ESA-ECMWF Workshop 2021 Machine Learning for Earth System Observation and Prediction
Posters
| Incorporating Spatial Information Into Ensemble Post-processing via Autoencoder Neural Networks Sebastian Lerch (Karlsruhe Institute Of Technology), Kai Polsterer (Heidelberg Institute for Theoretical Studies) |
| Self-supervised methods for joint SAR and multispectral land cover mapping Antonio Montanaro (Politecnico Di Torino),Diego Valsesia (Politecnico di Torino), Giulia Fracastoro (Politecnico di Torino), Enrico Magli (Politecnico di Torino) |
| Machine Learning Methods for Postprocessing Ensemble Forecasts of Wind Gusts: A Systematic Comparison Benedikt Schulz (Karlsruhe Institute of Technology), Sebastian Lerch (Karlsruhe Institute of Technology) |
| Comparing the significance of new data products from satellites containing night-time light and day-time aerosol information for air quality Prediction Ankit Didwania (Gujarat Technological University), Vibha Patel (Gujarat Technological University) |
| Improvement of Ku-band Winds in Rainy Regions Obtained by a Support Vector Machine Method Xingou Xu (National Space Science Center, Chinese Academy of Sciences), Ad Stoffelen (Royal Netherlands Meteorological Institute) |
| S2S-Forecasting of Central European Winter Temperature Based on Quantile Random Forests Selina Kiefer Karlsruhe (Institute For Technology) |
| Automated Polynya Identification Tool (APIT) James Hickson (ARGANS), Estrella Olmedo (Barcelona Expert Centre), Verónica Gonzalez (Barcelona Expert Centre), Diego Fernández (ESA) |
| Feasibility Study of Real Time Oil Spill Tracking, Exploiting Dedicated AI On-Board Satellite Gianluca Giuffrida (University Of Pisa), Lorenzo Diana (University of Pisa), Pietro Nannipieri (University of Pisa), Luca Fanucci (University Of Pisa) |
| Multivariate Ensemble Post-Processing Using Generative Machine Learning Methods Jieyu Chen (Karlsruhe Institute Of Technology), Sebastian Lerch (Karlsruhe Institute Of Technology) |
| Prediction of Ocean Driven Antarctic Ice Shelf Melting Using Machine Learning Sebastian Rosier (Northumbria University), Christopher Bull (Northumbria University) |
| Estimating Industrial Greenhouse Gas Emissions from Satellite Imagery Joëlle Hanna (University of St Gallen), Michael Mommert (University of St Gallen), Damian Borth (University of St Gallen) |
| Post-Processing of NWP Model Output by Machine Learning Algorithms for Severe Weather Forecasting Antonio Vocino (COMET - Italian Air Force Meteorological Centre), Francesca Marcucci (COMET - Italian Air Force Meteorological Centre), Raffaele Golino (Geo-K), Fabio Del Frate (Tor Vergata University) |
| AiTLAS: Artificial Intelligence Toolbox for Earth Observation Dragi Kocev (Jozef Stefan Institute), Ivica Dimitrovski (Bias Variance Labs, Jozef Stefan Institute), Ivan Kitanovski (Bias Variance Labs, Jozef Stefan Institute), Panče Panov (Jozef Stefan Institute, Bias Variance Labs), Nikola Simidjievski (Bias Variance Labs, University of Cambridge) |
| Combining Airborne LiDAR and Sentinel-2 Data for the Classification of Amazonian Secondary Forests and Calculation of Carbon Stocks in different Successional Stages Leonard Pfaff (Karlsruher Institut Für Technologie), Yhasmin Mendes de Moura (Karlsruher Institut Für Technologie), Fabian Faßnacht (Karlsruher Institut Für Technologie), Camila Silva (IPAM), Ricardo Dalagnol (INPE), Lenio Galvao (INPE) |
| Deep Learning in Space: The Big Data Problems or Big Problems with Data? Jakub Nalepa (KP Labs) |
| Deep Learning weather uncertainty quantification for EO satellite mission planning Jonathan Guerra (Airbus Defence & Space), Mathieu Picard (Airbus Defence & Space) |
| Digital Mapping of Soil Organic Matter Using Open Source Accessible Products of ESA® in Arable Plain Fuat Kaya (Isparta University Of Applied Sciences Faculty Of Agriculture Department Of Soil Science And Plant Nutrition), Levent BAŞAYİĞİT (Isparta University Of Applied Sciences Faculty Of Agriculture Department Of Soil Science And Plant Nutrition) |
| Enhancing the Maritime Monitoring by Deep Learning Maria Daniela Graziano (University of Naples Federico II), Roberto Del Prete (University of Naples Federico II), Alfredo Renga (University of Naples Federico II) |
| Satellite Tracking & Monitoring using Orbitshub ACCAT Systems Divya Krishnamoorthy (Orbitshub) |
| AI Ecosystem for Energy Meteorology, Optimization of Renewable Energy Applications and Power Forecasts Anton Kaifel (ZSW), Martin Felder (ZSW), Frank Sehnke (ZSW), Linda Menger (ZSW), Kay Ohnmeiß (ZSW) |
| High-resolution soil moisture retrieval from remote sensing microwave observations Grigorios Tsagkatakis (Forth), Mahta Moghaddam (University of Southern California), Panagiotis Tsakalides (Forth) |
| FloodSENS: Flood Segmentation in Partially Clouded Optical Satellite Images Ben Gaffinet (RSS-Hydro), Ron Hagensieker (osir.io), Laura Giustarini (RSS-Hydro), Guy Schumann (RSS-Hydro) |
| Training Dataset Requirements for Cloud Masking Carsten Brockmann (Brockmann Consult GmbH), Jan Wevers (Brockmann Consult GmbH) |
| Daily to Sub-daily precipitation downscaling based on multiple datasets using artificial neural networks in Brazil Rogerio Batista (Inpe), Alan Calheiros (Inpe) |
| Intelligent Dashboard of the Celestial Meteor CAMS Data Julia Nguyen (SpaceML), Chicheng Ren |
| Assessment of Methane Mitigation Potential of Large Oil and Gas Leaks Clément Giron (Kayrros), Thomas Lauvaux (University de Saclay), Alexandre D'Aspremont (Kayrros, CNRS), Riley Duren (University of Arizona, Carbon Mapper) Daniel Cusworth (Jet Propulsion Laboratory) |
| It's a Bird, It's a Plane, It's a Meteor! Surya Ambardar (Student), Siddha Ganju (NVIDIA), Peter Jenniskens (SETI Institute) |
| Satellite Image Simulation by Neural Networks Based on RTTOV Radiative Transfer Model Tom Cocogne (French Satellite Meteorology Research Centre) |
| Humanitarian Disaster Assistance Informed by White Box Earth Observation-based Machine Learning Algorithms Thomas Chen (Academy For Mathematics, Science, And Engineering) |
| Spatio-temporal climate extremes – semi-supervised detection with a deep autoencoder Albrecht Schall (Max Planck Institute for Biogeochemistry) |