2023 Research Data Challenge

Illustration of a data cat and Research Data Challenge


All Day, April 21, 2023

Welcome to the inaugural Research Data Challenge, a campus-wide competition for undergrads and grad students! The University of Arizona now has a campus-wide license with Planet Labs, giving faculty, staff, students and designated campus colleagues access to a near daily stream of Earth-observation satellite data. We are kicking off access to this data with the Research Data Challenge, which requires participants to use Planet Labs data in innovative ways. 


The Challenge: “Earth Watch: Harnessing Data-Enabled Insights from Daily Earth Observing Satellites.” Analyze Geo-Political, Agricultural, Environmental, or Urban Environments using Planet Labs cube-satellite technology. 

The winners will receive $1,000.  

The deadline to register has passed. For those who have registered, the deadline to submit initial findings is Friday, March 10. 

The competition is an excellent opportunity for students to learn about and use Planet data and apply their analytical skills and innovation to a research problem. The challenge is sponsored by the University of Arizona’s Institute for Computation & Data-Enabled Insight, Arizona Institute for Resilience, Data Science Institute & Data Cooperative, University Libraries.


  • $1,000 to the winning undergraduate and graduate students (or teams from each category)
  • $400 to the runners up for each category
  • Certificate of participation to all of those who submit a final deliverable (see below)


Both undergraduate and graduate students, either individually or in teams and from all disciplines, are eligible to participate. If a team wins, all students on that team will split the prize.

Dates & Schedules

  • Feb. 15: Data Challenge Kickoff in the Main Library, Room 112. 
    • 10 a.m. - noon session: Storytelling through the Lens of Space. Will highlight use cases and provide demonstrations in using the data and developing Planet Stories
    • 2 - 3 p.m. session A: Creating a Map. Will demonstrate the fundamentals of map making using Planet data.
    • 2 - 3 p.m. session B: Advanced session for veteran Planet data users
    • 3 - 5 p.m. session: Drop-in time for Q&As and How To help
  • March 3, 11:59 p.m.: Deadline to register to participate
  • March 10, 11:59 p.m.: Deadline to submit an initial finding research plan and indicate the type of final deliverable
  • April 10, 11:59 p.m.: Final submission is due
  • April 21: Winners announced during an awards ceremony. More details to come.

Challenge Rules 

Data: Students will use data from Planet Labs, which includes high-resolution images of the Earth's surface captured by a fleet of cube satellites. The data includes information on land use, vegetation, water
bodies, and urban infrastructure.

Methods: Students will use the data to perform in a variety of analyses using either Google Earth Engine or Microsoft Planetary Computer, and artificial intelligence and machine learning techniques. They can experiment with various supervised and unsupervised learning algorithms, computer vision techniques, and deep
learning models to extract features, classify and cluster the data.

Deliverable: Students will create a report detailing their findings and provide a visual representation of their analysis using maps or images generated using the platform they choose. They will also have to submit one
of the following deliverables:

  • A website that showcases the results of their analysis and provides explanations and visualizations of the methods used.
  • A GitHub repository that contains the code and any additional materials used in the analysis.
  • A poster that summarizes the main findings and methods used in the analysis.
  • A slide show that presents the results of the analysis.

Judging Criteria

  • The best submission will be selected based on the quality of the analysis, the innovation of the methods used, and the clarity of the deliverable.
  • The prizes will be awarded by a panel of experts in the field of environmental and urban studies, data science, and remote sensing.

Good luck!



Angela Cruze