2021 IEEE GRSS Data Fusion Contest Track MSD

Organized by yky - Current server time: Jan. 28, 2021, 2:22 a.m. UTC
Reward $20,000

Current

Future Development Phase
March 12, 2021, noon UTC

Next

Test phase
March 8, 2021, noon UTC

End

Competition Ends
Never

Multitemporal Semantic Change Detection

The multitemporal semantic change detection challenge track (Track MSD) of the 2021 IEEE GRSS Data Fusion Contest, organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (GRSS) and Microsoft Research and Microsoft AI for Earth, aims to promote research in automatic land cover change detection and classification from multitemporal, multiresolution, and multispectral imagery.

The task of Track MSD is to create bitemporal high resolution land cover maps using only low-resolution and noisy land cover labels for training. Such a scenario is often encountered around the world, as the proliferation of new sensors with either high spatial resolution (submeter) or high temporal resolution (weekly or even daily) remains unmatched by equally rich label data. Instead, detecting change would have to rely on the analysis of a sequence of input images in an unsupervised manner or with aid of weak, noisy, and outdated labels.

Participants will receive a dataset of 2250 tiles covering the US state of Maryland. For each tile, the following layers of data will be provided:

  • 1m multispectral aerial imagery for 2013
  • 1m multispectral aerial imagery for 2017
  • 30m multispectral satellite imagery for 5 points in time between 2013 and 2017
  • 30m noisy low-resolution land cover labels for 2013
  • 30m noisy low-resolution land cover labels for 2016

Participants will need to infer high-resolution land cover maps that identify changes between the 2013 and 2017 high-resolution imagery for a subset of these 2250 tiles. The land cover change maps will be calculated between classes of a simplified scheme based on that of the noisy 30m low-resolution labels. The change maps will be scored on their accuracy in identifying areas with several particular kinds of change, described in the “Land cover change” section below.

The challenge is twofold: identifying what has changed between two high-resolution aerial images, and identifying what class of change it is based on weak labels.

For details about the 2021 IEEE GRSS Data Fusion Contest: http://www.grss-ieee.org/community/technical-committees/data-fusion/

Evaluation

The task of Track MSD is to create bitemporal high resolution land cover maps using only low-resolution and noisy land cover labels for training. Participants are required to submit land cover change maps in TIFF at a 1m GSD with the Byte (uint8) data type.

The contest consists of two phases:

  • Phase 1 (Development phase): Participants are provided with training data (which includes reference data) and validation data (without reference data) to train and validate their algorithms. Participants can submit prediction results for the validation set to the Codalab competition website to get feedback on the performance from January 4 to March 7, 2021. The performance of the best submission from each account will be displayed on the leaderboard. In parallel, participants need to submit a short paper of 1-2 pages clarifying the used approach, the team members, their Codalab accounts, and one Codalab account to be used for Phase 2 by February 28, 2021 to be eligible to enter Phase 2. Please send a paper to iadf_chairs@grss-ieee.org using IGARSS paper template.
  • Phase 2 (Test phase): Participants receive the test data set (without the corresponding reference data) and submit their binary classification maps from March 8 to March 12, 2021. After evaluation of the results, four winners per track are announced on March 26, 2021.

Performance is assessed using the intersection-over-union (IoU) averaged over 8 types of changes.

The winners will have approximately one month (submission deadlline: April 23, 2021) to write their manuscript that will be included in the IGARSS 2021 proceedings. Manuscripts are 4-page IEEE-style formatted. Each manuscript describes the addressed problem, the proposed method, and the experimental results.

Awards

  • The first, second, third, and fourth-ranked teams in Track MSD will be declared as winners.
  • The authors of the winning submissions will:
    • Present their manuscripts in an invited session dedicated to the Contest at IGARSS 2021
    • Publish their manuscripts in the Proceedings of IGARSS 2021
    • Be awarded IEEE Certificates of Recognition
  • The first, second, and third-ranked teams in Track MSD will receive Azure credits of $10,000, $7,000, and $3,000 (USD), respectively, as a special prize.
  • The authors of the first and second-ranked teams in Track MSD will co-author a journal paper (in a limit of 3 co-authors per submission), which will summarize the outcome of the Contest and will be submitted with open access to IEEE JSTARS.
  • Top-ranked teams will be awarded during IGARSS 2021, Brussels, Belgium in July 2021. The costs for open-access publication will be supported by the GRSS. The winner team prize is kindly sponsored by Microsoft.

Terms and Conditions

Participants of this challenge acknowledge that they have read and agree to the following Contest Terms and Conditions:

  • In any scientific publication using the data, the data shall be referenced as follows: “[REF. NO.] 2021 IEEE GRSS Data Fusion Contest. Online: http://www.grss-ieee.org/community/technical-committees/data-fusion”.
  • Any scientific publication using the data shall include a section “Acknowledgement”. This section shall include the following sentence: “The authors would like to thank the IEEE GRSS Image Analysis and Data Fusion Technical Committee and Microsoft for organizing the Data Fusion Contest”.

Development Phase

Start: Jan. 4, 2021, noon

Description: Development phase: tune your models and submit prediction results on validation data.

Test phase

Start: March 8, 2021, noon

Description: Test phase: tune your models and submit prediction results on test data.

Future Development Phase

Start: March 12, 2021, noon

Description: Future-development phase: tune your models and submit prediction results on test data.

Competition Ends

Never

You must be logged in to participate in competitions.

Sign In
# Username Score
1 tulilin 0.6081
2 AsheLee 0.6038
3 lyttok 0.5905