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Wildfire GOFER confidence heatmap viewer

Wildfire Modeling

Updated Feb 2026

Git Repo
PythonJavaScriptREarth Enginescikit-learn

Wildfire Modeling is a research workflow for collecting wildfire-related geospatial data, converting it into GOFER-style JSON, and running local regression analyses over fire spread and continuation. It sits between raw remote-sensing data and downstream modeling experiments.

Earth Engine download and normalization pipeline

Locational spread + continuation regression workflows

Lightweight local viewer for GOFER-style JSON outputs

What I built

  • CLI scripts for downloading GOES confidence stacks and aligned RTMA meteorology
  • Conversion tools that normalize geospatial outputs into modeling-friendly JSON
  • Regression workflows and notebooks for single-fire and multi-fire analysis

How it works

  1. 1Download wildfire confidence stacks and aligned meteorology
  2. 2Convert outputs into GOFER-style JSON time series
  3. 3Run locational regressions and inspect outputs through notebooks or the local viewer

Results

  • ✓Repeatable research workflow from Earth Engine exports to regression outputs
  • ✓Supports both single-fire analysis and broader multi-fire experiments

Next steps

  • Tighten environment bootstrapping and add clearer example outputs
  • Expand the multiresolution data path and result visualization