Characterizing wildfire behavior with ECOSTRESS land surface temperature across four California case studies

Since 2000, wildfires in the western United States have increased in both frequency and intensity due to hydro-meteorological shifts, prolonged drought, and expanded human activity. Although geostationary systems enable rapid detection and moderate-resolution sensors offer broad coverage, a gap persists for high-spatial-resolution thermal observations that can assess fine-scale fire behavior. The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) provides 70-meter land surface temperature (LST) observations with multi-day revisit intervals, providing enhanced spatial detail for active-fire analysis. In this study, we evaluate the capability of ECOSTRESS Level 2 LST data, which uses 5 thermal bands, to characterize wildfire behavior across four California fires: Carr (2018), Kincade (2019), August Complex (2020), and Dixie (2021). We developed a consistent framework to identify hotspots (LST ≥ 60 ° C ), estimate a satellite-derived rate-of-spread (ROS) proxy using the 95th percentile radial expansion from ignition, and assess relationships between mean active-fire temperature and mean post-fire burn severity (dNBR). Across all fires, median hotspot temperatures ranged from 62 to 77 °C, while 95th percentile values ranged from 117 to 179 °C, indicating right-skewed radiometric distributions. The ROS proxy showed directional variability, with median values typically between 0.05 to 3 km day −1 and substantial heterogeneity among quadrants. Regression indicates consistent positive relationships between mean active-fire temperature and mean burn severity, with R 2 values from 0.51 to 0.88. These relationships were stronger in smaller, short-duration fires. Additionally, the ECOSTRESS derived hotspots were validated against Fire Radiative Power (FRP) data derived from VIIRS, and it was demonstrated that ECOSTRESS-derived thermal anomalies are spatially coherent with independently derived FRP intensity patterns. Our findings indicate that ECOSTRESS provides valuable high-spatial-resolution thermal observations that can resolve fire growth patterns and link active-fire thermal dynamics to subsequent burn severity. • This work proposes a novel framework to analyze ECOSTRESS LST products as a wildfire monitoring tool. • The relationship between ECOSTRESS-derived high temperature hotspots and burn severity is demonstrated across four California case studies and the hotspots are validated against Fire radiative Power derived from VIIRS. • ECOSTRESS LST enables high-resolution monitoring of wildfire spread and quantification of rate of spread during the active fire phase.