Welcome to the 1st workshop on Complex Data Challenges in Earth Observation (CDCEO) 2021. This workshop is held as a satellite event at the 30th ACM International Conference on Information and Knowledge Management (CIKM). CIKM 2021 runs as a fully virtual conference.

The workshop focuses on advancing research in Earth observation (EO) by effectively interpreting the high-dimensional heterogeneous data obtained by high-resolution remote sensing technologies.

Big data accumulated by ground, aerial, and satellite-based remote sensors at an unprecedented scale and resolution invite the application of modern data-hungry machine learning (ML) methods.

The workshop aims to bring together researchers in the fields of remote sensing, geographic information systems, weather and climate modeling, computer vision, and others with a general interest in applying data-driven models in EO.

Workshop Topics

The workshop invites advanced applications and method development in image and signal processing, data fusion, feature extraction, meta learning, and many more.

The workshop topics include but are not limited to:

  • spatiotemporal data processing and analysis;

  • multi-resolution, multi-temporal, multi-sensor, and multi-modal data fusion;

  • ML for weather and climate research;

  • deep learning and its applications to e.g., semantic segmentation, scene classification, and feature extraction;

  • advanced applications of time-series data analysis, e.g., urban sprawl, deforestation, crop monitoring, weather forecasts; 

  • feature extraction, feature selection, and dimensionality reduction;

  • meta learning, including transfer learning, few-shot learning, and active learning;

  • data acquisition and efficient pre-processing of diverse remote sensing measurements including:

    • passive sensor images (panchromatic, multispectral, and hyperspectral);

    • active sensor data (LiDAR, RADAR, and SAR);

  • integration and aggregation of complementary remote sensing measurements;

  • advances in signal processing with applications to, e.g., unmixing, denoising;

  • benchmark datasets with application to EO.

Important Dates

  • Submission opens: 14.06.2021
  • Submission deadline: 29.07.2021 (Anywhere on Earth) (extended)
  • Paper acceptance notifications: 20.08.2021 (extended)
  • Camera ready submissions: 28.08.2021 (Anywhere on Earth) (extended)
  • Workshop date:  01.11.2021.

Invited Speakers

Xavier Calbet

Nowcasting Sattelite Application Facility, Spanish Meteorological Agency, Spain

Application of Artificial Intelligence/Machine Learning techniques in Remote Sensing for Meteorology

Science coordinator for the EUMETSAT Nowcasting Satellite Application Facility (NWC SAF) and the State Meteorological Agency of the Government of Spain AEMET. He has worked with EUMETSAT in Darmstadt specializing in atmospheric profile retrievals obtained from hyper-spectral sounding instruments, such as the Infrared Atmospheric Sounding Interferometer, and planning for the future geostationary hyperspectral sounding mission MTG-IRS. He has also worked as a state meteorologist at AEMET.

Peter Dueben

European Centre for Medium-Range Weather Forecasts (ECMWF)

Machine Learning for Weather and Climate Predictions

Peter is the AI and Machine Learning Coordinator at ECMWF and holds a University Research Fellowship of the Royal Society that enables him to perform research towards the use of machine learning, high-performance computing, and reduced numerical precision in weather and climate predictions. Peter has also a strong interest in the quantification of uncertainty of predictions for chaotic systems. Peter is coordinator of the MAELSTROM EuroHPC-Join Undertaking project, work-package leader of the ESiWACE2 H2020 project, and Co-Pi of an US-INCITE grant to perform season-long, global, storm-resolving simulations. Before moving to ECMWF, Peter has written his PhD thesis at the Max Planck Institute for Meteorology and has worked as PostDoc with Tim Palmer at the University of Oxford.

Wolfgang Wagner

Department of Geodesy and Geoinformation, Technical University Wien, Austria

Earth Observation Data Centre for Water Resources Monitoring, Austria

Advancing the Understanding of Spaceborne Radar Observations using Machine Learning and Physical Models

Wolfgang Wagner received the Dipl.-Ing. (MSc) degree in physics and the Dr.techn. (PhD) degree in remote sensing from the Technische Universität Wien (TU Wien), Austria, in 1995 and 1999 respectively. In support of his master and PhD studies he received fellowships to carry out research at the University of Bern (1993), Atmospheric Environment Service Canada (1994), NASA Goddard Space Flight Centre (1995), European Space Agency (1996), and the Joint Research Centre of the European Commission (1996-1998). From 1999 to 2001 he was with the German Aerospace Agency (DLR). In 2001 he was appointed professor for remote sensing at the Institute of Photogrammetry and Remote Sensing of TU Wien. From 2006 to 2011 he was the head of the Institute of Photogrammetry and Remote Sensing, from 2012 to 2019 the head of the newly founded Department of Geodesy and Geoinformation, and since 2020 he serves as the dean of the Faculty for Mathematics and Geoinformation. Furthermore, he is co-founder of the EODC Earth Observation Data Centre, where he has worked part-time as senior scientist since December 2014. Since 2018 he has also been affiliated with the Global Change Research Institute of the Czech Academy of Sciences (CzechGlobe).

