2^ndEDITION

Please find here all the information on the 2^nd edition.

Agenda

	Monday, 15 November
10:30-10:45	Welcome and introduction ESA Pierre-Philippe Mathieu (ESA)
10:45-11:00	Welcome and introduction ECMWF Andy Brown (ECMWF)
	Keynote: ML for the ESOP - Setting the scene Chair: Rochelle Schneider (ESA)
11:00-11:45	Machine learning on the Earth System with remote sensing: towards machines that we can understand and interact with Keynote Speaker: Devis Tuia (EPFL)
11:45-12:30	Combining data assimilation and machine learning to extract more information from earth observations Keynote Speaker: Alan Geer (ECMWF)
12:30-14:00	Poster session
	Session 1.1: Enhancing Satellite Observation with ML Chair: Bertrand Le Saux (ESA)
14:00-14:30	Benefits and opportunities of Explainable Machine Learning in the environmental sciences Ribana Roscher (Technical University of Munich and University of Bonn)
14:30-15:00	Atmospheric Retrievals in a Machine Learning Context: A Radiometric Story Over the Ocean Mario Echeverri Bautista (KNMI)
15:00-15:30	Permutation invariance and uncertainty in multitemporal image super-resolution Diego Valsesia (Politecnico Di Torino)
15:30-16:00	Coffee Break
	Session 1.2: Enhancing Satellite Observation with ML Chair: Rochelle Schneider (ESA)
16:00-16:30	CNN-based Detection of Tiny Objects in Remote Areas UsingSpatiotemporal Earth Observation Data Roman Pflugfelder (TU Wien)
16:30-17:00	Estimate of XCO2 from OCO-2 Observations Using a Neural Network Approach Francois-Marie Breon (CEA/LSCE)
17:00-17:30	Autonomous Robotic Teams, Machine Learning, and the Next Generation of Earth Observing System David J Lary (Hanson Center for Space Sciences, University of Texas at Dallas)
	Tuesday, 16 November
	Session 1.3: Enhancing Satellite Observation with ML Chair: Begüm Demir (TU Berlin)
09:00-09:30	Free High Resolution Imagery - Open-Source Models and Package for Sentinel 2 Super-Resolution Julien Cornebise (UCL)
09:30-10:00	Deep Learning Implementations to Facilitate the Assimilation of Satellite Observations. A Case Study for LST and SST Using IASI Observations Eulalie Boucher (Lerma - Observatoire De Paris)
10:00-10:30	Machine Learning Techniques for Automated ULF Wave Recognition in Swarm Time Series Georgios Balasis (National Observatory of Athens)
10:30-11:00	Coffee Break
	Session 2.1: Hybrid Data Assimilation - ML Approaches Chair: Alan Geer (ECMWF)
11:00-11:30	Data Assimilation + Machine Learning = Data Learning Rossella Arcucci (Imperial College London)
11:30-12:00	Use of AI to facilitate the NWP assimilation of EOs: retrieval, radiative transfer and physical integration of satellite products Filipe Aires (CNRS)
12:00-12:30	Gaussian Assimilation of non-Gaussian Image Data via Pre-Processing by Variational Auto-Encoder (VAE) Daisuke Hotta (Japan Meteorological Agency)
12:30-13:00	Correcting model error with an online Artificial Neural Network Marcin Chrust (ECMWF)
13:00-14:00	Lunch break
	Session 2.2: Hybrid Data Assimilation - ML Approaches Chair: Rossella Arcucci (Imperial College London)
14:00-14:30	Model error correction with data assimilation and machine learning Alban Farchi (CEREA - ENPC)
14:30-15:00	Towards the Direct Assimilation of Scatterometer Backscatter Triplet Sean Healy (ECMWF)
15:00-15:30	Data-Driven Surrogate Model with Latent Data assimilation for Wildfire Forecasting Sibo Cheng (Imperial College London)
15:30-16:00	Coffee break
	Session 3.1: Geophysical Forecasting with ML and Hybrid Models Chair: Anca Anghelea (ESA)
16:00-16:30	Neural-Network Parameterization of Subgrid Momentum Transport Learned from a High-Resolution Simulation Janni Yuval (MIT)
