Overview
The AI for Urban Heat Resilience Hackathon 2026 is a two-day, in-person technical hackathon that brings together developers, startups, researchers, and students to build AI-driven solutions addressing urban heat risk, a growing climate and public-health challenge.
Participants will design and prototype data- and compute-intensive AI workflows that infer high-resolution land-surface temperature and urban thermal risk from lower-resolution satellite imagery, using drone-based thermal data and auxiliary urban datasets. The hackathon emphasizes applied machine learning, scalable cloud computing, and responsible AI for real-world decision-making in climate resilience and public health.
The deadline to apply is March 5, 2026.
Prizes
Top-performing teams will be recognized and awarded at the close of the hackathon:
🥇 1st Place: $3,000
🥈 2nd Place: $2,000
🥉 3rd Place: $1,000
⭐ Most Innovative / Most Collaborative Team: $500
Objectives
The hackathon aims to:
- Advance AI and machine-learning methods for thermal downscaling and inference
- Enable integration of multi-modal geospatial datasets (satellite, drone, and urban context data)
- Provide hands-on experience with scalable, cloud-based AI infrastructure
- Foster collaboration between academia, industry, and startups
- Produce technically sound prototypes with pathways to real-world deployment
Challenge Focus Areas
Teams will work within a shared technical framework and may focus on one or more of the following areas:
- Thermal Downscaling & Super-Resolution: AI models that infer fine-scale thermal surfaces from coarse satellite inputs.
- Multi-Source Data Fusion: Combining satellite imagery, drone thermal scans, and auxiliary urban datasets.
- Urban Heat Risk Mapping: Translating thermal outputs into interpretable risk metrics relevant to climate resilience and public health.
- Model Efficiency & Scalability: Designing computationally efficient pipelines suitable for large-scale or resource-constrained settings.
- Responsible & Equitable AI: Addressing bias, transparency, and ethical data use in climate and health applications.
Who Should Apply
This hackathon is intended for participants with strong technical backgrounds who are comfortable working in programming and data science environments. We welcome applications from:
- Developers and software engineers
- Startups and early-stage technology teams working in AI, climate tech, health tech, or urban analytics
- Data scientists and AI/ML practitioners
- Graduate students and advanced undergraduates with solid technical training
- Researchers with experience in Python-based workflows, geospatial analysis, vision foundation models, cloud computing, and CNNs
- Participants should be comfortable using programming tools and software (e.g., Python, Jupyter notebooks, and version control systems) and working in collaborative, cloud-based development environments
- Intermediate-to-advanced technical experience is highly recommended, and teams are expected to demonstrate clear technical capacity
Data & Technical Environment
Participants will work with curated datasets that may include:
- Satellite-derived land surface temperature products
- High-resolution drone-based thermal imagery
- Auxiliary urban datasets, for example, building data
- Weather datasets
All development will take place in a cloud-based AWS environment, with pre-configured team accounts, centralized data access, and collaborative notebook workflows. Pre-hackathon technical onboarding materials and documentation will be provided.
Mentorship & Support
Teams will receive technical and domain guidance from mentors with expertise in:
- Artificial intelligence and machine learning
- Geospatial analysis and remote sensing
- Climate resilience and public-health applications
- Cloud infrastructure and MLOps
Deliverables
By the end of the hackathon, teams are expected to produce:
- A working technical prototype or proof-of-concept
- Clear documentation of methods, data usage, and assumptions
- A short final presentation or live demo
Application
⏳ Application Deadline: March 13, 2026
Code of Conduct
All participants are expected to adhere to a professional code of conduct emphasizing respect, inclusivity, collaboration, and responsible data use. A formal Code of Conduct will be shared with accepted participants.