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: 15.07.2021 (Anywhere on Earth)
  • Paper acceptance notifications: 15.08.2021
  • Camera ready submissions: 23.08.2021 (Anywhere on Earth)
  • Workshop date:  01.11.2021.

Invited Speakers

TBA

Program

TBA

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 in a JCR-indexed 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 Centre for Earth Observation, 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.

©2021 IARAI - INSTITUTE OF ADVANCED RESEARCH IN ARTIFICIAL INTELLIGENCE

Imprint | Privacy Policy

Stay in the know with developments at IARAI

We can let you know if there’s any

updates from the Institute.
You can later also tailor your news feed to specific research areas or keywords (Privacy)
Loading

Log in with your credentials

or    

Forgot your details?

Create Account