2013 IEEE GRSS Data Fusion Contest: Fusion of Hyperspectral and LiDAR Data
The 2013 Contest was aimed at exploring the synergetic use of hyperspectral and LiDAR data. The hyperspectral imagery was composed of 144 spectral bands from 380 to 1050 nm. A co-registered LiDAR derived Digital Surface Model (DSM) was also made available to all participants. Both data sets had the same spatial resolution (2.5m). As shown in Fig. 1, the data was acquired by the National Science Foundation (NSF)-funded Center for Airborne Laser Mapping (NCALM) in the summer of 2012 over the University of Houston and the neighboring urban area.
Composition of the hyperspectral and LiDAR data sets over the University of Houston campus.
This year, the Contest consisted of two parallel competitions:
Best Classification Challenge, with the objective of promoting innovation in classification algorithms, and to provide fair performance comparisons among state-of-the-art algorithms. For this task, users were provided with training samples from 14 classes of interest, including various types of vegetation, soil, water, but also less common targets, such as commercial buildings, highways, railway, and vehicles. The validation samples that the Contest organizers used to evaluate the submissions were not disclosed.
Best Paper Challenge, with the objective of promoting novel use of hyperspectral and LiDAR data. The deliverable was a 4-page manuscript describing the problem, methodology, results and discussion. The goal of this challenge was to encourage the participants to consider hyperspectral and LiDAR data fusion problems and to demonstrate novel and effective approaches to address them.
The Data Fusion Award Committee consisted of seven independent judges from universities and industries:
- Jocelyn Chanussot, Grenoble Institute of Technology, France
- Melba Crawford, Purdue University, USA
- Jenny Du, Mississippi State University, USA
- Paolo Gamba, University of Pavia, Italy
- Fabio Pacifici, DigitalGlobe, Inc., USA
- Antonio Plaza, University of Extremadura, Spain
- Saurabh Prasad, University of Houston, USA
Papers were judged in terms of sound scientific reasoning, problem definition, methodology, validation, and presentation.
More than 900 researchers from universities, national labs, space agencies, and corporations across the globe registered to the Contest, demonstrating the great interest of the community in the DFTC activities in promoting cutting-edge research of remote sensing image processing and analysis. The data sets were downloaded from a total of 69 different countries, with a large number of registrations from less developed areas. Fig. 2 shows the geographical distribution of the participants, where other indicates the sum of all countries with less than 10 participants.
Geographical distribution of the participants for countries with more than 10 participants.
Final results were announced at the 2013 IEEE International Geoscience and Remote Sensing Symposium held in Melbourne, Australia. The winners of the 2013 Data Fusion Contest are:
- Christian Debes, Andreas Merentitis, Roel Heremans, Jürgen Hahn, Nick Frangiadakis, and Tim van Kasteren from AGT International and Technische Universität Darmstadt, Germany, are the winners of the Best Classification Challenge. Details can be found at http://hyperspectral.ee.uh.edu/?page_id=695
- Wenzhi Liao, Rik Bellens, Aleksandra Pizurica, Sidharta Gautama, and Wilfried Philips from Ghent University, Belgium, are the winners of the Best Paper Challenge with a paper entitled “GRAPH-BASED FEATURE FUSION OF HYPERSPECTRAL AND LIDAR REMOTE SENSING DATA USING MORPHOLOGICAL FEATURES”. Details can be found at http://hyperspectral.ee.uh.edu/?page_id=795
As shown in Fig. 3, the winning teams were awarded IEEE GRSS Certificates of Appreciations and iPads during the Technical Committees and Chapters Dinner. Additionally, as is tradition, a manuscript summarizing the Contest outcomes will be submitted for peer review to the IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS). To further enhance its impact in the community, the Data Fusion Technical Committee will support its open-access publication cost. Funding provided by the IEEE Geoscience and Remote Sensing Society and DigitalGlobe, Inc.
The Data Fusion Technical Committee congratulates the winners of the 2013 Contest during the Chapters and Technical Committees Dinner at IGARSS 2013. From left to right in each photo: (a) Qian Du, Fabio Pacifici, Andreas Merentitis, and Saurabh Prasad; (b) Qian Du, Fabio Pacifici, Paul Scheunders (on behalf of Liao et al.), and Saurabh Prasad.