A Multi-Source Remote Sensing-Based Burn Severity Assessment Method for Mountainous Transmission Line Wildfires: A Case Study in Beijing

Frequent wildfire incidents pose risks to high-voltage transmission line safety. To quantify wildfire burn severity and spatial extent, this study proposes a multi-source remote sensing-based monitoring and assessment method, implemented in wildfire surveillance practices in Beijing. The research integrates MCD64A1 wildfire datasets and MCD12Q1 land use data with Landsat 8 remote sensing imagery to establish a wildfire identification and burn severity assessment model. Specifically, MCD64A1 data were first employed to determine the temporal range and spatial distribution of wildfire events, followed by acquisition of contemporaneous Landsat 8 image data. Algorithmically, multi-band information from Landsat 8 imagery was utilized to compute two spectral indices for burn severity assessment: the differenced Normalized Burn Ratio (dNBR) and Relative differenced Normalized Burn Ratio (RdNBR). Scientific thresholds were established to identify and evaluate burn intensity, with spectral indices demonstrating positive correlations with combustion severity. Ultimately, wildfire burn severity index maps were generated at 30-meter spatial resolution. Validation through comparisons with MODIS FIRMS active fire data and Beijing wildfire incident reports confirmed the method's applicability for regional wildfire monitoring.