Recent developments in Unmanned Aerial Vehicles (UAVs) have made them ideal tools for remotely monitoring agricultural fields. Complementary advancements in computer vision have enabled automated post-processing of images to generate dense 3D reconstructions in the form of point clouds. In this paper we present a monitoring pipeline that uses a readily available, low cost UAV and camera for quickly surveying a winter wheat field, generate a 3D point cloud from the collected imagery and present methods for automated crop height estimation from the extracted point cloud and compare our estimates with those using standardized techniques.