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Multi-Modal and Multi-Temporal Data Fusion: Outcome of the 2012 GRSS Data Fusion Contest

Authors :
Richard Bamler
A. Buswell
T. Heyer
Michael G. Gartley
J. Jacobson
Jonas Eberle
K. Ewald
Junyi Tao
Stefan Auer
S. Hese
M. Voltersen
Christiane Schmullius
Robert Eckardt
Nesrin Salepci
Christian Berger
Qian Du
Fabio Pacifici
Chanussot, Jocelyn
Source :
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 6, Iss 3, Pp 1324-1340 (2013)
Publication Year :
2013
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), 2013.

Abstract

The 2012 Data Fusion Contest organized by the Data Fusion Technical Committee (DFTC) of the IEEE Geoscience and Remote Sensing Society (GRSS) aimed at investigating the potential use of very high spatial resolution (VHR) multi-modal/multi-temporal image fusion. Three different types of data sets, including spaceborne multi-spectral, spaceborne synthetic aperture radar (SAR), and airborne light detection and ranging (LiDAR) data collected over the downtown San Francisco area were distributed during the Contest. This paper highlights the three awarded research contributions which investigate (i) a new metric to assess urban density (UD) from multi-spectral and LiDAR data, (ii) simulation-based techniques to jointly use SAR and LiDAR data for image interpretation and change detection, and (iii) radiosity methods to improve surface reflectance retrievals of optical data in complex illumination environments. In particular, they demonstrate the usefulness of LiDAR data when fused with optical or SAR data. We believe these interesting investigations will stimulate further research in the related areas.

Details

ISSN :
21511535 and 19391404
Volume :
6
Database :
OpenAIRE
Journal :
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Accession number :
edsair.doi.dedup.....214b280c40c51b3734dac7eb74c9ed6d