The Data Fusion Contest is organized by the Data Fusion Technical Committee (DFTC) of the Geoscience and Remote Sensing Society (GRSS) of the International Institute of Electrical and Electronic Engineers (IEEE). The DFTC serves as a global, multi-disciplinary, network for geospatial data fusion, connecting people and resources. It aims at educating students and professionals, and at promoting the best practices in data fusion applications.

The current DFTC Chair and Co-Chair are Fabio Pacifici and Jenny Du, respectively. The committee maintains this site and distributes an e-mail newsletter to all committee members on a regular basis.

The DFTC has two main activities:

• organization of a special session held annually during the IGARSS meeting, gathering cutting edge contributions and covering various issues related to data fusion, such as: pan-sharpening, decision fusion, multimodal data fusion, data assimilation, multi-temporal data analysis, ensemble methods, etc.
• organization of a scientific challenge named Data Fusion Contest.

The Contest is annually proposed since 2006 and it is open not only to IEEE members, but to everyone, with the aim of evaluating existing methodologies at the research or operational level to solve remote sensing problems using data from different sensors.

The focus of the 2006 Contest was on the fusion of multi-spectral and panchromatic images [1]. Six Pleiades simulated images were provided by CNES, the French National Space Agency. Each data set included a very high spatial resolution panchromatic image (80 cm) with corresponding multi-spectral images (3.2 m resolution). A multi-spectral very high spatial resolution airborne image was available as ground reference and used by the organizing committee for the evaluation of the results, and not distributed to the participants.

In 2007, the Contest theme was urban mapping using radar and optical data [2]. A set of satellite radar and optical images (9 ERS amplitude data sets and 2 Landsat multi-spectral images) was available. The task was to obtain a classified map as accurate as possible with respect to the unknown (to the participants) ground reference, depicting land cover and land use classes for the urban area under test.

The 2008 Contest was dedicated to the classification of very high spatial resolution (1.3 m) hyper-spectral imagery [3]. The data set was distributed to every participant, and the task was to obtain a classified map as accurate as possible with respect to the unknown (to the participants) ground reference. The data set consisted of airborne data from the Reflective Optics System Imaging Spectrometer (ROSIS-03) optical sensor. The number of bands of ROSIS-03 was 115 with a spectral coverage ranging from 0.43 to 0.86 μm. Thirteen noisy bands were removed.

In 2009-2010, the aim of Contest was to perform change detection using multi-temporal and multi-modal data. Two pairs of data sets were available over Gloucester, UK, before and after a flood event. The data set contained SPOT and ERS images (before and after). The optical and radar images were provided by CNES. As for the previous editions of the Contest, the ground truth used to assess the results was not provided to the participants. Singular results were tested and ranked a first time using the K coefficient. The best 5 results were used to perform information fusion using majority voting. Then, re-ranking was carried out after evaluating which result most improved the information fusion results with respect to the above mentioned K coefficient.

[1]   L. Alparone, L. Wald, J. Chanussot, C. Thomas, P. Gamba, and L. M. Bruce, “Comparison of pansharpening algorithms: Outcome of the 2006 GRS-S data fusion contest”, IEEE Transactions on Geoscience and Remote Sensing, vol. 45, no. 10, pp. 3012–3021, Oct. 2007.

[2]   F. Pacifici, F. Del Frate, W. J. Emery, P. Gamba, J. Chanussot, “Urban mapping using coarse SAR and optical data: outcome of the 2007 GRS-S data fusion contest”, IEEE Geoscience and Remote Sensing Letters, vol. 5, no. 3, pp. 331-335, July 2008

[3]   G. Licciardi, F. Pacifici, D. Tuia, S. Prasad, T. West, F. Giacco, J. Inglada, E. Christophe, J. Chanussot, P. Gamba, “Decision fusion for the classification of hyperspectral data: outcome of the 2008 GRS-S data fusion contest”, IEEE Transactions on Geoscience and Remote Sensing, vol. 47, no. 11, pp. 3857-3865, November 2009