Deriving a minimum set of viewpoints for maximum coverage over any given digital elevation model data

This paper introduces how to automatically derive a minimum set of viewpoints for maximum coverage over a large scale of digital terrain data. This is a typical data and computation-intensive research covering a series of geocomputation tasks that have not been implemented efficiently or optimally in prior works. This paper introduces a three-step computational solution to resolve the problem. For any given digital elevation model (DEM) data, automatic generation of control viewpoints is the first step through map algebra calculation and hydrological modeling approaches. For each viewpoint, the viewshed calculation then has to be implemented. The combined viewshed derived from the viewshed of all viewpoints establishes the maximum viewshed coverage of the given DEM. Finally, detecting the minimum set of viewpoints for the maximum coverage is a Non-deterministic Polynomial-time hard problem. The outcome of the computation has broader societal impacts since the research questions and solutions can be adapted into real-world application and decision-making practice, such as the distribution, optimization and management of telecommunication infrastructure and wildfire observation towers, and military tactics and operations dependent upon landscape and terrain features.