Potential and Limitations of the New European Ground Motion Service in Landslides at a Local Scale
Abstract
:1. Introduction
2. Materials and Methods
2.1. Setting
2.2. Sentinel-1 A-DInSAR by Means of European Ground Motion Service
2.3. Geomorphological Mapping
2.4. Damage Inventory Map
2.5. Collection and Analysis of Climatic Data
3. Results
3.1. Sentinel-1 A-DInSAR Measurements
3.2. Geomorphological Features and Sentinel-1 A-DInSAR
3.3. Buildings Damage and Sentinel-1 A-DInSAR
3.4. Daily Rainfall Records vs. Sentinel-1 A-DInSAR
4. Discussion
4.1. La Miera Landslide Characterization
4.2. Potential and Limitations of the EGMS
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Wallemacq, P.; House, R.; McClean, D.; Below, R. Economic Losses, Poverty and Disasters: 1998–2017; United Nations Office for Disaster Risk Reduction: Geneva, Switzerland, 2018; pp. 6–13. [Google Scholar]
- European Environment Agency (EEA). Mapping the Impacts of Natural Hazards and Technological Accidents in Europe: An overview of the Last Decade; EEA Technical report No 13/2010; European Environment Agency (EEA): Copenhagen, Denmark, 2010; pp. 81–93.
- Domínguez-Cuesta, M.J.; Jiménez-Sánchez, M.; Rodríguez García, A. Press archives as temporal records of landslides in the North of Spain: Relationships between rainfall and instability slope events. Geomorphology 1999, 30, 125–132. [Google Scholar] [CrossRef]
- Valenzuela, P.; Domínguez-Cuesta, M.J.; Mora García, M.A.; Jiménez-Sánchez, M. A spatio-temporal landslide inventory for the NW of Spain: BAPA database. Geomorphology 2017, 293, 11–23. [Google Scholar] [CrossRef]
- González Moradas, M.R.; Lima de Montes, Y. Cartografía del riesgo a los deslizamientos en la zona central del Principado de Asturias. Mapping 2001, 73, 6–14. [Google Scholar]
- Domínguez-Cuesta, M.J.; Jiménez-Sánchez, M.; Berrezueta, E. Landslides in the Central Coalfield (Cantabrian Mountains, NW Spain): Geomorphological features, conditioning factors and methodological implications in susceptibility assessment. Geomorphology 2007, 89, 358–369. [Google Scholar] [CrossRef]
- Valenzuela, P.; Iglesias, M.; Domínguez-Cuesta, M.; Mora García, M. Meteorological Patterns Linked to Landslide Triggering in Asturias (NW Spain): A Preliminary Analysis. Geosciences 2018, 8, 18. [Google Scholar] [CrossRef]
- Rączkowska, Z.; Zwoliński, Z. Digital geomorphological map of Poland. Geogr. Pol. 2015, 88, 205–210. [Google Scholar] [CrossRef]
- Chandler, B.M.P.; Lovell, H.; Boston, C.M.; Lukas, S.; Barr, I.D.; Benediktsson, I.O.; Benn, D.I.; Clark, C.D.; Darvill, C.M.; Evans, D.J.A.; et al. Glacial geomorphological mapping: A review of approaches and frameworks for best practice. Earth Sci. Rev. 2018, 185, 806–846. [Google Scholar] [CrossRef]
- Keller, E.; Adamaitis, C.; Alessio, P.; Anderson, S.; Goto, E.; Gray, S.; Gurrola, L.; Morell, K. Applications in geomorphology. Geomorphology 2020, 366, 106729. [Google Scholar] [CrossRef]
- Bruschi, V.M.; Coratza, P.; Piacentini, D.; Soldati, M. Geomorphological features of the Rio della Rocca valley (northern Apennines, Italy). J. Maps 2012, 8, 445–452. [Google Scholar] [CrossRef]
