Posters

ESSI2.10

The evolution of data acquisition systems has enabled increasing data quality and the volume of information to be analyzed, processed and interpreted. Nowadays, there has been a growing interest in the geophysical time series and image processing analysis in all most disciplines relates to Earth Sciences, such as Seismology, Geochemistry, Geodesy, Volcanology, Geology and Satellite Observations.
A major challenge that arises is how to structure and organize the huge amount of data and to determine the type of information that could help the scientific community for a deeper knowledge on the complex dynamics of geophysical and geochemical systems in our Planet.
The high volume of data recorded by those systems requires an appropriate framework that can enhance classical approaches by exploiting the latent knowledge embedded in the data. New rising methodologies have to tackle the long-term problems of data management, accessibility and deployment. Data Mining, Cloud Computing and Machine Learning are the most appropriate disciplines for the analysis of such high throughput data.
In this session, we welcome contributions focused on recent machine learning advances applied to Earth and planetary sciences, with a focus on remote sensing techniques and early warning systems. This is a highly interdisciplinary session, where artificial intelligence is combined with Earth sciences techniques in order to improve the knowledge of the complexity of our Planet.
This session is partially sponsored by the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 798480, and by Government of Spain through the research project TEC2015-814 68752.

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Convener: Luciano Zuccarello | Co-conveners: Carmen Benitez, Angel Bueno Rodriguez, Simona Scollo, Manuel Titos Luzon
Posters
| Attendance Tue, 09 Apr, 14:00–15:45
 
Hall X1

Attendance time: Tuesday, 9 April 2019, 14:00–15:45 | Hall X1

Chairperson: Luciano Zuccarello
X1.65 |
EGU2019-41
| Highlight
Melanie Brandmeier and Yuanze Chen
Hall X1
X1.66 |
EGU2019-42
| Highlight
Zayd Hamdi, Melanie Brandmeier, and Christoph Straub
Hall X1
X1.67 |
EGU2019-1865
| Highlight
Patrice Carbonneau, Toby Breckon, James Dietrich, Stephen Dugdale, Mark Fonstad, Hitoshi Miyamoto, and Amy Woodget
Hall X1
Hall X1
X1.69 |
EGU2019-10644
| Highlight
Luciano Zuccarello, Luz García Martínez, Isaac Alvarez, María Carmen Benitez, Manuel Titos, Angel Bueno, Janire Prudencio, and Jesus Ibanez
Hall X1
X1.70 |
EGU2019-11386
| Highlight
Guillermo Cortés, Roberto Carniel, Philippe Lesage, M. Ángeles Mendoza, and Ivo Della Lucia
Hall X1
X1.71 |
EGU2019-13759
| Highlight
Luz García, Luciano Zucarello, Isaac Álvarez, Carmen Benítez, Arianna Cuius, Manuel Titos, Angel Bueno, Sonia Mota, Janire Prudencio, and Jesús Ibáñez
Hall X1
X1.72 |
EGU2019-14560
| Highlight
Bouwe Andela, Berend Weel, Elena Ranguelova, Niels Drost, Maximilian Filtenborg, Derk Barten, Debraj Roy, and Mike Lees
Hall X1
X1.73 |
EGU2019-15461
| Highlight
Manuel Titos, Ángel Bueno, Luz García, Luciano Zuccarello, Isaac Álvarez, Jesús Ibañez, and Carmen Benítez
Hall X1
X1.74 |
EGU2019-15770
| Highlight
Araceli García Yeguas, Luz García, Carmen Benítez, Sonia Mota, and Jesús M. Ibáñez
Hall X1
X1.75 |
EGU2019-16873
| Highlight
Javhar Aminov, Chen Xi, Bao Anming, Jovid Aminov, Yunus Mamadjanov, and Latipa Tuerhanjiang
Hall X1
X1.76 |
EGU2019-17897
| Highlight
Antonio Mora, Gustavo Romero, Carmen Benítez, Manuel Titos, Sonia Mota, and Isaac Álvarez
Hall X1
X1.77 |
EGU2019-18882
| Highlight
Anna Wawrzaszek, Małgorzata Jenerowicz, Wojciech Drzewiecki, Michał Krupiński, and Sebastian Aleksandrowicz