Program

Time(CET)Title of the talkSpeakerAffiliation
1st session – Novemeber 1st, 12:00 – 1:15 PM
12:00Invited talk: Advancing the Understanding of Spaceborne Radar Observations using Machine Learning and Physical Models

Wolfgang Wanger Department of Geodesy and Geoinformation, TU Wien, Austria
Earth Observation Data Centre for Water Resources Monitoring, Austria
12:30Towards Very-Low Latency Storm Nowcasting through AI-Based On-Board Satellite Data Processing

Robert HinzDEIMOS Space S.L.U, Spain
12:45Hyperspectral Anomaly Detection based on Low-rank Structure Exploration

Shizhen ChangWuhan University, China
13:00Towards Geographical Aware Neural Networks for Geospatial Vector Data: A Case Study on Land Use and Land Cover Classification

Marvin Mc Cutchan

Institute of Advanced Research in Artificial Intelligence, Austria

TU Wien, Austria

13:15 – 13:25COFFE BREAK (IARAI topia world)
2nd session – Novemeber 1st, 1:25 – 2:55 PM
13:25Invited talk: Machine Learning for Weather and Climate Predictions

Peter Dueben European Centre for Medium-Range Weather Forecasts (ECMWF)
13:55Deep Hybrid Network: Dual Graph Filter Fuzzy for Hyperspectral Image Classification

Ding YaoXi’an Research Institute of High Technology, China
14:10Region-Growing Fully Convolutional Networks for Hyperspectral Image Classification with Point-Level Supervision

Yonghao XuWuhan University, China
14:25Uncertainty-aware Graph-based Multimodal Remote Sensing Setection of Out-of-distribution Samples

Iain RollandUniversity of Cambridge, UK
14:40On the Exploitation of Heterophily in Graph-based Multimodal Remote Sensing Data Analysis

TBATBA
14:55 – 15:05COFFE BREAK (IARAI topia world)
Poster Session – Novemeber 1st, 3:05 – 4:05 PM
15:05Graph Neural Sparsification for Hyperspectral Image Classification with Local and Global Consistency

 Haojie HuXi’an Research Institute of High Technology, China
Hyperspectral Denoising: From Conventional techniques Towards Deep Learning ones

Behnood RastiAlexander von Humboldt Research Fellow, Helmholtz Institute Freiberg for Resource Technology, Germany
Point-based Weakly Supervised Deep Learning for Water Extraction from High-resolution Remote Sensing Imagery

Ming LuHunan University, China
Machine Learning Model Development for Space Weather Forecast

Randa NatrasTechnical University of Munich, Germany
Large-scale Hyperspectral Image Clustering Using Contrastive Learning

TBATBA
FORCE on Nextflow: Scalable Analysis of Earth Observation data on Commodity Clusters

Fabian LehmannInstitute for Computer Science, Humboldt-Universität zu Berlin, Germany
Change Detection for Hyperspectral Imagery based on Multi-layer Cascade Screening Strategy

Lian LiuAerospace Information Research Institute, Chinese Academy of Sciences, China
End-to-end CNN-CRFs for Multi-date Crop Classification Using Multitemporal Remote Sensing Image Sequences

Laura Elena Cué La RosaPontifical Catholic University of Rio de Janeiro (PUC-Rio), Brazil
15:45Poster session Q&A  
16:05 – 16:15COFFE BREAK (IARAI topia world)
Special Weater4cast Comeptition Session – Novemeber 1st, 4:15 – 6:00 PM
16:15Invited talk: Application of Artificial Intelligence/Machine Learning techniques in Remote Sensing for Meteorology

Xavier Calbet Spanish Meteorological Agency AEMET, Spain
16:45The Weater4cast Stage1 Competition Design and Data

TBAInstitute of Advanced Research in Artificial Intelligence, Austria
16:551st prize: Spatiotemporal Weather Data Predictions with Shortcut Recurrent-Convolutional Networks: A Solution for the Weather4cast challenge

Jussi LeinonenFederal Office of Meteorology and Climatology  MeteoSwiss, Switzerland
17:102nd prize: Utilizing UNet for the future weather prediction: Weather4cast 2021’

Sungbin Choi 
17:253rd prize: A Variational U-Net for Weather Forecasting

Pak Hay Kwok, Qi Qi 
17:40Efficient Spatio-temporal Weather Forecasting with Deep Neural Networks