- Mikkelsen, P.E. Field Instrumentation. In Landslides: Investigation and Mitigation; Turner, A.K., Schuster, R.L., Eds.; Transportation Research Board, National Academy of Sciences: Washington, DC, USA, 1996; pp. 278–316. [Google Scholar]
- Jaboyedoff, M.; Oppikofer, T.; Abellán, A.; Derron, M.H.; Loye, A.; Metzger, R.; Pedrazzini, A. Use of LIDAR in lanslide investigations: A review. Nat. Hazards 2012, 61, 5–28. [Google Scholar] [CrossRef]
- Mondini, A.C.; Guzzetti, F.; Chang, K.T.; Monserrat, O.; Martha, T.R.; Manconi, A. Landslide failures detection and mapping using Synthetic Aperture Radar: Past, present and future. Earth Sci. Rev. 2021, 216, 103574. [Google Scholar] [CrossRef]
- Jongmans, D.; Garambois, S. Geophysical investigation of landslides: A review. Bull. Soc. Géol. Fr. 2007, 178, 101–112. [Google Scholar] [CrossRef]
- Domínguez-Cuesta, M.J.; Quintana, L.; Valenzuela, P.; Cuervas-Mons, J.; Alonso, J.L.; García Cortés, S. Evolution of a human-induced mass movement under the influence of rainfall and soil moisture. Landslides 2021, 18, 3685–3693. [Google Scholar] [CrossRef]
- Smith, H.G.; Neverman, A.J.; Betts, H.; Spiekermann, R. The influence of spatial patterns in rainfall on shallow landslides. Geomorphology 2023, 437, 108795. [Google Scholar] [CrossRef]
- Sidle, R.C. Using Weather and Climate Information for Landslide Prevention and Mitigation. In Climate and Land Degradation. Environmental Science and Engineering; Sivakumar, M.V.K., Ndiang’ui, N., Eds.; Springer: Berlin, Germany, 2007; pp. 285–307. [Google Scholar] [CrossRef]
- Fruneau, B.; Achache, J.; Delacourt, C. Observation and modelling of the Saint-Etienne-de-Tinée landslide using SAR interferometry. Tectonophysics 1996, 265, 181–190. [Google Scholar] [CrossRef]
- Herrera, G.; Notti, D.; García-Davalillo, J.C.; Mora, O.; Cooksley, G.; Sánchez, M.; Arnaud, A.; Crosetto, M. Analysis with C- and X-band satellite SAR data of the Portalet landslide area. Landslides 2011, 8, 195–206. [Google Scholar] [CrossRef]
- Mateos, R.M.; Ezquerro, P.; Azañón, J.M.; Gelabert, B.; Herrera, G.; Fernández-Merodo, J.A.; Spizzichino, D.; Sarro, R.; García-Moreno, I.; Béjar-Pizarro, M. Coastal lateral spreading in the world heritage site of the Tramuntana Range (Majorca, Spain). The use of PSInSAR monitoring to identify vulnerability. Landslides 2018, 15, 797–809. [Google Scholar] [CrossRef]
- Pedretti, L.; Bordoni, M.; Vivaldi, V.; Figini, S.; Parnigoni, M.; Grossi, A.; Lanteri, L.; Tararbra, M.; Negro, N.; Meisina, C. InterpolatiON of InSAR Time series for the dEtection of ground deforMatiOn eVEnts (ONtheMOVE): Application to slow-moving landslides. Landslides 2023, 20, 1797–1813. [Google Scholar] [CrossRef]
- Rott, H. Advances in interferometric synthetic aperture radar (InSAR) in earth system science. Prog. Phys. Geogr. Earth Environ. 2009, 33, 769–791. [Google Scholar] [CrossRef]
- Ferretti, A.; Prati, C.; Rocca, F. Nonlinear subsidence rate estimation using permanent scatterers in differential SAR interferometry. IEEE Trans. Geosci. Remote Sens. 2000, 38, 2202–2212. [Google Scholar] [CrossRef]
