2014 IEEE GRSS Data
Fusion of Thermal Infrared Hyperspectral and VIS Data
Upon courtesy of the data owner, the data set of the 2014 Data Fusion Contest is kept available to the community for scientific purposes.
and Organization of the Contest
The 2014 Data Fusion
Contest, organized by the Image
Analysis and Data Fusion (IADF) Technical Committee of the IEEE Geoscience and Remote
aimed at providing a challenging image analysis opportunity, including
multiresolution and multisensor fusion, very high resolution imagery,
and a completely new data type, which was never before considered in
Data Fusion Contests.
The 2014 Contest involved two datasets acquired at different spectral
ranges and spatial resolutions: a coarser-resolution
(LWIR, thermal infrared) hyperspectral data set and fine-resolution
data acquired in the visible (VIS) wavelength range. The
acquired by an 84-channel imager that covered the wavelengths between
7.8 to 11.5 µm with approximately 1-m spatial resolution.
latter was a series of color images acquired during separate
flight-lines with approximately 20-cm spatial resolution. The two
data sources covered an urban area near Thetford Mines in
Québec, Canada, and were acquired and were provided for the
Contest by Telops Inc.
The 2014 Data Fusion Contest consisted of two parallel
- The Classification Contest,
which was designed to promote innovation in classification algorithms,
as well as to provide
objective and fair comparisons among methods. The goal was to
exploit coarser resolution thermal hyperspectral data and finer
resolution color data to
generate an accurate classification result at the finer of the two
observed resolutions. Ranking was based on quantitative accuracy
parameters computed with respect to undisclosed test samples. In
accuracy, another relevant aspect to assess a classification method is
its computational burden, given the provided amount of training
samples. In the Classification Contest, participants were given a
limited time to submit their classification maps after the
competition was started. For allowing the participants to effectively
focus their methods on the proposed multiresolution task and type of
input data, the Classification Contest consisted of two steps:
1: Participants were provided with a subset of the data,
ground truth to train their algorithms.
2: Participants received the full data set and submitted
their classification maps by two weeks from the release of the full
data set. In parallel,
they submitted a description of the approach used.
- The Paper Contest, which
aimed at promoting novel synergetic uses of
multiresolution and multisensor data. Participants submitted 4-page
IEEE-style manuscripts using the aforementioned data for fusion tasks.
Each manuscript described the addressed problem, the proposed
method, and the experimental results. The topic of the manuscript in
the data fusion area was totally open and participants were encouraged to
tackle open problems in multisensor and/or multiresolution data
processing, as well as in the analysis of thermal hyperspectral
imagery. Papers were evaluated and ranked by an Award Committee.
Schedule and Deadlines
and comments on the data and the Contest can be submitted to the
Linkedin group of the IADF Technical Committee: http://www.linkedin.com/groups?home=&gid=3678437&trk=anet_ug_hm&goback=.gmr_3678437
Data for the Contest
can be requested by registering
to the Contest. Participants
must read and accept the Contest Terms and Conditions.
thermal hyperspectral image was acquired using the "Hyper-Cam," an airborne LWIR
hyperspectral imager, which is based on a
spectrometer (FTS). The hyperspectral imager was integrated to a
gyro-stabilized platform inside a fixed-wing aircraft. The airborne
LWIR hyperspectral imagery consists of 84 spectral bands in the 868 to
1280 cm^-1 region (7.8 µm to 11.5 µm), at a
resolution of 6 cm^-1 (full-width-halfmaximum). It has been calibrated
to at-sensor spectral radiance units, in W/(m^2 sr cm^-1). The spatial
resolution is approximately 1 m.
A digital color camera
(2 MegaPixels), mounted on the same airborne platform,
was also used to acquire visible imagery data that consisted of
multiple color sub-images associated with distinct flight-lines. The
color imagery consists of RGB uncalibrated digital data. The spatial
resolution of the color data used in the competition is 20 cm.
two airborne data sources are georeferenced. The average height of both
sensors above ground was 2650 ft
(807 m). The two data sources were collected simultaneously on May 21,
2013, between 22:27:36 to 23:46:01 UTC.
that the airborne color data are
composed of a series
of spatially disjoint sub-images and that
the data subset
released for training purposes in Step 1 included only one of these
color sub-images (one flight-line), together with the
of the airborne thermal hyperspectral image (see Fig. 1).