16:30-17:00	Machine learning based climate modelling and analysis Veronika Eyring (DLR and University of Bremen)
17:00-17:30	Atmospheric Physics-Guided Machine Learning: Towards Physically-Consistent, Data-Driven, and Interpretable Models of Convection Tom Beucler (University of Lausanne)
	Wednesday, 17 November
	Session 3.2: Geophysical Forecasting with ML and Hybrid Models Chair: Marc Bocquet (ENPC)
09.00-10.30	Learning parameters of a numerical model from observations Tijana Janjic (Ludwig-Maximilians-Universität München)
09.30-10.00	Machine Learning for Seamless Thunderstorm Nowcasting from Multiple Data Sources Jussi Leinonen (MeteoSwiss)
10.00-10.30	Smartriver: Artificial Intelligence for Effective Water Resources Forecast and Management Stefano Bagli (Gecosistema)
	Session 4.1: ML for Post-Processing and Dissemination Chair: Gustau Camps Vals (IPL - Universitat de València)
11:00-11:30	Post-processing of precipitation with Bernstein quantile distribution networks John Bjørnar Bremnes (Norwegian Meteorological Institute)
11:30-12:00	Machine Learning-Based Post-Process Correction of the High-Resolution Multi-Wavelength Sentinel-3 Synergy Aerosol Product Antti Lipponen (Finnish Meteorological Institute)
12:00-12:30	Integrating Reanalysis and Satellite Cloud Information to Estimate Downward Long-wave Radiation Fluxes Using Multivariate Adaptive Regression Splines: Application to EUMETSAT LSA-SAF Francisco Lopes (Instituto Dom Luis)
12:30-13:00	A spatiotemporal ensemble machine learning framework for predictive mapping: One model to rule them all? Tom Hengl (OpenGeoHub foundation)
13:00-14:00	Lunch Break
	Session 4.2: ML for Post-Processing and Dissemination Chair: Claudia Vitolo (ESA)
14:00-14:30	Using Convolutional Neural Networks to Detect Emissions Plumes From TROPOMI Data Douglas Finch (University Of Edinburgh)
14:30-15:00	Downscaling air pollution levels by fusing Geospatial Vector Data and Sentinel 5P observations over Europe Marvin Mc Cutchan (Iarai and Tu Wien)
15:00-15:30	The Self-Attentive Ensemble Transformer: Representing Ensemble Interactions in Neural Networks Tobias Finn (Universität Hamburg)
15:30-16:00	Coffee break
	Session 4.3: ML for Post-Processing and Dissemination Chair: Peter Dueben (ECMWF)
16:00-16:30	How Earth Observations and Machine Learning are Supporting Agricultural Monitoring and Food Security Globally Catherine Nakalembe (University of Maryland and NASA Harvest)
16:30-17:00	Flood Segmentation on Sentinel-1 SAR Imagery with Semi-Supervised Learning Siddha Ganju, (Nvidia, SpaceML, and FDL)
17:00-17:30	Description of Working Group Massimo Bonavita (ECMWF)
	Thursday, 18 November
	Working Groups - Thematic areas
9:00-10:30	WG1 - Enhancing Satellite Observation with ML Chairs: Begüm Demir and Bertrand Le Saux
9:00-10:30	WG2 - Hybrid Data Assimilation - ML Approaches Chairs: Rossella Arcucci and Alan Geer
9:00-10:30	WG3 - Geophysical Forecasting with ML and Hybrid Models Chairs: Claudia Vitolo and Peter Dueben
9:00-10:30	WG4 - ML for Post-Processing and Dissemination Chairs: Rochelle Schneider and Massimo Bonavita
10:30-11:00	Coffee Break
11:00-12:00	WG1 - Enhancing Satellite Observation with ML Chairs: Begüm Demir and Bertrand Le Saux
11:00-12:00	WG2 - Hybrid Data Assimilation - ML Approaches Chairs: Rossella Arcucci and Alan Geer
11:00-12:00	WG3 - Geophysical Forecasting with ML and Hybrid Models Chairs: Claudia Vitolo and Peter Dueben
11:00-12:00	WG4 - ML for Post-Processing and Dissemination Chairs: Rochelle Schneider and Massimo Bonavita
12:00-13:00	WG chairs finalise reports
13:00-14:00	Lunch break
	Session 5: Working Groups plenary discussion and close
14:00-15:30	Working Groups - plenary discussion and close Chair: Massimo Bonavita (ECMWF)

