Resources
A central hub for help, learning materials, and policies for the GeoAI Arctic Mapping Challenge.
π‘ Tip: If youβre new here, start with the Quick Links below.
Quick Links
Contact Us
- Competition support: wenwen@asu.edu, chiayuhsu@asu.edu
- Technical Q&A: Use the CodeBench forum for public questions: https://codebench.com/geoai-rts/forum
Tutorials & Learning Materials
Official
- Baseline notebook: Includes data loading, visualization, baseline model, and submission formatter.
- Submission format mini-guide: See Participate β Results Format for 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 (dataset) and Li et al., 2025 (baseline model) (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
- Teaming is allowed (default max 5 members unless otherwise stated).
- Do not share labels or predictions across different teams.
- Follow the CodeBench 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
- CodeBench Platform: https://codebench.com
- Leaderboard: https://codebench.com/geoai-rts/leaderboard
- Forum: https://codebench.com/geoai-rts/forum
- Dataset Paper (Yang et al., 2023): https://doi.org/10.1016/j.rse.2023.113495
- Baseline Model (Li et al., 2025): https://doi.org/10.1109/JSTARS.2025.3564310
Frequently Asked Questions
Q1. Where do I download the data?
A: Register on CodeBench β challenge page β Download tab. Or see the Dataset Page.
Q2. Whatβs the submission format?
A: COCO-style JSON (see Participate β Results Format). A helper is included in the baseline notebook.
Q4. Can I keep evaluating after prizes are awarded?
A: Yes β use the Benchmark Phase for continuous, no-award evaluation.
Q5. Can I use external data?
A: Yes, but you must document it in your method description.