Akshay Punjabi, Pablo Izquierdo Ayala 
17:50Spatiotemporal Swin-Transformer Network for Short Time Weather Forecasting

Alabi BojesomoKhalifa University, UAE
18:00Closing remarks
Pedram GhamisiInstitute of Advanced Research in Artificial Intelligence, Austria
18:05Get-together (IARAI topia world)
Time
(CET)
Title of the talk Speaker Affiliation
1st session – Novemeber 1st, 12:00 – 1:15 PM
12:00 Invited talk: Advancing the Understanding of Spaceborne Radar Observations using Machine Learning and Physical Models

by Wolfgang Wanger
Wolfgang Wanger  Department of Geodesy and Geoinformation, TU Wien, Austria
Earth Observation Data Centre for Water Resources Monitoring, Austria
12:30 Towards Very-Low Latency Storm Nowcasting through AI-Based On-Board Satellite Data Processing

by Robert Hinz
Robert Hinz DEIMOS Space S.L.U, Spain
12:45 Hyperspectral Anomaly Detection based on Low-rank Structure Exploration

by Shizhen Chang
Shizhen Chang Wuhan University, China
13:00 Towards Geographical Aware Neural Networks for Geospatial Vector Data: A Case Study on Land Use and Land Cover ClassificationA

by Marvin Mc Cutchan
Marvin Mc Cutchan

Institute of Advanced Research in Artificial Intelligence, Austria

TU Wien, Austria

13:15 – 13:25 COFFE BREAK (IARAI topia world)    
2nd session – Novemeber 1st, 1:25 – 2:55 PM
13:25 Invited talk: Machine Learning for Weather and Climate Predictions

by Peter Dueben
Peter Dueben  European Centre for Medium-Range Weather Forecasts (ECMWF)
13:55 Deep Hybrid Network: Dual Graph Filter Fuzzy for Hyperspectral Image Classification

by Ding Yao
Ding Yao Xi’an Research Institute of High Technology, China
14:10 Region-Growing Fully Convolutional Networks for Hyperspectral Image Classification with Point-Level Supervision

by Yonghao Xu
Yonghao Xu Wuhan University, China
14:25 Uncertainty-aware Graph-based Multimodal Remote Sensing Setection of Out-of-distribution Samples

by Iain Rolland
Iain Rolland University of Cambridge, UK
14:40 On the Exploitation of Heterophily in Graph-based Multimodal Remote Sensing Data Analysis

TBA
TBA TBA
14:55 – 15:05 COFFE BREAK (IARAI topia world)    
Poster Session – Novemeber 1st, 3:05 – 4:05 PM
15:05 Graph Neural Sparsification for Hyperspectral Image Classification with Local and Global Consistency

by Haojie Hu
 Haojie Hu Xi’an Research Institute of High Technology, China
Hyperspectral Denoising: From Conventional techniques Towards Deep Learning ones

by Behnood Rasti
Behnood Rasti Alexander von Humboldt Research Fellow, Helmholtz Institute Freiberg for Resource Technology, Germany
Point-based Weakly Supervised Deep Learning for Water Extraction from High-resolution Remote Sensing Imagery

by Ming Lu
Ming Lu Hunan University, China
Machine Learning Model Development for Space Weather Forecast

by Randa Natras
Randa Natras Technical University of Munich, Germany
Large-scale Hyperspectral Image Clustering Using Contrastive Learning

TBA
TBA TBA
FORCE on Nextflow: Scalable Analysis of Earth Observation data on Commodity Clusters

by Fabian Lehmann
Fabian Lehmann Institute for Computer Science, Humboldt-Universität zu Berlin, Germany
Change Detection for Hyperspectral Imagery based on Multi-layer Cascade Screening Strategy

by Lian Liu
Lian Liu Aerospace Information Research Institute, Chinese Academy of Sciences, China
End-to-end CNN-CRFs for Multi-date Crop Classification Using Multitemporal Remote Sensing Image Sequences

by Laura Elena Cué La Rosa
Laura Elena Cué La Rosa Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Brazil
15:45 Poster session Q&A    
16:05 – 16:15 COFFE BREAK (IARAI topia world)    
Special Weater4cast Comeptition Session – Novemeber 1st, 4:15 – 6:00 PM
16:15 Invited talk: Application of Artificial Intelligence/Machine Learning techniques in Remote Sensing for Meteorology

by Xavier Calbet
Xavier Calbet  Spanish Meteorological Agency AEMET, Spain
16:45 The Weater4cast Stage1 Competition Design and Data