Posters

ID	Poster Title
1	Incorporating Spatial Information Into Ensemble Post-processing via Autoencoder Neural Networks Sebastian Lerch (Karlsruhe Institute Of Technology), Kai Polsterer (Heidelberg Institute for Theoretical Studies)
2	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)
3	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)
4	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)
5	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)
6	S2S-Forecasting of Central European Winter Temperature Based on Quantile Random Forests Selina Kiefer Karlsruhe (Institute For Technology)
7	Automated Polynya Identification Tool (APIT) James Hickson (ARGANS), Estrella Olmedo (Barcelona Expert Centre), Verónica Gonzalez (Barcelona Expert Centre), Diego Fernández (ESA)
8	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)
9	Multivariate Ensemble Post-Processing Using Generative Machine Learning Methods Jieyu Chen (Karlsruhe Institute Of Technology), Sebastian Lerch (Karlsruhe Institute Of Technology)
10	Prediction of Ocean Driven Antarctic Ice Shelf Melting Using Machine Learning Sebastian Rosier (Northumbria University), Christopher Bull (Northumbria University)
11	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)
12	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)
13	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)
14	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)
15	Deep Learning in Space: The Big Data Problems or Big Problems with Data? Jakub Nalepa (KP Labs)
16	Deep Learning weather uncertainty quantification for EO satellite mission planning Jonathan Guerra (Airbus Defence & Space), Mathieu Picard (Airbus Defence & Space)
17	Digital Mapping of Soil Organic Matter Using Open Source Accessible Products of ESA® in Arable Plain Fuat Kaya Isparta (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)
18	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),
19	Satellite Tracking & Monitoring using Orbitshub ACCAT Systems Divya Krishnamoorthy (Orbitshub)
20	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)
21	High-resolution soil moisture retrieval from remote sensing microwave observations Grigorios Tsagkatakis (Forth), Mahta Moghaddam (University of Southern California), Panagiotis Tsakalides (Forth)
22	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)
23	Training Dataset Requirements for Cloud Masking Carsten Brockmann (Brockmann Consult GmbH), Jan Wevers (Brockmann Consult GmbH)
24	Daily to Sub-daily precipitation downscaling based on multiple datasets using artificial neural networks in Brazil Rogerio Batista (Inpe), Alan Calheiros (Inpe)
25	Intelligent Dashboard of the Celestial Meteor CAMS Data Julia Nguyen (SpaceML), Chicheng Ren
26	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)
27	It's a Bird, It's a Plane, It's a Meteor! Surya Ambardar (Student), Siddha Ganju (NVIDIA), Peter Jenniskens (SETI Institute)
28	Satellite Image Simulation by Neural Networks Based on RTTOV Radiative Transfer Model Tom Cocogne (French Satellite Meteorology Research Centre)
29	Humanitarian Disaster Assistance Informed by White Box Earth Observation-based Machine Learning Algorithms Thomas Chen (Academy For Mathematics, Science, And Engineering)
30	Spatio-temporal climate extremes – semi-supervised detection with a deep autoencoder Albrecht Schall (Max Planck Institute for Biogeochemistry)

deadlines

Abstract Submissions opens: 28 June 2021

Abstract Submission closes: 15 August 2021

Registration opens: 16 August 2021

Abstract acceptance notification: Early October

Registration closes: 1 November 2021

2nd EDITION

Agenda

Posters

deadlines

2^ndEDITION