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The identification and modeling of the terrain from point cloud data is animportant component of Terrestrial Remote Sensing (TRS) applications. The mainfocus in terrain modeling is capturing details of complex geological featuresof landforms. Traditional terrain modeling approaches rely on the user to exertcontrol over terrain features. However, relying on the user input to manuallydevelop the digital terrain becomes intractable when considering the amount ofdata generated by new remote sensing systems capable of producing massiveaerial and ground-based point clouds from scanned environments. This articleprovides a novel terrain modeling technique capable of automatically generatingaccurate and physically realistic Digital Terrain Models (DTM) from a varietyof point cloud data. The proposed method runs efficiently on large-scale pointcloud data with real-time performance over large segments of terrestriallandforms. Moreover, generated digital models are designed to effectivelyrender within a Virtual Reality (VR) environment in real time. The paperconcludes with an in-depth discussion of possible research directions andoutstanding technical and scientific challenges to improve the proposedapproach.

An Automatic Digital Terrain Generation Technique for Terrestrial Sensing and Virtual Reality Applications