- Ferretti, A.; Prati, C.; Rocca, F. Permanent scatterers in SAR interferometry. IEEE Trans. Geosci. Remote Sens. 2001, 39, 1528–1530. [Google Scholar] [CrossRef]
- Berardino, P.; Fornaro, G.; Lanari, R.; Sansosti, E. A new algorithm for monitoring localized deformation phenomena based on small baseline differential SAR interferograms. IEEE Trans. Geosci. Remote Sens. 2002, 40, 2375–2383. [Google Scholar] [CrossRef]
- Mora, O.; Mallorqui, J.J.; Broquetas, A. Linear and Nonlinear Terrain Deformation Maps From a Reduced Set of Interferometric SAR Images. IEEE Trans. Geosci. Remote Sens. 2003, 41, 2243–2253. [Google Scholar] [CrossRef]
- Galve, J.P.; Pérez-Peña, J.V.; Azañón, J.M.; Closson, D.; Caló, F.; Reyes-Carmona, C.; Jabaloy, A.; Ruano, P.; Mateos, R.M.; Notti, D.; et al. Evaluation of the SBAS InSAR service of the European space Agency’s Geohazard Exploitation Platform (GEP). Remote Sens. 2017, 9, 1291. [Google Scholar] [CrossRef]
- Cigna, F.; Tapete, D. Sentinel-1 Big Data Processing with P-SBAS InSAR in the Geohazards Exploitation Platform: An Experiment on Coastal Land Subsidence and Landslides in Italy. Remote Sens. 2021, 13, 885. [Google Scholar] [CrossRef]
- Cuervas-Mons, J.; Zêzere, J.L.; Domínguez-Cuesta, M.J.; Barra, A.; Reyes-Carmona, C.; Monserrat, O.; Oliveira, S.C.; Melo, R. Assessment of Urban Subsidence in the Lisbon Metropolitan Area (Central-West of Portugal) Applying Sentinel-1 SAR Dataset and Active Deformation Areas Procedure. Remote Sens. 2022, 14, 4084. [Google Scholar] [CrossRef]
- Crosetto, M.; Solari, L.; Balasis-Levinsen, J. The Evolution of Wide-Area DInSAR: From Regional and National Services to the European Ground Motion Service. Remote Sens. 2020, 12, 2043. [Google Scholar] [CrossRef]
- Crosetto, M.; Solari, L.; Balasis-Levinsen, J.; Bateson, L.; Casagli, N.; Frei, M.; Oyen, A.; Moldestad, D.A.; Mróz, M. Deformation monitoring at European Scale: The Copernicus Ground Motion Service. In Proceedings of the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Science, XXIV ISPRS Congress 2021, Nice, France, 5–9 July 2021; Volume XLIII-B3-2021, pp. 141–146. [Google Scholar]
- Festa, D.; Soldato, M. Del EGMStream, a Desktop App for EGMS Data Downstream. Remote Sens. 2023, 15, 2581. [Google Scholar] [CrossRef]
- Crosetto, M.; Solari, L.; Barra, A.; Monserrat, O.; Cuevas-González, M.; Palamà, R.; Wassie, Y.; Shahbazi, S.; Mirmazloumi, S.M.; Crippa, B.; et al. Analysis of the products of the Copernicus Ground Motion. In Proceedings of the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Science, XXIV ISPRS Congress 2022, Nice, France, 5–9 July 2022; Volume XLIII-B3-2022, pp. 257–262. [Google Scholar] [CrossRef]
- Costantini, M.; Minati, F.; Trillo, F.; Ferretti, A.; Passera, E.; Rucci, A.; Dehls, J.; Larsen, Y.; Marinkovic, P.; Eineder, M.; et al. EGMS: Europe-Wide Ground Motion Monitoring based on Full Resolution Insar Processing of All Sentinel-1 Acquisitions. In Proceedings of the IGARSS 2022–2022 IEEE International Geoscience and Remote Sensing Symposium, Kuala Lumpur, Malaysia, 17–22 July 2022; pp. 5093–5096. [Google Scholar] [CrossRef]
