What is he best known for?
The fields of study he is best known for:
- Geophysics
- Plate tectonics
- Mathematical analysis
Ramón Carbonell mainly focuses on Seismology, Tectonics, Reflection, Lithosphere and Crust.
His research investigates the connection between Tectonics and topics such as Massif that intersect with problems in Geomorphology, Imbrication, Induced seismicity, Mediterranean climate and Peninsula.
His study in Reflection is interdisciplinary in nature, drawing from both Amplitude, Mohorovičić discontinuity and Core.
Within one scientific family, Ramón Carbonell focuses on topics pertaining to Root under Mohorovičić discontinuity, and may sometimes address concerns connected to Petrology.
His studies in Lithosphere integrate themes in fields like Slab, Mantle and Continental margin.
Ramón Carbonell works mostly in the field of Crust, limiting it down to concerns involving Mafic and, occasionally, Carboniferous and Paleozoic.
His most cited work include:
- Crustal structure of the transpressional Variscan orogen of SW Iberia: SW Iberia deep seismic reflection profile (IBERSEIS) (200 citations)
- TOPO-EUROPE: the geoscience of coupled deep earth-surface processes (102 citations)
- Crustal Root Beneath the Urals: Wide-Angle Seismic Evidence (79 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Seismology, Crust, Reflection, Geophysics and Lithosphere.
His Seismology research includes themes of Seismic tomography, Mantle and Peninsula.
His Crust research is multidisciplinary, relying on both Seismic wave, Seismic refraction, Mohorovičić discontinuity and Transect.
The study incorporates disciplines such as Massif and Continental margin in addition to Lithosphere.
His research in Massif focuses on subjects like Fracture, which are connected to Fault and Borehole.
He has included themes like Discontinuity, Mafic and Paleozoic in his Tectonics study.
He most often published in these fields:
- Seismology (51.28%)
- Crust (20.94%)
- Reflection (14.96%)
What were the highlights of his more recent work (between 2018-2021)?
- Seismology (51.28%)
- Paleontology (11.54%)
- Geophysical imaging (7.26%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Seismology, Paleontology, Geophysical imaging, Reflection and Massif.
His work in Seismology addresses issues such as Depth sounding, which are connected to fields such as Library science.
His work in Paleontology covers topics such as Reflectivity which are related to areas like Mantle.
His Reflection study combines topics in areas such as Seismic processing, Tectonics, Peninsula and Geophone.
His Tectonics research focuses on subjects like Induced seismicity, which are linked to Seismic hazard.
He combines subjects such as Seismic modeling, Discontinuity and Crust with his study of Massif.
Between 2018 and 2021, his most popular works were:
- Seismometers Within Cities: A Tool to Connect Earth Sciences and Society (8 citations)
- Using seismic attributes in seismotectonic research: an application to the Norcia M w = 6.5 earthquake (30 October 2016) in central Italy (6 citations)
- Lithospheric image of the Central Iberian Zone (Iberian Massif) using global-phase seismic interferometry (5 citations)
In his most recent research, the most cited papers focused on:
- Geophysics
- Plate tectonics
- Mathematical analysis
His primary areas of investigation include Seismology, Paleontology, Lithosphere, Multidisciplinary approach and Reflection.
His Seismology study frequently links to other fields, such as Depth sounding.
His Lithosphere study often links to related topics such as Intraplate earthquake.
His studies deal with areas such as Tectonics, Active fault, Seismic attribute and Geophone as well as Reflection.
His Structural geology study incorporates themes from Seismic tomography, Inversion and Lithology.
His Foreland basin study integrates concerns from other disciplines, such as Massif, Imbrication and Crust.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
