Roberto Tomás

Dr. Roberto Tomás

Departamento de Ingeniería Civil, Universidad de Alicante, Ap. Correos 99, 03080, Alacant/Alicante, Spain
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Research Focus & Metrics

Academic Career Length

28Years (1999-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2021 in Science
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Journal Article
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Gerardo HerreraGerardo Herrera
Gerardo Herrera
PEPablo Ezquerro
Pablo Ezquerro
Roberto TomásRoberto Tomás
Roberto Tomás
MBMarta Bejar-Pizarro
Marta Bejar-Pizarro
JLJuan López-Vinielles
Juan López-Vinielles
SYShujun Ye
Shujun Ye
Nineteen percent of the global population may face a high probability of subsidence

1 July 2014 in Computers & Geosciences
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Journal Article
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Adrian RiquelmeAdrian Riquelme
Adrian Riquelme
Abellan AntonioAbellan Antonio
Abellan Antonio
Roberto TomásRoberto Tomás
Roberto Tomás
Michel JaboyedoffMichel Jaboyedoff
Michel Jaboyedoff

1 December 2013 in Engineering Geology
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VBV. Brotóns
V. Brotóns
Roberto TomásRoberto Tomás
Roberto Tomás
Salvador IvorraSalvador Ivorra
Salvador Ivorra
JAJ.C. Alarcón
J.C. Alarcón

2 June 2016 in Remote Sensing
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MCMi Chen
Mi Chen
Roberto TomásRoberto Tomás
Roberto Tomás
Zhenhong LiZhenhong Li
Zhenhong Li
Mahdi MotaghMahdi Motagh
Mahdi Motagh
TLTAO LI
TAO LI
XGXulong Gong
Xulong Gong
Beijing is one of the most water-stressed cities in the world. Due to over-exploitation of groundwater, the Beijing region has been suffering from land subsidence since 1935. In this study, the Small Baseline InSAR technique has been employed to process Envisat ASAR images acquired between 2003 and 2010 and TerraSAR-X stripmap images collected from 2010 to 2011 to investigate land subsidence in the Beijing region. The maximum subsidence is seen in the eastern part of Beijing with a rate greater than 100 mm/year. Comparisons between InSAR and GPS derived subsidence rates show an RMS difference of 2.94 mm/year with a mean of 2.41 ± 1.84 mm/year. In addition, a high correlation was observed between InSAR subsidence rate maps derived from two different datasets (i.e., Envisat and TerraSAR-X). These demonstrate once again that InSAR is a powerful tool for monitoring land subsidence. InSAR derived subsidence rate maps have allowed for a comprehensive spatio-temporal analysis to identify the main triggering factors of land subsidence. Some interesting relationships in terms of land subsidence were found with groundwater level, active faults, accumulated soft soil thickness and different aquifer types. Furthermore, a relationship with the distances to pumping wells was also recognized in this work.

1 December 2016 in Remote Sensing of Environment
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Keren DaiKeren Dai
Keren Dai
Zhenhong LiZhenhong Li
Zhenhong Li
Roberto TomásRoberto Tomás
Roberto Tomás
GLGuoxiang Liu
Guoxiang Liu
BYBing Yu
Bing Yu
JSJulia Stockamp
Julia Stockamp
The Daguangbao mega-landslide (China), induced by the 2008 Wenchuan earthquake (Mw = 7.9), with an area of approximately 8 km2, is one of the largest landslides in the world. Experts predicted that the potential risk and instability of the landslide might remain for many decades, or even longer. Monitoring the activity of such a large landslide is hence critical. Terrain Observation by Progressive Scans (TOPS) mode from the Sentinel-1 satellite provides us with up-to-date high-quality Synthetic Aperture Radar (SAR) images over a wide ground coverage (250 × 250 km), enabling full exploitation of various InSAR applications. However, the TOPS mode introduces azimuth-dependent Doppler variations to radar signals, which requires an additional processing step especially for SAR interferometry. Sentinel-1 TOPS data have been widely applied to earthquakes, but the performance of TOPS data-based time series analysis requires further exploitation. In this study, Sentinel-1 TOPS data were employed to investigate landslide post-seismic activities for the first time. To deal with the azimuth-dependent Doppler variations, a processing chain of TOPS time series interferometry approach was developed. Since the Daguangbao landslide is as a result of the collapse of a whole mountain caused by the 2008 Mw 7.9 Wenchuan earthquake, the existing Digital Elevation Models (DEMs, e.g. SRTM and ASTER) exhibit height differences of up to approximately 500 m. Tandem-X images acquired after the earthquake were used to generate a high resolution post-seismic DEM. The high gradient topographic errors of the SRTM DEM (i.e. the differences between the pre-seismic SRTM and the actual post-seismic elevation), together with low coherence in mountainous areas make it difficult to derive a precise DEM using the traditional InSAR processing procedure. A re-flattening iterative method was hence developed to generate a precise TanDEM-X DEM in this study. The volume of the coseismic Daguangbao landslide was estimated to be of 1.189 ± 0.110 × 109 m3 by comparing the postseismic Tandem-X DEM with the preseismic SRTM DEM, which is consistent with the engineering geological survey result. The time-series results from Sentinel-1 show that some sectors of the Daguangbao landslide are still active (and displaying four sliding zones) and exhibiting a maximum displacement rate of 8 cm/year, even eight years after the Wenchuan earthquake. The good performance of TOPS in this time series analysis indicates that up-to-date high-quality TOPS data with spatiotemporal baselines offer significant potential in terms of future InSAR applications.This work was supported by the National Natural Science Foundation of China under Grant No. 41474003. The research stay of Dr. Tomás at Newcastle University was funded by the Ministry of Education, Culture and Sport within the framework of Project PRX14/00100. Additional funding was obtained from the Spanish Government under projects TIN2014-55413-C2-2-P and ESP2013-47780-C2-2-R. Part of this work is also supported by the UK Natural Environmental Research Council (NERC) through the Centre for the Observation and Modelling of Earthquakes, Volcanoes and Tectonics (COMET, ref.: come30001) and the LICS and CEDRRiC projects (ref. NE/K010794/1 and NE/N012151/1, respectively), the ESA-MOST DRAGON-3 projects (ref. 10607 and 10665), the ESA-MOST DRAGON-4 project (ref. 32244) and the Open Fund from the Key Laboratory of Earth Fissures Geological Disaster, Ministry of Land and Resources (ref.: gla2013001)

11 February 2020 in IEEE Geoscience and Remote Sensing Magazine
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KDKeren Dai
Keren Dai
Zhenhong LiZhenhong Li
Zhenhong Li
QXQiang Xu
Qiang Xu
RBRoland Burgmann
Roland Burgmann
DMDavid G. Milledge
David G. Milledge
JLJingnan Liu
Jingnan Liu