Home » ECRS » Section B: Big Data Handling

2nd International Electronic Conference on Remote Sensing

B: Big Data Handling


Dear Colleagues,

This session on Big Data Handling is intended to collate papers on the latest techniques to manage, exploit, process, and analyze big data in remote sensing applications. The session is expected to bring together experts from different research areas to discover and realize the values of big data in various remote sensing areas. As a result, different techniques and applications exploiting big data will be gathered as a first necessary effort towards the incorporation of this technology into the remote sensing field, and also help academia, governments, and industries to gain insights into the potential of using big data techniques and concepts in remote sensing applications.

Best regards,

Prof. Mingmin Chi
Prof. Jón Atli Benediktsson
Prof. Mihai Datcu

Section Chairs

Prof. Mingmin Chi

Shanghai Key Laboratory of Data Science
School of Computer Science, Fudan University
314-2 Computer Building, 825 Zhang Heng Road
Shanghai 201203, China

Prof. Jón Atli Benediktsson

Faculty of Electrical and Computer Engineering
University of Iceland, Sæmundargata 2, 101 Reykjavik, Iceland

Prof. Mihai Datcu

German Aerospace Center (DLR)
Remote Sensing Technology Institute
Photogrammetry and Image Analysis
Oberpfaffenhofen, 82234 Weßling, Germany

Keywords:

  • Remote Sensing
  • Radar/Lidar/Microwave
  • Multispectral/Hyperspectral
  • High/Very-High Resolution
  • Spatial data
  • Social media data
  • Big data applications
  • Big data analytical techniques
  • Big data collection
  • Big data (content-based image) retrieval
  • Big data evaluation standards
  • Big data storage
  • Big data visualization
  • Cloud computing
  • High performance computing
  • Supercomputing

 

 

List of Accepted Abstracts (3)
Road Extraction from High Resolution Image with Deep Convolution Network – A Case Study of GF-2 Image
EUCALYPTUS VOLUME ESTIMATION IN TERRESTRIAL LASER SCANNING DATA USING INTERPOLATION AND RANSAC METHOD
Determining Relative Errors of Satellite Precipitation Data over The Netherlands