TBA
TBA Institute of Advanced Research in Artificial Intelligence, Austria
16:55 1st prize: Spatiotemporal Weather Data Predictions with Shortcut Recurrent-Convolutional Networks: A Solution for the Weather4cast challenge

by Jussi Leinonen
Jussi Leinonen Federal Office of Meteorology and Climatology  MeteoSwiss, Switzerland
17:10 2nd prize: Utilizing UNet for the future weather prediction: Weather4cast 2021’

by Sungbin Choi
Sungbin Choi  
17:25 3rd prize: A Variational U-Net for Weather Forecasting

by Pak Hay Kwok, Qi Qi
Pak Hay Kwok, Qi Qi  
17:40 Efficient Spatio-temporal Weather Forecasting with Deep Neural Networks

by Akshay Punjabi, Pablo Izquierdo Ayala
Akshay Punjabi, Pablo Izquierdo Ayala  
17:50 Spatiotemporal Swin-Transformer Network for Short Time Weather Forecasting

by Alabi Bojesomo
Alabi Bojesomo Khalifa University, UAE
18:00 Closing remarks

by Pedram Ghamisi
Pedram Ghamisi Institute of Advanced Research in Artificial Intelligence, Austria
18:05 Get-together (IARAI topia world)    

Submission Instruction

Authors are invited to submit original papers presenting research, position papers or papers presenting research in progress that have not been previously published, and are not being considered for publication elsewhere.

Blind reviewing process preformed by members of Program Committee will be applied to select papers based on their novelty, technical quality, potential impact, clarity, and reproducibility.

Workshop papers will be included in a CIKM companion volume published by http://ceur-ws.org/.  Papers must be formatted in CEUR style guidelines and be submitted via EasyChair.  The page limit is 4 – 6 pages plus references.  At least one of the authors of the accepted papers must register for the workshop for the paper to be included into the workshop proceedings.

Special issue

Authors of the accepted papers will be invited to extend their work and submit it for a special issue of the IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing journal.

A special session of the workshop will present the winning solutions and highlights from a unique multi-sensor weather forecasting competition. Join the competition via weather4cast.ai and predict weather products in various Earth regions!

Weather forecasts are of obvious immediate value, but also are an important part of EO, informing about continuing changes of our environment. Modern ML methods have recently become viable alternatives to long standing physics-based forecasting solutions.

The goal of the competition is a short-term prediction of the selected weather products based on meteorological satellites data obtained in collaboration with AEMETNWC SAF. The competition data are presented in a form of weather movies that consist of multi-channel images encoding the cloud properties, temperature, turbulence, and rainfall. The images are recorded at 15 minute intervals through the entire year in various Earth regions. Learn more… 

Steering Committee

Pedram Ghamisi

Institute of Advanced Research
in Artificial Intelligence, Austria

Helmholtz-Zentrum Dresden-Rossendorf, Germany

Antonio Plaza

University of Extremadura, Spain

Liangpei Zhang

Wuhan University, China

Program Committee

  • Shizhen Chang, Wuhan University, China; Institute of Advanced Research in Artificial Intelligence, Austria
  • Leyuan Fang, Hunan University, China
  • Omid Ghorbanzadeh, University of Salzburg, Austria; Institute of Advanced Research in Artificial Intelligence, Austria
  • Danfeng Hong, German Aerospace Center, Germany
  • Andrea Marinoni, UiT the Arctic University of Norway, Norway
  • Claudio Persello, University of Twente, The Netherlands
  • Behnood Rasti, Helmholtz-Zentrum Dresden-Rossendorf, Germany
  • Martin Werner, Technical University of Munich, Germany
  • Yonghao Xu, Wuhan University, China; Institute of Advanced Research in Artificial Intelligence, Austria 
  • Jun Zhou, Griffith University, Australia

Organizing Committee

Aleksandra
Gruca

Institute of Advanced Research in Artificial Intelligence, Austria

Silesian University of Technology, Poland

Pedro
Herruzo

Institute of Advanced Research in Artificial Intelligence, Austria

Pilar
Rípodas

Spanish Meteorological Agency, Spain

Andrzej
Kucik

European Space Agency
Φ-lab, Italy

Christian
Briese

Earth Observation Data Centre for Water Resources Monitoring, Austria

Pedram Ghamisi

Institute of Advanced Research in Artificial Intelligence, Austria

Helmholtz-Zentrum Dresden-Rossendorf, Germany

Michael
Kopp
Institute of Advanced Research in Artificial Intelligence, Austria
 
HereTechnologies, Switzerland
david_team
David
Kreil

Institute of Advanced Research in Artificial Intelligence, Austria

sepp_team
Sepp
Hochreiter
Institute of Advanced Research in Artificial Intelligence, Austria.

Institute of Advanced Research in Artificial Intelligence, Austria

European Space Agency
Φ-lab, Italy

 Spanish Meteorological Agency, Spain

Earth Observation Data Centre for Water Resources Monitoring, Austria

Contact

cdceo@iarai.ac.at

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