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

TL;DR

This paper introduces an automatic, efficient method for generating accurate digital terrain models from large point cloud datasets, suitable for terrestrial sensing and real-time VR applications.

Contribution

It presents a novel terrain modeling technique that automatically creates realistic DTMs from diverse point cloud data, enabling real-time rendering in VR environments.

Findings

Runs efficiently on large-scale point clouds

Produces physically realistic digital terrain models

Supports real-time VR rendering

Abstract

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.