Resources
A central hub for help, learning materials, and policies for the GeoAI Arctic Challenge.
๐ก Tip: If youโre new here, start with the Quick Links below.
Quick Links
๐ Starter Materials
Helper scripts to load data, inspect labels, validate submissions, and encode masks.
Contact Us
- Competition support: wenwen@asu.edu, chiayuhsu@asu.edu
- Technical Q&A: Use the Codabench forum for public questions
Tutorials & Learning Materials
Official
- Starter materials: The Codabench files include helper scripts for loading images, inspecting labels, validating submissions, and encoding masks.
- Submission format mini-guide: See Participate -> Submission Format for the COCO results JSON schema.
External
Terms & Conditions
- Data Usage
- The dataset is provided for research and competition purposes within this challenge.
- Redistribution of the dataset or derivatives outside the challenge requires permission from the original data owners and curators.
- Attribution
- Works or publications using this dataset should cite:
Yang et al., 2023 (source dataset) and Li et al., 2025 (related RTS modeling work) (see citations below).
- Works or publications using this dataset should cite:
- Submissions
- Predictions must follow the required submission format and reflect automated model outputs (no manual labeling of test sets).
- External data usage, if used, must be documented in your method description.
- Teams & Conduct
- Each team may include 1 to 5 members.
- Do not share labels or predictions across different teams.
- Follow the Codabench code of conduct and site terms.
- Privacy
- Team name, institution, and scores may appear on the public leaderboard.
- Disqualification
- Violations of the rules, data misuse, or attempts to game the leaderboard may result in removal from the competition.
Questions about policy? Email wenwen@asu.edu, chiayuhsu@asu.edu
Useful External Resources
- Codabench Platform: https://www.codabench.org
- Competition Page: https://www.codabench.org/competitions/10283/
- Forum: https://www.codabench.org/competitions/10283/forum
- Dataset Paper (Yang et al., 2023): https://doi.org/10.1016/j.rse.2023.113495
- Related RTS Modeling Work (Li et al., 2025): https://doi.org/10.1109/JSTARS.2025.3564310
Frequently Asked Questions
Q1. Where do I download the data?
A: Register and receive approval on Codabench, then download the public release package from the Files section. You can also see the Dataset Page for data details.
Q2. Whatโs the submission format?
A: COCO results-format JSON with compressed RLE masks. See Participate -> Submission Format.
Q3. Can I use external data?
A: Yes, but you must document it in your method description.