Quantifying post-fire differences in forest structure and aboveground biomass using the TECIS full-waveform LiDAR system

Wildfires can substantially alter forest vertical structures and carbon stocks. However, the characterization of post-fire forest structure and aboveground biomass (AGB) differences at large spatial scales remains difficult because observations of the three-dimensional forest structure are still limited. This study aimed to examine whether the terrestrial ecosystem carbon inventory satellite (TECIS, also referred to as Goumang) full-waveform light detection and ranging (LiDAR) system of China can capture post-fire vertical structural differences and forest type-specific AGB variations at the footprint-level. We developed a hierarchical framework linking data from field plots, airborne LiDAR observations, TECIS footprints, and Sentinel-1/2 imagery. Within the airborne LiDAR coverage range, airborne waveforms were simulated to evaluate waveform consistency and to compare TECIS-derived structural parameters with airborne LiDAR references. The TECIS-derived canopy height results yielded a coefficient of determination (R 2 ) of 0.65 with a relative root mean square error (rRMSE) of 30.25% against the airborne LiDAR reference data. With a field-calibrated airborne LiDAR AGB surface as the intermediate reference, we developed forest type-specific TECIS footprint-level AGB models, which achieved R 2 values ranging from 0.65 to 0.75, with an overall R 2 value of 0.72 and an rRMSE of 48.93%. On the basis of these footprint-level estimates, the relative height (RH) profiles revealed clear burned–unburned differences, particularly in the middle and upper canopy layers (RH75–RH95). The mean AGB values in burned areas were lower than those in unburned areas by 52.6%, 50.1%, and 41.6% for coniferous, mixed, and broadleaf forests, respectively. To extend the footprint observations to continuous maps, the TECIS-derived footprint estimates were integrated with Sentinel-1/2 data. The final Sentinel-derived AGB map revealed an R 2 value of 0.64, an RMSE of 27.69 Mg/ha, and an rRMSE of 34.71% against independent field plot data. Overall, the TECIS system effectively captured post-fire structural differences and supported footprint-level and regional assessments of the forest structure and AGB under post-fire conditions.