IEEE GRSS Data Fusion Contest winners announced

Roughly 1,150 people from 78 countries participated in the IEEE Geoscience and Remote Sensing Society’s (GRSS) Data Fusion Contest. The contest, which is helping connect students and researchers around the world, is a forum for the scientific community to evaluate and compare existing or novel methods to solve remote sensing problems with data from various airborne and spaceborne sensors. Participants were asked to examine three different data sets (optical, SAR, and LiDAR) over San Francisco, California, USA. Images from the sensors cover buildings, skyscrapers, commercial and industrial structures, parks and private housing, and highways and bridges. Participants used the data to quickly assess important information about the city, such as its urban density.

The Society awarded the winning teams with IEEE GRSS Certificates of Appreciation and monetary prizes at this year’s IEEE International Geoscience and Remote Sensing Symposium.

1) C. Berger, M. Voltersen, R. Eckardt, J. Eberle, T. Heyer, N. Salepci, S. Hese, and C. Schmullius, from the University of Jena, Germany, with a paper entitled Fusion of High-Resolution Optical Imagery and Object Height Information for an Integrated Assessment of Urban Density (UD).

2) J. Tao from and R. Bamler from the German Aerospace Center (DLR), and S. Auer from Technische Universität München, Germany, with a paper entitled Combination of Lidar and Sar Data With Simulation Techniques for Image Interpretation and Change Detection.

3) K. Ewald and A. Buswell from Ball Aerospace & Technologies Corp., M. Gartley from the Rochester Institute of Technology, and J. Jacobson from the National Air and Space Intelligence Center, United States, with a paper entitled Radiosity Technique for Reflectance Retrieval Applied to Worldview-2 Data.

At the end of the contest, K. Ewald, M. Gartley, J. Jacobson, and A. Buswell said they would donate their monetary prize to United Way, a non-profit, charitable organization that supports education, income, and health (

A manuscript summarizing the contest outcomes will be submitted for peer review to IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS).

The IEEE GRSS Data Fusion Technical Committee would like to express its great appreciation to DigitalGlobe, Astrium Services, and USGS/CLICK for donating data sets to the scientific community and for their continuing support in providing resources for this initiative.

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