- Siegmund, R.; Brcic, R.; Kotzerke, P.; Eineder, M. The European Ground Motion Service EGMS–Processing Central Europe with First Results on Quality and Point Densities. In Proceedings of the IGARSS 2022–2022 IEEE International Geoscience and Remote Sensing Symposium, Kuala Lumpur, Malaysia, 17–22 July 2022; pp. 5105–5108. [Google Scholar] [CrossRef]
- Dehls, J.F.; Kenyeres, A.; Tóth, S.; Larsen, Y.; Marinkovic, P. Towards Geodetically Robust Datum Connection of Large-Scale InSar Results–EGMS Perspective. In Proceedings of the IGARSS 2022–2022 IEEE International Geoscience and Remote Sensing Symposium, Kuala Lumpur, Malaysia, 17–22 July 2022; pp. 5097–5100. [Google Scholar] [CrossRef]
- Even, M.; Westerhaus, M.; Kutterer, H. German and European Ground Motion Service: A Comparison. PFG J. Photogramm. Remote Sens. Geoinf. Sci. 2024, 92, 253–270. [Google Scholar] [CrossRef]
- Yang, C.H.; Stemmler, C.; Müterthies, A. Ground movement analysis in post-mining city using MTInSAR with help of European Ground Motion Service. In Proceedings of the ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences 2023, Cairo, Egypt, 2–7 September 2023; Volume X-1/W1-2023, pp. 739–745. [Google Scholar] [CrossRef]
- Tzampoglou, P.; Loupasakis, C. Hydrogeological Hazards in Open Pit Coal Mines–Investigating Triggering Mechanisms by Validating the European Ground Motion Service Product with Ground Truth Data. Water 2023, 15, 1474. [Google Scholar] [CrossRef]
- Eskandari, R.; Scaioni, M. European Ground Motion Service for bridge monitoring: Temporal and thermal deformation cross-check using Cosmo-SkyMed InSAR. In Proceedings of the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Science 2023, Cairo, Egypt, 2–7 September 2023; Volume XLVIII-1/W2-2023, pp. 1235–1241. [Google Scholar] [CrossRef]
- Torre, D.; Galve, J.P.; Reyes-Carmona, C.; Alfonso-Jorde, D.; Ballesteros, D.; Menichetti, M.; Piacentini, D.; Troiani, F.; Azañón, J.M. Geomorphological assessment as basic complement of InSAR analysis for landslide processes understanding. Landslides 2024, 21, 1273–1292. [Google Scholar] [CrossRef]
- Instituto Geológico y Minero de España. Mapa Geológico de España. Pola de Lena 78 (13-06); Instituto Geológico y Minero de España: Madrid, Spain, 1973. [Google Scholar]
- Instituto Geológico y Minero de España Información Geocientífica del IGME. Visor Cartográfico 2023. Available online: http://info.igme.es/visor/ (accessed on 15 June 2023).
- Instituto de Recursos Naturales y Ordenación del Territorio (INDUROT) Cartografía Temática Ambiental del Principado de Asturias. Formaciones Superficiales 1:25,000. Available online: https://ideas.asturias.es/catalogo-de-metadatos/?uuid=spaGOPActa1990 (accessed on 15 June 2023).
- Ministerio de Hacienda y Función Pública. Gobierno de España. Sede Electrónica del Catastro. Buscador de Inmuebles y Visor Cartográfico. Available online: https://www.sedecatastro.gob.es/ (accessed on 1 September 2023).
