EGU22-7308, updated on 07 Nov 2024
https://doi.org/10.5194/egusphere-egu22-7308
EGU General Assembly 2022
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Building an InSAR-based database to support geohazard risk management by exploiting large ground deformation datasets

Marta Béjar-Pizarro1, Pablo Ezquerro1, Carolina Guardiola-Albert1, Héctor Aguilera Alonso1, Margarita Patricia Sanabria Pabón1, Oriol Monserrat2, Anna Barra2, Cristina Reyes-Carmona1, Rosa Maria Mateos1, Juan Carlos García López Davalillo1, Juan López Vinielles1, Guadalupe Bru1, Roberto Sarro1, Jorge Pedro Galve3, Roberto Tomás4, Virginia Rodríguez Gómez1, Joaquín Mulas de la Peña1, and Gerardo Herrera1
Marta Béjar-Pizarro et al.
  • 1Geohazards InSAR laboratory and Modelling group (InSARlab), Geological Survey of Spain (IGME-CSIC), Ríos Rosas 23, 28003 Madrid, Spain; (m.bejar@igme.es, g.bru@igme.es ; p.ezquerro@igme.es ; c.guardiola@igme.es, rm.mateos@igme.es, c.reyes@igme.es, r.sarr
  • 2Centre Tecnològic de Telecomunicacions de Catalunya (CTTC/CERCA), Geomatics Division, Avinguda Carl Friedrich Gauss 7, 08860 Castelldefels, Spain, (abarra@cttc.cat; omonserrat@cttc.cat)
  • 3Departamento de Geodinámica, Universidad de Granada, Avda. del Hospicio, s/n, 18010 Granada, Spain (jpgalve@gmail.com)
  • 4Departamento de Ingeniería Civil. Universidad de Alicante, Alicante, Spain (roberto.tomas@ua.es)

The detection of areas of the Earth’s surface experiencing active deformation processes and the identification of the responsible phenomena (e.g. landslides activated after rainy events, subsidence due to groundwater extraction in agricultural areas, consolidation settlements, instabilities in active or abandoned mines) is critical for geohazard risk management and ultimately to mitigate the unwanted effects on the affected populations and the environment.

This will now be possible at European level thanks to the Copernicus European Ground Motion Service (EGMS), which will provide ground displacement measurements derived from time series analyses of Sentinel-1 data, using Interferometric Synthetic Aperture Radar (InSAR). The EGMS, which will be available to users in the first quarter of 2022 and will be updated annually, will be especially useful to identify displacements associated to landslides, subsidence and deformation of infrastructure.  To fully exploit the capabilities of this large InSAR datasets, it is fundamental to develop automatic analysis tools, such as machine learning algorithms, which require an InSAR-derived deformation database to train and improve them.  

Here we present the preliminary InSAR-derived deformation database developed in the framework of the SARAI project, which incorporates the previous InSAR results of the IGME-InSARlab and CTTC teams in Spain. The database contains classified points of measurement with the associated InSAR deformation and a set of environmental variables potentially correlated with the deformation phenomena, such as geology/lithology, land-surface slope, land cover, meteorological data, population density, and inventories such as the mining registry, the groundwater database, and the IGME’s land movements database (MOVES). We discuss the main strategies used to identify and classify pixels and areas that are moving, the covariables used and some ideas to improve the database in the future. This work has been developed in the framework of project PID2020-116540RB-C22 funded by MCIN/ AEI /10.13039/501100011033 and e-Shape project, with funding from the European Union’s Horizon 2020 research and innovation program under grant agreement 820852.

How to cite: Béjar-Pizarro, M., Ezquerro, P., Guardiola-Albert, C., Aguilera Alonso, H., Sanabria Pabón, M. P., Monserrat, O., Barra, A., Reyes-Carmona, C., Mateos, R. M., García López Davalillo, J. C., López Vinielles, J., Bru, G., Sarro, R., Galve, J. P., Tomás, R., Rodríguez Gómez, V., Mulas de la Peña, J., and Herrera, G.: Building an InSAR-based database to support geohazard risk management by exploiting large ground deformation datasets, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7308, https://doi.org/10.5194/egusphere-egu22-7308, 2022.