Wildfire Propagation Modeling using Satellite-Derived Parameters and Generalized Elliptical Frames

TL;DR

This paper presents a satellite-based, geometric modeling framework for wildfire spread that adapts to data availability, accurately simulating fire propagation using elliptical frames and hybrid strategies.

Contribution

It introduces a novel hybrid geometric approach for wildfire modeling that functions effectively in both data-rich and data-limited scenarios using satellite observations.

Findings

Successfully modeled wildfire propagation with satellite data

Reproduced key features of the Eaton Fire spread

Demonstrated robustness in data-limited conditions

Abstract

Wildfires pose significant threats to ecosystems and communities, yet accurately modeling fire spread remains challenging, particularly in regions where environmental and fuel data are scarce or unavailable. This study introduces an innovative conceptual and methodological framework for simulating wildfire propagation and estimating the rate of spread using a hybrid geometric and data-driven approach that relies exclusively on multi-source satellite observations. The framework integrates thermal fire-front detections, atmospheric conditions, and vegetation indices using two complementary geometric modeling strategies. The first strategy applies the Huygens principle, where generalized elliptical frames are expanded locally at every point along the fire perimeter, and their combined envelope forms the evolving wavefront. This method is best suited for situations in which environmental variables are available and can be incorporated to refine the anisotropic spread function. The second strategy relies solely on the generalized elliptical frames themselves; for each time step, an elliptical frame is constructed from the inferred head and back rates of spread and wind, and the burned area is obtained by enclosing the region determined by these curves. Together, these two methods provide a flexible toolkit that adapts to both data-rich and data-limited conditions while retaining a unified geometric interpretation of wildfire spread. To demonstrate the applicability of the method, we present a case study based on the Eaton Fire, January 2025, using publicly available multi-day satellite imagery. Despite the absence of complete operational datasets for that event, the model driven only by satellite-derived parameters reproduces key qualitative features of the observed propagation pattern, underscoring the flexibility and robustness of the proposed approach in data-limited contexts.