- Pérez-Estaún, A.; Bastida, F.; Alonso, J.L.; Marquínez, J.; Aller, J.; Álvarez-Marrón, J.; Marcos, A.; Pulgar, J.A. A Thin-skinned Tectonics Model for an Arcuate Fold and Thrust Belt: The Cantabrian Zone (Variscan Ibero-Armorican Arc). Tectonics 1988, 7, 517–537. [Google Scholar] [CrossRef]
- García-Loygorri, A.; Ortuño, G.; De Liñan, C.C.; Gervilla, M.; Greber, C.; Feys, R. El Carbonífero de la Cuenca Central Asturiana. Trab. Geol. 1971, 3, 101–150. [Google Scholar]
- Shahbazi, S.; Crosetto, M.; Barra, A. Ground Deformation Analysis Using Basic Products of the Copernicus Ground Motion Service. In Proceedings of the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXIV ISPRS Congress 2022, Nice, France, 5–9 July 2022; Volume XLIII-B3-2022, pp. 349–354. [Google Scholar] [CrossRef]
- Ferretti, A.; Fumagalli, A.; Novali, F.; Prati, C.; Rocca, F.; Rucci, A. A New Algorithm for Processing Interferometric Data-Stacks: SqueeSAR. IEEE Trans. Geosci. Remote Sens. 2011, 49, 3460–3470. [Google Scholar] [CrossRef]
- Ferretti, A.; Passera, E.; Capes, R. End-to-end implementation and operation of the European Ground Motion Servuce (EGMS). Algorithm Theoretical Basis Document. EGMS-SC1, 2023. Available online: https://land.copernicus.eu/user-corner/technical-library/egms-algorithm-theoretical-basis-document (accessed on 10 April 2023).
- Hrysiewicz, A.; Khoshlahjeh Azar, M.; Holohan, E.P. EGMS-toolkit: A set of Python scripts for improved access to datasets from the European Ground Motion Service. Earth Sci. Inform. 2024. [Google Scholar] [CrossRef]
- Scheiber, R.; Moreira, A. Coregistration of interferometric SAR images using spectral diversity. IEEE Trans. Geosci. Remote Sens. 2000, 38, 2179–2191. [Google Scholar] [CrossRef]
- Costantini, M. A novel phase unwrapping method based on network programming. IEEE Trans. Geosci. Remote Sens. 1998, 36, 813–821. [Google Scholar] [CrossRef]
- Instituto Geográfico Nacional Centro de Descargas. Organismo Autónomo Centro Nacional de Información Geográfica. Available online: https://centrodedescargas.cnig.es/CentroDescargas/index.jsp# (accessed on 15 June 2023).
- Cooper, A.H. The classification, recording, databasing and use of information about building damage caused by subsidence and landslides. Q. J. Eng. Geol. Hydrogeol. 2008, 41, 409–424. [Google Scholar] [CrossRef]
- Agencia Estatal de Meteorología (AEMET) AEMET OpenData 2023. Available online: https://www.aemet.es/es/datos_abiertos/AEMET_OpenData (accessed on 1 September 2023).
- Cruden, D.; Varnes, D. Landslide Types and Processes. In Landslides: Investigation and Mitigation; Turner, A.K., Schuster, R.L., Eds.; Transportation Research Board, National Academy of Sciences: Washington, DC, USA, 1996; pp. 36–75. [Google Scholar]
- Finnegan, N.J.; Perkins, J.P.; Nereson, A.L.; Handwerger, A.L. Unsaturated Flow Processes and the Onset of Seasonal Deformation in Slow-Moving Landslides. J. Geophys. Res. Earth Surf. 2021, 126, e2020JF005758. [Google Scholar] [CrossRef]
- Troncone, A.; Pugliese, L.; Lamanna, G.; Conte, E. Prediction of rainfall-induced landslide movements in the presence of stabilizing piles. Eng. Geol. 2021, 288, 106143. [Google Scholar] [CrossRef]
