About Ryan
Ryan Noe's background is in geospatial research, with topics including ecosystem service modeling, climate change, conservation prioritization, and land use change. His work seeks to make the outcomes of environmental management decisions more accessible through spatial research, data, and tools.
He holds an M.S. in Natural Resource Science and Management from the University of Minnesota and a B.A. in Environmental Studies from Carleton College.
Key Projects and Initiatives
Zooniverse Mapping Extension
Zooniverse is the world's largest people-powered research platform, but until recently, mapping-based projects weren't supported. A National Science Foundation award allowed the team to build web mapping capabilities into the platform; Ryan provided guidance to both developers and pilot researchers to ensure a smooth transition, and now serves as a mapping ambassador helping build a community of researchers using crowdsourced mapping in research.
Center for Migration Studies State and National Data Tool
Ryan created a web application to query and display estimates of undocumented, eligible-to-naturalize, and liminal migrant populations by U.S. state. Users can explore the application to learn about the demographics of migrants with varying legal statuses in the United States.
Minnesota Climate Mapping and Analysis Tool (MN CliMAT)
The Minnesota Climate Adaptation Partnership needed a way to analyze and share the vast troves of data produced from dynamically downscaling climate change projections. Ryan wrote Python pipelines to aggregate daily data into longer-term averages and calculate derived climate variables, then built the web application that displays over 100,000 climate variables and calculates average values for any area of interest.
Areas of Expertise
- Developing custom web applications for scientists, policy makers, and the public across a wide range of disciplines.
- Applying spatial tools to evaluate natural resource conservation, land management, and environmental policy initiatives.
- Analyzing environmental datasets and flood hazard metrics to support local government and community decision-making.
- Translating complex spatial and environmental datasets into accessible web maps, story maps, and visual reporting formats.