The identification and modeling of the terrain from point cloud data is an
important component of Terrestrial Remote Sensing (TRS) applications. The main
focus in terrain modeling is capturing details of complex geological features
of landforms. Traditional terrain modeling approaches rely on the user to exert
control over terrain features. However, relying on the user input to manually
develop the digital terrain becomes intractable when considering the amount of
data generated by new remote sensing systems capable of producing massive
aerial and ground-based point clouds from scanned environments. This article
provides a novel terrain modeling technique capable of automatically generating
accurate and physically realistic Digital Terrain Models (DTM) from a variety
of point cloud data. The proposed method runs efficiently on large-scale point
cloud data with real-time performance over large segments of terrestrial
landforms. Moreover, generated digital models are designed to effectively
render within a Virtual Reality (VR) environment in real time. The paper
concludes with an in-depth discussion of possible research directions and
outstanding technical and scientific challenges to improve the proposed
approach