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- Wildfire risk & WUI exposure modeling that blends burn probability, suppression capacity, and socio-environmental vulnerability metrics.
- Remote sensing pipelines for monitoring fuel conditions, burn severity, and vegetation dynamics using Landsat, Sentinel, GEDI, and NAIP imagery.
- Open-source spatial analytics with reproducible workflows powered by R, Python, and Google Earth Engine.
- Story-driven communication through interactive maps, dashboards, and spatial storytelling that connect science with stakeholders.
- Understanding the role of Conservation Reserve Program lands in wildfire risk in the Great Plains.
- Building geospatial data products that support decision-making for conservation partners and agencies.
- Creating user-friendly tools that allow the public to engage with science.
| Data Science & Modeling | GIS & Remote Sensing | Cloud & Collaboration |
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- 🗺️ Interactive mapping with Leaflet, Shiny Apps, Mapbox for scenario planning and storytelling.
- 📊 Reproducible analytics packages and templates that combine Quarto, Git, and cloud storage.
- 🎙️ Workshops & talks on wildfire analytics, spatial R/Python workflows, and ethical data practices.
Explore more case studies, maps, and publications at noahweidig.com.
Always excited to collaborate on projects that make landscapes and communities more resilient.