Encarni Medina-Lopez
Published: 7 May 2019
#Coastal engineering; #Marine energy; #satellite remote sensing; #water-energy-environment trilemma; #Oceanography
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School/College |
School of Engineering / The University of Edinburgh |
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emedina@ed.ac.uk |
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Telephone |
0131 650 5642 |
Research vision
My research focuses on the use of remote sensing to tackle the water-energy-environment trilemma. I am also interested in studying the interaction of marine energy converters and the ocean, as well as the relationship between these, social and environmental factors, and the built environment.
At present, I am using satellite data, in situ measurements, and machine learning techniques to investigate processes modelling the coastal environment. More specifically, I am developing deep neural networks to estimate ocean temperature and salinity from optical satellites (i.e. ocean colour). My research focuses on the use of high-resolution imagery, allowing for the obtention of accurate oceanographic parameters. I am also extending this research to the application on the coastal boundary. A common problem for remote sensing is the accurate estimation of the coastal boundaries. With the use of numerical models and neural networks it would be possible to calculate erosion onset in the coast and use that information to calibrate results from satellite imagery.
Expectations from collaboration
I am looking for expertise in environmental modelling, either analytical, numerical or experimental. I have particular interest in the areas of Environmental Hydraulics and Coastal Engineering. I would also appreciate people with expertise in social/economic impacts on the natural and built environment.
Key Skills
- Numerical modelling (CFD),
- machine learning,
- remote sensing
First published: 7 May 2019
