The characteristics of dynamic construction sites increase the difficulty of collecting the high-quality geometric data necessary to achieve construction management activities. This paper introduces a new autonomous framework for 3D geometric data collection in a dynamic cluttered environment using an unmanned ground vehicle (UGV) and an unmanned aerial vehicle (UAV). This method first deploys UAV to collect photo images of a site and builds a point cloud of the 3D terrain of the site, including obstacle information. A mesh grid is then created from the UAV-generated point cloud, and simulation for laser-scan planning is conducted to determine the stationary laser-scan positions at which a mobile robot can collect data with less occluded views while capturing all crucial geometric information. Finally, optimal paths for the UGV to navigate among the estimated scan positions are generated. Promising test results regarding data accuracy and collection time show that the proposed collaborative UAV-UGV approach can significantly reduce human intervention and provide technologies for enabling construction site to be frequently monitored, updated, and analyzed for timely decision-making.