 2015
Railway deformation detected by DInSAR over active sinkholes in the Ebro Valley evaporite karst, Spain
Departamento de Geodinámica, Universidad de Granada, Campus de Fuentenueva s/n, 18071 Granada, Spain
C. Castañeda
Estación Experimental de Aula Dei, EEAD-CSIC, Ave. Montañana 1005, 50059 Zaragoza, Spain
F. Gutiérrez
Departamento de Ciencias de la Tierra, Universidad de Zaragoza, C/Pedro Cerbuna 12, 50009 Zaragoza, Spain
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Cited
19 citations as recorded by crossref.
- Geohazard assessment of Mexico City’s Metro system derived from SAR interferometry observations D. Solano-Rojas et al. 10.1038/s41598-024-53525-y
- Hydro-Stratigraphic Conditions and Human Activity Leading to Development of a Sinkhole Cluster in a Mediterranean Water Ecosystem S. Margiotta et al. 10.3390/hydrology8030111
- Studying subsidence in urban areas and its effect on transportation infrastructure using the method based on Persistent Scatterer. M. Arjmandrad et al. 10.52547/jgst.12.3.113
- Analysis of the Deformation Behavior and Sinkhole Risk in Kerdabad, Iran Using the PS-InSAR Method M. Khoshlahjeh Azar et al. 10.3390/rs13142696
- Non-Invasive Methodological Approach to Detect and Characterize High-Risk Sinkholes in Urban Cover Evaporite Karst: Integrated Reflection Seismics, PS-InSAR, Leveling, 3D-GPR and Ancillary Data. A NE Italian Case Study A. Busetti et al. 10.3390/rs12223814
- Surface Motion Prediction and Mapping for Road Infrastructures Management by PS-InSAR Measurements and Machine Learning Algorithms N. Fiorentini et al. 10.3390/rs12233976
- Multi- and inter-disciplinary approaches towards understanding the sinkholes’ phenomenon in the Dead Sea Basin H. Salem 10.1007/s42452-020-2146-0
- Evaluation of the SBAS InSAR Service of the European Space Agency’s Geohazard Exploitation Platform (GEP) J. Galve et al. 10.3390/rs9121291
- Can Machine Learning and PS-InSAR Reliably Stand in for Road Profilometric Surveys? N. Fiorentini et al. 10.3390/s21103377
- The Role of Earth Observation, with a Focus on SAR Interferometry, for Sinkhole Hazard Assessment A. Theron & J. Engelbrecht 10.3390/rs10101506
- Natural Sinkhole Monitoring and Characterization: The Case of Latera Sinkhole (Latium, Central Italy) L. Puzzilli et al. 10.3390/geosciences14010018
- A catenary model for the analysis of arching effect in soils and its application to predicting sinkhole collapse J. Alonso et al. 10.1680/jgeot.20.P.235
- DInSAR data assimilation for settlement prediction: case study of a railway embankment in the Netherlands D. Peduto et al. 10.1139/cgj-2016-0425
- Characterizing and monitoring a high-risk sinkhole in an urban area underlain by salt through non-invasive methods: Detailed mapping, high-precision leveling and GPR J. Sevil et al. 10.1016/j.enggeo.2020.105641
- Evolution of surface deformation related to salt-extraction-caused sinkholes in Solotvyno (Ukraine) revealed by Sentinel-1 radar interferometry E. Szűcs et al. 10.5194/nhess-21-977-2021
- Multi-Temporal Satellite Interferometry for Fast-Motion Detection: An Application to Salt Solution Mining L. Solari et al. 10.3390/rs12233919
- Earthquake-induced landslide monitoring and survey by means of InSAR T. Smail et al. 10.5194/nhess-22-1609-2022
- Rapid subsidence in damaging sinkholes: Measurement by high-precision leveling and the role of salt dissolution G. Desir et al. 10.1016/j.geomorph.2017.12.004
- Paleoflood records from sinkholes using an example from the Ebro River floodplain, northeastern Spain F. Gutiérrez et al. 10.1017/qua.2017.23
17 citations as recorded by crossref.
