Automatic Classification of Active Deformation Areas Based on Synthetic Aperture Radar Data and Environmental Covariates Using Machine Learning—Application in SE Spain-Reference-Cited by-同舟云学术

Automatic Classification of Active Deformation Areas Based on Synthetic Aperture Radar Data and Environmental Covariates Using Machine Learning—Application in SE Spain

Published:2023-12-29 Issue: Volume:382 Page:15
ISSN:
Container-title:IV Conference on Geomatics Engineering
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Author:

Rivera-Rivera Jhonatan¹²^ORCID,Béjar-Pizarro Marta²^ORCID,Aguilera Héctor²^ORCID,Guardiola-Albert Carolina²^ORCID,Husillos César²,Ezquerro Pablo²^ORCID,Barra Anna³,Mateos Rosa María²^ORCID,Cuevas-González María³,Sarro Roberto²^ORCID,Monserrat Oriol³^ORCID,Martínez-Corbella Mónica²^ORCID,Crosetto Michele³,López-Vinielles Juan²^ORCID

Affiliation:

1. ETSI Topografía, Geodesia y Cartografía, Universidad Politécnica de Madrid (UPM), 28031 Madrid, Spain

2. Geological Survey and Mining Institute of Spain (CN IGME-CSIC), Rios Rosas 23, 28003 Madrid, Spain

3. Geomatics Research Unit, Centre Tecnológic Telecomunicacions Catalunya (CTTC/CERCA), 08860 Castelldefels, Spain

Publisher

MDPI

Link

https://www.mdpi.com/2673-4931/28/1/15/pdf

Reference6 articles.

1. Bonì, R., Pilla, G., and Meisina, C. (2016). Methodology for Detection and Interpretation of Ground Motion Areas with the A-DInSAR Time Series Analysis. Remote Sens., 8.

2. Barra, A., Solari, L., Béjar-Pizarro, M., Monserrat, O., Bianchini, S., Herrera, G., Crosetto, M., Sarro, R., González-Alonso, E., and Mateos, R.M. (2017). A Methodology to Detect and Update Active Deformation Areas Based on Sentinel-1 SAR Images. Remote Sens., 9.

3. Ground motion areas detection (GMA-D): An innovative approach to identify ground deformation areas using the SAR-based displacement time series;Meisina;Proc. IAHS,2020

4. Navarro, J.A., Cuevas, M., Barra, A., and Crosetto, M. (2018, January 24–27). Detection of Active Deformation Areas based on Sentinel-1 imagery: An efficient, fast and flexible implementation. Proceedings of the 18th International Scientific and Technical Conference, Crete, Greece.

5. Tomás, R., Pagán, J.I., Navarro, J.A., Cano, M., Pastor, J.L., Riquelme, A., Cuevas-González, M., Crosetto, M., Barra, A., and Monserrat, O. (2019). Semi-Automatic Identification and Pre-Screening of Geological–Geotechnical Deformational Processes Using Persistent Scatterer Interferometry Datasets. Remote Sens., 11.