While fire is an important ecological process in the western United States, wildfire size and severity have increased over recent decades as a result of climate change, historical fire suppression, and lack of adequate fuels management. Due to the urgency to build ecosystem resilience and protect life and property, land managers implement fuel management programs. Technology used to quantify ladder fuels, which bridge the gap between the surface and canopy, and lead to more severe canopy fires, can inform management treatments to reduce future wildfire risk. In this study, we evaluated several remote sensing techniques and field measurements to quantify ladder fuels and related ladder fuel metrics to wildfire burn severity. Ladder fuel data at 1-m strata from 1-8 m were collected using a photo banner, a terrestrial laser scanner (TLS), a handheld-mobile laser scanner (HMLS), an unoccupied aerial system (UAS) with a multispectral camera and Structure from Motion (SfM) processing (UAS-SfM), and an airborne laser scanner (ALS) in 35 plots in oak woodlands in Sonoma County, California, USA prior to the occurrence of natural wildfires. Canopy base height (CBH) was estimated in the field, and post-wildfire burn severity was calculated using the Relativized delta Normalized Burn Ratio (RdNBR). The linear relationships between ladder fuel metrics at each stratum collected via different methods were compared using Pearson’s correlation (r) and RdNBR prediction via ladder fuel estimation was evaluated with a generalized linear model (GLM). All methods were not consistently related to each other, unless CBH class was included as a means of categorizing structural differences among plots. The UAS-SfM approach often could not produce measurements below 8 m due to lack of below-canopy detection, and, therefore, is highly limited for ladder fuels estimation in oak woodland and mixed conifer forests. The most common ladder fuels strata included in the burn severity model were 1-2 m and 3-4 m. The most predictive models included data from TLS and ALS with R2 of 0.67 and 0.66, respectively. By accounting for interactions between ladder fuels, CBH, and burn severity, diverse remote sensing approaches can be used to estimate and validate ladder fuels.