- Handwerger, A.L.; Fielding, E.J.; Sangha, S.S.; Bekaert, D.P.S. Landslide Sensitivity and Response to Precipitation Changes in Wet and Dry Climates. Geophys. Res. Lett. 2022, 49, e2022GL099499. [Google Scholar] [CrossRef] [PubMed]
- Valenzuela, P.; Domínguez-Cuesta, M.J.; Mora García, M.A.; Jiménez-Sánchez, M. Rainfall thresholds for the triggering of landslides considering previous soil moisture conditions (Asturias, NW Spain). Landslides 2018, 15, 273–282. [Google Scholar] [CrossRef]
- Prats-Iraola, P.; Scheiber, R.; Marotti, L.; Wollstadt, S.; Reigber, A. TOPS Interferometry With TerraSAR-X. IEEE Trans. Geosci. Remote Sens. 2012, 50, 3179–3188. [Google Scholar] [CrossRef]
- Costantini, M.; Falco, S.; Malvarosa, F.; Minati, F.; Trillo, F.; Vecchioli, F. Persistent Scatterer Pair Interferometry: Approach and Application to COSMO-SkyMed SAR Data. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2014, 7, 2869–2879. [Google Scholar] [CrossRef]
- Yagüe-Martínez, N.; Prats-Iraola, P.; Member, S.; González, F.R.; Brcic, R.; Shau, R.; Member, S.; Geudtner, D.; Eineder, M.; Member, S.; et al. Interferometric Processing of Sentinel-1 TOPS Data. IEEE Trans. Geosci. Remote Sens. 2016, 54, 2220–2234. [Google Scholar] [CrossRef]
- Barra, A.; Reyes-Carmona, C.; Herrera, G.; Galve, J.P.; Solari, L.; Mateos, R.M.; Azañón, J.M.; Béjar-Pizarro, M.; López-Vinielles, J.; Palamà, R.; et al. From satellite interferometry displacements to potential damage maps: A tool for risk reduction and urban planning. Remote Sens. Environ. 2022, 282, 113294. [Google Scholar] [CrossRef]
- Esposito, C.; Mastrantoni, G.; Marmoni, G.M.; Antonielli, B.; Caprari, P.; Pica, A.; Schilirò, L.; Mazzanti, P.; Bozzano, F. From theory to practice: Optimisation of available information for landslide hazard assessment in Rome relying on official, fragmented data sources. Landslides 2023, 20, 2055–2073. [Google Scholar] [CrossRef]
- Hussain, Y.; Schlögel, R.; Innocenti, A.; Hamza, O.; Iannucci, R.; Martino, S.; Havenith, H. Review on the Geophysical and UAV-Based Methods Applied to Landslides. Remote Sens. 2022, 14, 4564. [Google Scholar] [CrossRef]
- Pellicani, R.; Argentiero, I.; Manzari, P.; Spilotro, G.; Marzo, C.; Ermini, R.; Apollonio, C. UAV and Airborne LiDAR Data for Interpreting Kinematic Evolution of Landslide Movements: The Case Study of the Montescaglioso Landslide. Geosciences 2019, 9, 248. [Google Scholar] [CrossRef]
- Domínguez-Cuesta, M.J.; Rodríguez-Rodríguez, L.; López-Fernández, C.; Pando, L.; Cuervas-Mons, J.; Olona, J.; González-Pumariega, P.; Serrano, J.; Valenzuela, P.; Jiménez-Sánchez, M. Using Remote Sensing Methods to Study Active Geomorphologic Processes on Cantabrian Coastal Cliffs. Remote Sens. 2022, 14, 5139. [Google Scholar] [CrossRef]
- Hooper, A. A multi-temporal InSAR method incorporating both persistent scatterer and small baseline approaches. Geophys. Res. Lett. 2008, 35, L16302. Available online: https://homepages.see.leeds.ac.uk/~earahoo/stamps/ (accessed on 15 January 2024). [CrossRef]
- Bovenga, F.; Nutricato, R.; Refice, A.; Guerriero, L.; Chiaradia, M.T. SPINUA: A flexible processing chain for ERS/ENVISAT long term interferometry. In Proceedings of the 2004 Envisat & ERS Symposium, Salzburg, Austria, 6–10 September 2004; Available online: https://github.com/khalidtijani/dcs-cnr-issia-spinua (accessed on 15 January 2024).