In the full data set, the airborne thermal hyperspectral image
covers the whole
considered ground area, while, in the airborne color data, the
sub-images associated with distinct flight-lines are spatially
by blank (missing) data (see Fig. 2).
Compared to the full data set, the data subset included approximately
20% of the thermal hyperspectral samples and 30% of the available color
be submitted to
the Classification Contest were expected to be at 20-cm spatial
resolution and to cover the areas endowed with both thermal
and color airborne observations (i.e., all pixels endowed with non-blank samples
in the airborne color data).
Step 1 along
with the data subset. This map has the same
spatial resolution as and is registered with the airborne color data subset. It has
been made available for the Contest in both GeoTIFF and
EXELISVIS-ENVI binary raster RAW formats. For both file formats, pixel
values in the map are encoded through 8-bpp unsigned
integers and represent seven thematic classes according to the
|Fig. 1. Example of
the structure of
the data subset: airborne color
sub-image at 20-cm
(bottom right); subset of the airborne thermal hyperspectral channels at 1-m
spatial resolution (top); and training map at the same resolution of
the color data (bottom left). Click
Example of the structure of the full
data set: airborne thermal hyperspectral
channels covering the whole considered area at 1-m spatial resolution
(top); and airborne color data at 20-cm spatial resolution, including multiple
sub-images associated with distinct flight-lines and spatially
separated by blank (missing) data (bottom). Click to enlarge.
samples provided through this training map were allowed to be used for
training purposes in the Classification Contest.
For the Paper Contest, additional
data were also provided by Telops Inc.,
To learn more about
all data provided by Telops Inc. for the Contest, click
here to download a description of the airborne and ground data.
74 individual orthorectified
which the airborne thermal hyperspectral image was generated through mosaicing.
- Ground spectral measurements
obtained using a similar
LWIR hyperspectral imager as the one used for the
airborne acquisition. This hyperspectral imager was
installed on a tripod on the ground, the line-of-sight of the
instrument being approximately parallel to the horizon. A digital color camera
was also taking visible ground data of the same scene, which were provided along with the ground spectral measurements. These imagers were
installed at a geographic position located inside the ground area that
was covered by the aforementioned airborne data.
Deadline for the submission of a classification map to the Classification Contest was March 5, 2014, i.e., two weeks after the release of the full data set.
Deadline for the submission of a manuscript to the Paper Contest was June 15, 2014.
For both competitions, submission consisted in sending the
classification map or the manuscript as an attachment to an e-mail
addressed to the contact e-mail address of the IADF Technical Committee.
Submissions were required to be compliant with the following formatting instructions:
Failure to follow
automatically made the submission invalid, resulting in the
classification map or manuscript not being evaluated.
subject line of the submission e-mail
was IADFTC_2014_Classification_Contest and
IADFTC_2014_Paper_Contest for the Classification and Paper Contests,
body of the submission e-mail for the
Classification Contest included a short abstract (max 100 words),
in which the classification algorithm was outlined.
classification map submitted to the Classification Contest had the same size and spatial resolution as the input color airborne data source in
the full data set,
was registered with these airborne color data, and was recorded as a
TIFF or GeoTIFF file with pixel values (grey levels) encoded through
8-bpp unsigned integers. In the classification map, a thematic class label was
expected to be assigned to
all pixel locations corresponding to available (non-blank)
samples in the airborne color data. These thematic class labels were
represented through the
legend: 0 = unclassified; 1 = road; 2 = trees; 3 = red roof; 4 = grey
roof; 5 = concrete roof; 6 = vegetation; 7 = bare soil.
submitted to the Paper Contest described the addressed problem, the
proposed method, and the experimental results. The manuscript was
written in English and was formatted as a PDF file following the
guidelines and templates of the 2014 IEEE Geoscience and Remote Sensing
Symposium (IGARSS-2014; details can be found at www.igarss2014.org).
The manuscript specified the name(s), affiliation(s), and e-mail
contact(s) of the participant(s).
name of the submitted
file was formatted as lastname_firstname_email_address.tif and
lastname_firstname_email_address.pdf for the Classification Contest and
Paper Contest, respectively. The TIF file for the Classification
Contest was ZIP-compressed before attaching it to the submission
e-mail and the name of the compressed file was
lastname_firstname_email_address.zip. For example, if John Doe, e-mail:
firstname.lastname@example.org, participated to the Classification
Contest, then his classification map was named
doe_john_someid_at_somedept_dot_someuni_dot_edu.tif and the file
attached to the submission e-mail was doe_john_someid_at_somedept_dot_someuni_dot_edu.zip.
