This study proposes a sampling method for ground-truthing LiDAR-derived data that will allow researchers to verify or predict the accuracy of results over a large area. Our case study is focused on a 24 km2area centered on the site of Yaxnohcah in the Yucatan Peninsula. This area is characterized by a variety of dense tropical rainforest and wetland vegetation zones with limited road and trail access. Twenty-one 100 x 100 m blocks were selected for study, which included examples of several different vegetation zones. A pedestrian survey of transects through the blocks was conducted, recording two types of errors. Type 1 errors consist of cultural features that are identified in the field, but are not seen in the digital elevation model (DEM) or digital surface model (DSM). Type 2 errors consist of features that appear to be cultural when viewed on the DEM or DSM, but are caused by different vegetative features. Concurrently, we conducted an extensive vegetation survey of each block, identifying major species present and heights of stories. The results demonstrate that the lidar survey data are extremely reliable and a sample can be used to assess data accuracy, fidelity, and confidence over a larger area.