- Pieraccini, M.; Miccinesi, L. Ground-Based Radar Interferometry: A Bibliographic Review without. Remote Sens. 2019, 11, 1029. [Google Scholar] [CrossRef]
- Chang, S.; Deng, Y.; Zhang, Y.; Zhao, Q.; Wang, R.; Zhang, K. An Advanced Scheme for Range Ambiguity Suppression of Spaceborne SAR Based on Blind Source Separation. IEEE Trans. Geosci. Remote Sens. 2022, 60, 5230112. [Google Scholar] [CrossRef]
- Crosetto, M.; Gili, J.A.; Monserrat, O.; Cuevas-González, M.; Corominas, J.; Serral, D. Interferometric SAR monitoring of the Vallcebre landslide (Spain) using corner reflectors. Nat. Hazard Earth Syst. Sci. 2013, 13, 923–933. [Google Scholar] [CrossRef]
- Luzi, G.; Espín-López, P.F.; Pérez Mira, F.; Monserrat, O.; Crosetto, M. A Low-Cost Active Reflector for Interferometric Monitoring Based on Sentinel-1 SAR Images. Sensors 2021, 21, 2008. [Google Scholar] [CrossRef] [PubMed]
- Xia, Z.; Motagh, M.; Li, T. Performance Analysis of Dihedral Corner Reflectors for Slope Movements: A Case Study from Aniangzhai Landslide in China. IEEE Geosci. Remote Sens. Lett. 2022, 19, 4515606. [Google Scholar] [CrossRef]
- Huang, G.; Du, S.; Wang, D. GNSS techniques for real-time monitoring of landslides: A review. Satell. Navig. 2023, 4, 5. [Google Scholar] [CrossRef]
- Domínguez-Cuesta, M.J.; González-Pumariega, P.; Valenzuela, P.; López-Fernández, C.; Rodríguez-Rodríguez, L.; Ballesteros, D.; Mora, M.; Meléndez, M.; Herrera, F.; Marigil, M.A.; et al. Understanding the retreat of the Jurassic Cantabrian coast (N Spain): Comprehensive monitoring and 4D evolution model of the Tazones Lighthouse landslide. Mar. Geol. 2022, 449, 106836. [Google Scholar] [CrossRef]
Dataset | Level | Time Period | Number of Acquisitions | Product Code |
---|---|---|---|---|
001 ascending track | L2b | 01/2015–12/2021 | 359 | L2b_001_0255_IW1_VV |
052 descending track | L2b | 01/2015–12/2021 | 345 | L2b_052_0818_IW1_VV |
East–West component (Horizontal motion) | L3 | 01/2016–12/2021 | 363 | L3_E30N23_100km_E |
Vertical component (Vertical motion) | L3 | 01/2016–12/2021 | 363 | L3_E30N23_100km_U |
Dataset | Deformation Period | Displacement (mm) | Accumulated Rainfall (l/m2) | Rainfall (l/m2) | R2 |
---|---|---|---|---|---|
TS-Desc | 01/2021–08/2021 | −19.2 | −5134.2–−5601.2 | 30.8–40.4 | 0.84 |
TS-Hor | 10/2018–04/2019 | −7.3 | −3136.4–−3549.0 | 38.2–56.0 | 0.63 |
11/2019–01/2020 | −9.7 | −3898.0–−4295.2 | 50.2–50.8 | 0.65 | |
10/2020–03/2021 | −8.1 | −4744.4–−5364.4 | 24.0–40.1 | 0.45 | |
09/2021–12/2021 | −9.6 | −5603.8–−6065.8 | 58.2 | 0.91 |
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Cuervas-Mons, J.; Domínguez-Cuesta, M.J.; Jiménez-Sánchez, M. Potential and Limitations of the New European Ground Motion Service in Landslides at a Local Scale. Appl. Sci. 2024, 14, 7796. https://doi.org/10.3390/app14177796
Cuervas-Mons J, Domínguez-Cuesta MJ, Jiménez-Sánchez M. Potential and Limitations of the New European Ground Motion Service in Landslides at a Local Scale. Applied Sciences. 2024; 14(17):7796. https://doi.org/10.3390/app14177796
Chicago/Turabian StyleCuervas-Mons, José, María José Domínguez-Cuesta, and Montserrat Jiménez-Sánchez. 2024. "Potential and Limitations of the New European Ground Motion Service in Landslides at a Local Scale" Applied Sciences 14, no. 17: 7796. https://doi.org/10.3390/app14177796