The Data Fusion Contest is organized by the Data Fusion Technical Committee of the IEEE Geoscience and Remote Sensing Society (GRSS). The Committee serves as a global, multi-disciplinary, network for geospatial data fusion, with the objective of connecting people and resources, educating students and professionals, and promoting the best practices in data fusion applications. The Contest is open not only to IEEE members, but to everyone, with the goal of evaluating existing methodologies at the research or operational level to solve remote sensing problems using data from a variety of sensors.

This year, the Contest involves two datasets – a hyperspectral image and a LiDAR derived Digital Surface Model (DSM), both at the same spatial resolution (2.5m). The hyperspectral imagery has 144 spectral bands in the 380 nm to 1050 nm region. The dataset was acquired over the University of Houston campus and the neighboring urban area.

The Contest consists of two parallel competitions. Users are welcome to participate in one or both of them.

  1. Best Paper Award, with the objective of promoting novel synergetic use of hyperspectral and LiDAR data. The deliverable will be a 4-page IEEE-style manuscript that addresses the problem, methodology, results and discussion. We encourage the participants to consider various open problems in the realm of multi-sensor data fusion and to use the dataset provided to demonstrate novel and effective approaches to addressing these problems.

  2. Best Classification Award, to promote innovation in classification algorithms, and to provide objective and fair performance comparisons among state-of-the-art algorithms. For this task, users will be provided with ground truth to train and gauge the efficacy of their algorithms. Participants will use the ground truth provided to them, along with the multi-sensor dataset, and submit their classification maps and a brief description of the algorithm.

Important Dates

  • Best Classification Award – Results to be submitted between February 16, 2013 and May 1, 2013.
  • Best Paper Award – Manuscripts to be submitted by May 31, 2013

Discussion Forum

Questions, technical or otherwise, should be submitted only to the IEEE GRSS Data Fusion Discussion Forum at

How to Obtain the Data and Enter the Contest

You may request the data by emailing Prof. Saurabh Prasad ( In your email, please be sure to indicate your Name, Contact information, affiliation (University, research lab etc.), and an acknowledgement that you have read and agree to the Terms and Conditions.

This year the Contest involves two datasets – a hyperspectral image and a LiDAR derived DSM, both at the same spatial resolution (2.5m). The hyperspectral imagery consists of 144 spectral bands in the 380 nm to 1050 nm region and has been calibrated to at-sensor spectral radiance units, SRU =μW/(cm2sr nm). The corresponding co-registered DSM consists of elevation in meters above sea level (per the Geoid 2012A model). The “las” file corresponding to this LiDAR data is available upon email request – The data was acquired by the NSF-funded Center for Airborne Laser Mapping (NCALM) over the University of Houston campus and the neighboring urban area. Further details of the data acquisition are as follows – the LiDAR data was acquired on June 22, 2012, between the time 14:37:55 to 15:38:10 UTC. The  average height of the sensor above ground was 2000ft; The hyperspectral data was acquired on June 23, 2012 between the times 17:37:10 to 17:39:50 UTC. The average height of the sensor above ground was 5500ft.

To enter the Best Paper Award challenge, participants are required to submit a manuscript that will be judged in terms of sound scientific reasoning, problem definition, methodology, validation, and presentation. The deadline for the submission is May 31, 2013. Reports must be 4-page, double column, single spaced, and formatted in accordance with the IEEE International Geoscience and Remote Sensing Symposium template (available at Submissions should clearly present the theoretical rationale, experimental details, results, and discussions. The document must be in English and submitted in PDF format. Make sure to include the following:

  • title,
  • first and last names of each of the authors,
  • affiliations,
  • contact email.

Manuscripts can be submitted electronically to with 2013DFTC_Manuscript in the subject line of the email.

To enter the Best Classification Award challenge, participants are required to submit a classification map employing the training samples provided along with the multi-sensor datasets. The validation samples that the Contest organizers will use to evaluate the submissions will not be disclosed. Each team will be allowed to submit one (and only one) classification result between February 16 and May 1, 2013. The organizers will use measurements of statistical significance among accuracies obtained from the submitted maps, to select the winning team. If there is a tie in submissions, the teams in a tie will be asked to submit a manuscript (according to the Best Paper Award requirements defined above) by May 31, 2013. The Award Committee will evaluate these contributions to select the winning team of the Best Classification Award category.

Participants interested in entering the Best Classification Award challenge can find, along with the data, training samples that may be used to train a supervised classification algorithm. Only samples provided in this set are allowed to be used for training.

Training samples are distributed in two formats:

  • an “ROI” file that can be opened in EXELISVIS-ENVI
  • an ASCII file that can be opened by any programming language

The format of the classification result must comply with the following requirements:

  • the image must be an integer valued, gray-scale tif (or geotif) file
  • the name of the file must adhere to the following convention:


For example, if your email address is, then the file name should be:


  • each pixel in the image must be mapped to one of the following integer values depending upon your classification outcome:

0 – Unclassified
1 – Healthy grass
2 – Stressed grass
3 – Synthetic grass
4 – Trees
5 – Soil
6 – Water
7 – Residential
8 – Commercial
9 – Road
10 – Highway
11 – Railway
12 – Parking Lot 1
13 – Parking Lot 2
14 – Tennis Court
15 – Running Track

Classification results can be submitted electronically to with:

  • 2013DFTC_Classification in the subject line of the email
  • a brief description (50 words, at least) of the algorithm in the body of the email

Failure to follow these instructions will automatically make the submission invalid, resulting in your classification result not being evaluated.

Please note that one and only one submission is allowed per registered participant. Should multiple entries from any participant be received, then exclusively the first result submitted will be considered. Hence, it is advisable to submit the final result only if the participant is satisfied with it.

Award Committee

Each manuscript submitted for the Best Paper Award (and, if needed, for the Best Classification Award) will go through a double-blind peer-review process. Seven independent judges will review the manuscripts:

  • 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

Results and Prizes

Final results will be announced at the 2013 IEEE International Geoscience and Remote Sensing Symposium in Melbourne, Australia, in July 2013.

  • The winning teams will be awarded IEEE Certificates of Appreciation during the Technical Committees and Chapters Luncheon. The Data Fusion Technical Committee will cover the cost of the Luncheon for the two winning teams (up to 3 members per team).
  • Additionally, the Data Fusion Technical Committee is pleased to announce that the winning team of the Best Paper Award and Best Classification Award will receive one 16GB WiFi iPad, with the funding being provided by DigitalGlobe, Inc.
  • Finally, as is tradition, a manuscript summarizing the Contest outcomes will be submitted for peer review to an IEEE-GRSS Journal. To further enhance its impact in the community, the Data Fusion Technical Committee will support the open-access publication cost of the paper, with the funding provided by the IEEE Geoscience and Remote Sensing


The dataset was collected by NCALM at the University of Houston (UH) in June 2012, covering the University of Houston campus. The data was prepared and pre-processed with the assistance of Xiong Zhou, Minshan Cui, Abhinav Singhania and Dr. Juan Carlos Fernández Díaz.

The Data Fusion Technical Committee would like to express its great appreciation to NCALM for providing the data, to UH students, staff and faculty for preparing the data, and to GRSS and DigitalGlobe Inc. for their continuous support in providing funding and resources for the Data Fusion Contest.