Orals

NP4.3
Big data and machine learning in geosciences 

This session aims to bring together researchers working with big data sets generated from monitoring networks, extensive observational campaigns and detailed modeling efforts across various fields of geosciences. Topics of this session will include the identification and handling of specific problems arising from the need to analyze such large-scale data sets, together with methodological approaches towards semi or fully automated inference of relevant patterns in time and space aided by computer science-inspired techniques. Among others, this session shall address approaches from the following fields:
• Dimensionality and complexity of big data sets
• Data mining in Earth sciences
• Machine learning, including deep learning and other advanced approaches
• Visualization and visual analytics of big data
• Informatics and data science
• Emerging big data paradigms, such as datacubes

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Co-organized as AS5.20/CL5.25/ESSI2.3/GD8.5/HS3.5/NH11.11/SM7.8
Convener: Mikhail Kanevski | Co-conveners: Peter Baumann, Sandro Fiore, Kwo-Sen Kuo, Nicolas Younan
Orals
| Mon, 08 Apr, 10:45–12:30, 14:00–18:00
 
Room L3
Posters
| Attendance Tue, 09 Apr, 10:45–12:30
 
Hall X4

Monday, 8 April 2019 | Room L3

Chairperson: Nicolas Younan, Mikhail Kanevski
10:45–11:00 |
EGU2019-1659
Users of Big Earth Data in the spotlight - A user perspective on current and future cloud-based data systems
Julia Wagemann, Stephan Siemen, Jörg Bendix, and Bernhard Seeger
11:00–11:15 |
EGU2019-11094
Alternative Earth Science Datasets For Identifying Patterns and Events
Kaylin Bugbee, Robert Griffin, Brian Freitag, Jeffrey Miller, Rahul Ramachandran, and Jia Zhang
11:15–11:30 |
EGU2019-10177
Object Segmentation for Identification of Soil Erosion Sites in Swiss Alpine Grasslands with Neural Networks
Maxim Samarin and Volker Roth
11:30–11:45 |
EGU2019-18732
Performance of a Real-Time Machine Learning Based Seismic Catalog Generator Over a One Year Period in Production
Sepideh Karimi, Andrew Reynen, and Dario Baturan
11:45–12:00 |
EGU2019-10697
Complexity and connectivity variability in the climate of the past
Fabrizio Falasca, Julien Cretat, Pascale Braconnot, and Annalisa Bracco
12:00–12:15 |
EGU2019-8842
Atmospheric boundary layer classification with unsupervised learning from field campaign data
Thomas Rieutord, Alexandre Paci, and Alain Dabas
12:15–12:30 |
EGU2019-11238
Classification of Atmospheric Meteorological Events by a supervised machine learning
Anton Sokolov, Egor Dmitriev, Hervé Delbarre, and Cyril Gengembre
Lunch break
Chairperson: Sandro Fiore, Mikhail Kanevski
14:00–14:15 |
EGU2019-12798
Machine learning methods for predicting energy demand/production based on hydro-meteorological input
Konrad Bogner and Massimiliano Zappa
14:15–14:30 |
EGU2019-4221
Denoising Autoencoder and Anomaly Detection-Based Method to Automatically Looking for Changes on Martian Image Pairs
Alfiah Rizky Diana Putri, Panagiotis Sidiropoulos, and Jan-Peter Muller
14:30–14:45 |
EGU2019-9134
Deep Learning of Geological Structures in 3-D Seismic Reflection Data
Thilo Wrona, Indranil Pan, Rebecca Bell, Haakon Fossen, and Rob Gawthorpe
14:45–15:00 |
EGU2019-16256
| Highlight
Big data and machine learning in the bioeconomy sector: preliminary results from the Norwegian case
Jonathan Rizzi, Ingvild Nystuen, Misganu Debella-Gilo, Nils Egil Søvde, and Eva Solbjørg Flo Heggem
15:00–15:15 |
EGU2019-12541
Near Surface Ozone Predictions Based on Multiple Artificial Neural Network Architectures
Felix Kleinert, Bing Gong, Markus Götz, and Martin Georg Schultz
15:15–15:30 |
EGU2019-17539
Clustering of the Polar Vortex states using deep convolutional neural networks
Natalia Tilinina, Mikhail Krinitskiy, Yulia Zyulyaeva, and Sergey Gulev
15:30–15:45 |
EGU2019-4410
Evaluating aleatoric and epistemic uncertainties of time series deep learning models for soil moisture predictions
Kuai Fang, Chaopeng Shen, and Daniel Kifer
Coffee break
Chairperson: Kwo-Sen Kuo, Mikhail Kanevski
16:15–16:30 |
EGU2019-15318
Causal inference in Geosciences with multidimensional kernel deviance measures
Emiliano Diaz Salas Porras, Adrian Perez Suay, Valero Laparra, and Gustau Camps Valls
16:30–16:45 |
EGU2019-12085
| presentation
Detecting geophysical signals and sources with large-scale network data
Catherine de Groot-Hedlin and Michael Hedlin
16:45–17:00 |
EGU2019-10411
Data-assisted reduced-order modeling of climate dynamics
Themis Sapsis, Zhong Yi Wan, Boyko Dodov, Henk Dijkstra, and Christian Lessig
17:00–17:15 |
EGU2019-10543
Prediction of daily maximum ozone threshold exceedances by preprocessing and ensemble artificial intelligence techniques
Bing Gong, Martin G. Schultz, and Felix Kleinert
17:15–17:30 |
EGU2019-3424
Automated point cloud classification and analysis of rock slope processes using machine learning
Luke Weidner, Gabriel Walton, and Ryan Kromer
17:30–17:45 |
EGU2019-11185
A data-centric Bayesian learning framework and the outlook for a deep-learning-powered avenue for hydrologic knowledge discovery
Chaopeng Shen, Wen-Ping Tsai, and Kuai Fang
17:45–18:00 |
EGU2019-14074
| Highlight
A Topography of Climate Change Research
Max Callagan