A representation of the Earth’s surface that includes all objects upon it is a crucial form of geospatial data. This representation encompasses natural terrain features such as vegetation and bare earth, as well as man-made structures like buildings and bridges. The resultant dataset provides elevation values for these features, generating a comprehensive depiction of the visible above-ground landscape. For example, a model of a city would show not only the ground level, but also the heights of skyscrapers, trees, and power lines.
This type of model offers several advantages in a variety of applications. It is fundamental for urban planning, allowing accurate visualization and analysis of the built environment. It also plays a vital role in telecommunications, particularly in optimizing signal propagation and network design. Furthermore, this type of model is critical for line-of-sight analysis, enabling assessments of visibility across the landscape for various purposes, from military applications to environmental monitoring. Its development stems from advancements in remote sensing technologies, particularly lidar and photogrammetry, which have enabled efficient and accurate data collection.
