Daniel Fernandez

Ico_CTTC

Geomatics (GM)

Phd , Researcher

Phone: +34 936 45 29 00

Daniel Fernández holds a PhD in Theoretical Physics from the University of Barcelona (2013). During the early stages of his career, his research focused on the gauge/gravity duality; a conjecture related to the emergence of spacetime in a quantum gravity setting. His first works contributed to the evidence in favor of such a duality existing for the chromodynamics of the Standard Model. This was accomplished through the theoretical analysis of the quark-gluon plasma created in heavy ion collisions experiments.

Later research avenues in his career took him into number theory, specifically the structure of the prime numbers, and into the study of quantum critical fluids.

Since 2021 he has expanded the scope of his studies, using his expertise on mathematical modelling to develop classification algorithms to use on remote sensing data from Sentinel-2 that would result on a quantitative map of soil erosion risk for Iceland. This project resulted in the establishment of the start-up Fléttan , with funding from Rannís, the Icelandic Centre for Research. In February 2023, he joined the Geomatics Division of CTTC as researcher, involved in the PROMETEO project.

His current work for Fléttan has produced a reliable, widely applicable and cost-effective method to classify Icelandic and, by extension, Arctic soils into different categories of erosion risk. This was accomplished through a partnership with Landgræðslan, the Soil Conservation Service of Iceland.

His work at CTTC involves the improvement of analysis methods for the monitoring of highly dynamic areas, addressing one of the main technical limitations of Persistent Scatterer Interferometry (PSI): the spatially discontinuous nature of persistent scatterers (PS) on the ground, which in many cases are undersampled.

In order to monitor and analyze ground displacements, it’s crucial to derive coherent and precise displacement maps from these individual points. Adaptive filtering and interpolation algorithms play an indispensable role in this context. They are used to fill the gaps between the sparse PS points, generating a continuous displacement field that provides a comprehensive view of the deformation phenomenon under observation. Daniel’s work is focused on deriving detailed and more visually coherent displacement maps, enabling a better understanding of the underlying geophysical processes and facilitating more informed decision-making in areas like urban planning, hazard assessment, and infrastructure maintenance.

He has authored or co-authored 18 publications in various journals concerning the previous topics, given 12 presentations at international conferences, and co-advised 2 MSc students. He also has an extensive teaching experience over the course of 8 years on 5 different courses of the Physics and Mathematics degrees, as well as 2 graduate courses of the Elite Master Course “Theoretical and Mathematical Physics” in Munich, Germany.

ORCID: https://orcid.org/0000-0002-6896-1006

INSPIRE: https://inspirehep.net/authors/1202719

LinkedIn: https://www.linkedin.com/in/daniel-fern%C3%A1ndez-48b877180/

Relevant publications:

  • D. Fernández, E. Adermann, M. Pizzolato, R. Pechenkin, C. G. Rodríguez & A. Taravat, “Comparative Analysis of Machine Learning Algorithms for Soil Erosion Modelling Based on Remotely Sensed Data”, Remote Sens. 15, 482 (2023) [https://doi.org/10.3390/rs15020482].
  • D. Fernández, E. Adermann, M. Pizzolato, R. Pechenkin & C. G. Rodríguez, “Remote mapping of soil erosion risk in Iceland”. Oral presentation at the FOSS4G conference at the University of Florence, Italy (Aug 2022), published in Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci. XLVIII-4/W1-2022, 135–141 (2022) [https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-135-2022].

Projects:

Project Title: Fléttan Earth Observation EHF.
Funding agency: Icelandic Research Fund (Rannís), Reference/code: 2215789-0611
Amount: 13,029.29 euros
Years: Nov 2022 – Nov 2023
Project manager: Christina Guadalupe Rodríguez
Grant type: Business grant Seed [https://www.rannis.is/frettir/taeknithrounarsjodur/voruthlutun-taeknithrounarsjods-2022]

There are no related projects.

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