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In the pine savannas of the southeastern United States, prescribed fire is commonly used to manipulate understory structure and composition. Understory characteristics have traditionally been monitored with field sampling; however, remote sensing could provide rapid, spatially explicit monitoring of understory dynamics. We contrasted pre- vs. post-fire understory characteristics collected with fixed area plots with estimates from high-density LiDAR point clouds collected using the unmanned aerial vehicle (UAV)-borne GatorEye system. Measuring within 1 × 1 m field plots (<i>n</i> = 20), we found average understory height ranged from 0.17–1.26 m and biomass from 0.26–4.86 Mg C ha⁻¹ before the fire (May 2018), and five months after the fire (November 2018), height ranged from 0.11–1.09 m and biomass from 0.04–3.03 Mg C ha⁻¹. Understory heights estimated with LiDAR were significantly correlated with plot height measurements (<i>R</i>² = 0.576, <i>p</i> ≤ 0.001). Understory biomass was correlated with in situ heights (<i>R</i>² = 0.579, <i>p</i> ≤ 0.001) and LiDAR heights (<i>R</i>² = 0.507, <i>p</i> ≤ 0.001). The biomass estimates made with either height measurement did not differ for the measurement plots (<i>p</i> = 0.263). However, for the larger research area, the understory biomass estimated with the LiDAR indicated a smaller difference after the burn (~12.7% biomass reduction) than observed with in situ measurements (~16% biomass reduction). The two approaches likely differed because the research area’s spatial variability was not captured by the in-situ measurements (0.2% of the research area measured) versus the wall-to-wall coverage provided by LiDAR. The additional benefit of having spatially explicit measurements with LiDAR, and its ease of use, make it a promising tool for land managers wanting greater spatial and temporal resolution in tracking understory biomass and its response to prescribed fire.