The surface of the moon has learned to map with an unprecedented level of accuracy

The surface of the moon has learned to map with an unprecedented level of accuracy

By studying the limestone formation of Stevens Klint in Denmark, scientists have developed a method for interpreting shadows in images for more accurate topography. It is much faster and less labour-intensive. The results are published in Planetary and Space Science.

Mapping the shapes of the Moon is of great interest and importance for future human settlements and resource development; one of the first steps is to map topography with great detail and resolution; however, the Lunar Orbiter laser altimeter provides maps of low resolution heights compared to the size of detailed geological objects.

To improve resolution, scientists have developed a new method of increasing the scale of topography maps using images from the Lunar Reconnaissance Orbiter camera. Scientists have used the link between topography gradients and the degree of shadowing of incoming sunlight. Unlike previously published methods, the new approach is based on probabilistic linear inverse theory, and its computational efficiency is very high through the Sylvester equation. The method works with several images and includes albedo variations.

The surface of the Moon and rocky planets, in particular Mars, is of great interest to solar system researchers. In addition, detailed mapping is important for the safe landing of rovers. For example, if a sailor cannot see the details of the surface, it can easily get stuck in the sand or hit the rocks, and accurate topography of the surface gives rovers the opportunity to explore interesting geological formations.

The problem is that so far the methods of analysing images from orbital spacecraft have required enormous computing capacity.

The method of examining shades of shadows has existed before, but has been computationally ineffective. The new approach uses more direct and accurate computations, and is independent of the whole set of parameters that are entered into the computer.