- Geohazard assessment of Mexico City’s Metro system derived from SAR interferometry observations D. Solano-Rojas et al. 10.1038/s41598-024-53525-y
- Hydro-Stratigraphic Conditions and Human Activity Leading to Development of a Sinkhole Cluster in a Mediterranean Water Ecosystem S. Margiotta et al. 10.3390/hydrology8030111
- Studying subsidence in urban areas and its effect on transportation infrastructure using the method based on Persistent Scatterer. M. Arjmandrad et al. 10.52547/jgst.12.3.113
- Analysis of the Deformation Behavior and Sinkhole Risk in Kerdabad, Iran Using the PS-InSAR Method M. Khoshlahjeh Azar et al. 10.3390/rs13142696
- Non-Invasive Methodological Approach to Detect and Characterize High-Risk Sinkholes in Urban Cover Evaporite Karst: Integrated Reflection Seismics, PS-InSAR, Leveling, 3D-GPR and Ancillary Data. A NE Italian Case Study A. Busetti et al. 10.3390/rs12223814
- Surface Motion Prediction and Mapping for Road Infrastructures Management by PS-InSAR Measurements and Machine Learning Algorithms N. Fiorentini et al. 10.3390/rs12233976
- Multi- and inter-disciplinary approaches towards understanding the sinkholes’ phenomenon in the Dead Sea Basin H. Salem 10.1007/s42452-020-2146-0
- Evaluation of the SBAS InSAR Service of the European Space Agency’s Geohazard Exploitation Platform (GEP) J. Galve et al. 10.3390/rs9121291
- Can Machine Learning and PS-InSAR Reliably Stand in for Road Profilometric Surveys? N. Fiorentini et al. 10.3390/s21103377
- The Role of Earth Observation, with a Focus on SAR Interferometry, for Sinkhole Hazard Assessment A. Theron & J. Engelbrecht 10.3390/rs10101506
- Natural Sinkhole Monitoring and Characterization: The Case of Latera Sinkhole (Latium, Central Italy) L. Puzzilli et al. 10.3390/geosciences14010018
- A catenary model for the analysis of arching effect in soils and its application to predicting sinkhole collapse J. Alonso et al. 10.1680/jgeot.20.P.235
- DInSAR data assimilation for settlement prediction: case study of a railway embankment in the Netherlands D. Peduto et al. 10.1139/cgj-2016-0425
- Characterizing and monitoring a high-risk sinkhole in an urban area underlain by salt through non-invasive methods: Detailed mapping, high-precision leveling and GPR J. Sevil et al. 10.1016/j.enggeo.2020.105641
- Evolution of surface deformation related to salt-extraction-caused sinkholes in Solotvyno (Ukraine) revealed by Sentinel-1 radar interferometry E. Szűcs et al. 10.5194/nhess-21-977-2021
- Multi-Temporal Satellite Interferometry for Fast-Motion Detection: An Application to Salt Solution Mining L. Solari et al. 10.3390/rs12233919
- Earthquake-induced landslide monitoring and survey by means of InSAR T. Smail et al. 10.5194/nhess-22-1609-2022
2 citations as recorded by crossref.
- Rapid subsidence in damaging sinkholes: Measurement by high-precision leveling and the role of salt dissolution G. Desir et al. 10.1016/j.geomorph.2017.12.004
- Paleoflood records from sinkholes using an example from the Ebro River floodplain, northeastern Spain F. Gutiérrez et al. 10.1017/qua.2017.23
Saved (final revised paper)
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Latest update: 21 Nov 2024
Short summary
The bedrock of the Ebro Valley consists of soluble geological formations of evaporites. The subsurface dissolution of these rocks makes this area particularly prone to the development of sinkholes. These show subsidence that causes damage to man-made structures. The article focuss on the subsidence detected along railways that traverse sinkholes. DInSAR analysis may help in the identification of subsiding sectors of railway tracks that may compromise the safety of travellers.
The bedrock of the Ebro Valley consists of soluble geological formations of evaporites. The...
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