For each of the two tracks of the Contest, one and only one submission
was allowed per registered participant. Should
from any participant be received, then exclusively the first result
submitted was considered.
Note that, regardless of the common format, submissions to IGARSS-2014
and to the Paper Contest were independent, i.e., a manuscript submitted
to the Paper Contest was not considered for inclusion in the
IGARSS-2014 technical program.
Committee for the Paper Contest
manuscript submitted to the Paper
Contest was evaluated by an Award Committee
on the basis of its novelty, scientific contribution, analysis and
fusion methodology, experimental validation, and clarity of
explanation. The Award Committee was composed of:
A. Benediktsson, University of Iceland (Iceland)
Chamberland, Telops Inc., Québec (Canada)
Q. Du, Mississippi State University (USA)
Gamba, University of Pavia (Italy)
Moser, University of Genoa (Italy)
Pacifici, DigitalGlobe Inc. (USA)
Shimoni, Royal Military Academy (Belgium)
Tuia, University of Zurich (Switzerland)
Awards, and Prizes
The winning teams of both competitions
were awarded at IGARSS-2014
(Québec, Canada) in July 2014. The award ceremony
took place during the Technical Committees and Chapter Chairs Dinner. Each winning team
was awarded an IEEE
Certificate of Recognition and received a Nexus 7 tablet (one
Furthermore, a paper summarizing the outcomes of both
competitions will be submitted to the IEEE
Journal of Selected Topics in Applied Earth Observations and Remote
and in order to maximize impact and promote the potential of
current multisensor remote sensing technologies, the open-access option
will be used for this submission. The costs for open-access
publication, for the winning teams’ participations to the
Technical Committees and Chapter Chairs Dinner at IGARSS-2014, and for the prizes were supported by the GRSS.
Contest was organized in collaboration with Dr. Michal Shimoni (Signal and Image Centre, Royal Military
Academy, Belgium). The dataset was collected by Telops Inc.
The IADF Technical Committee wish to express its greatest
appreciation to Dr. Shimoni for her indispensable contribution to the
organization of the contest, to Telops Inc. for acquiring and providing
the data used in both competitions, to the Centre de Recherche Public
Gabriel Lippmann (CRPGL, Luxembourg) and to Dr. Martin Schlerf (CRPGL)
for their contribution of the Hyper-Cam LWIR sensor, to Dr. Michaela De
Martino (University of Genoa, Italy) for her contribution to the
preparation of the Classification Contest, and to the IEEE GRSS for
continuously supporting the annual Data Fusion Contest through funding
to Get the Data
data are provided only for the purpose of participation in the 2014
Data Fusion Contest. To
request the full data set, please click here to proceed to registration.
Those who have already registered to get the data subset released in Step 1 do
not need to register again to get the full data set and have received
download information directly via e-mail. For the sake of completeness, the data subset is also enclosed with the full data set.
By submitting the registration form, you acknowledge that you register
to the Contest, that you have read the following Contest Terms and Conditions,
and that you agree to these terms and conditions:
owner of the data and of the copyright on the data is Telops Inc.
data are only available for the scientific purposes of the 2014 IEEE
GRSS Data Fusion Contest.
dissemination or distribution of the data by any registered user is
data can be used in scientific publications
subject to approval by the IEEE GRSS IADF Technical Committee and by
Telops Inc. on a case-by-case basis. To submit a scientific publication
for approval, the publication shall be sent as an attachment to an
e-mail addressed to email@example.com
any scientific publication using the data, the
data shall be identified as “grss_dfc_2014” and
referenced as follows: “[REF. NO.] 2014 IEEE GRSS Data Fusion
scientific publication using the data shall
include a section “Acknowledgement.” This section
include the following sentence: “The authors would like to
Telops Inc. (Québec, Canada) for acquiring and providing the
data used in this study, the IEEE GRSS Image Analysis and Data Fusion
Technical Committee and Dr. Michal Shimoni (Signal and Image Centre,
Royal Military Academy, Belgium) for organizing the 2014 Data Fusion
Contest, the Centre de Recherche Public Gabriel Lippmann (CRPGL,
Luxembourg) and Dr. Martin Schlerf (CRPGL) for their contribution of
the Hyper-Cam LWIR sensor, and Dr. Michaela De Martino (University of
Genoa, Italy) for her contribution to data preparation.”