Master Thesis Defense by Tommaso Ferrari
Title: "Integration of Image Data for Improvement of Laser Altimetry of Mars Using Inverse Problems".
Mars is one of Earth’s closest hospitable neighbors, with an average distance of 230 million km, with biannual oppositions bringing the two planets within 100 million km of each other. It has similar amounts of sunlight, very similar day length and an atmosphere and temperature that can be modified to be habitable and to be able to sustain plant life.
Elon Musk’s SpaceX is already planning human missions on Mars for the oppositions of 2024-2026 or more realistically 2029 (possibly due to delays from a lawsuit and Coronavirus), and eventually martian colonization.
Mapping martian topographical features with high resolution is a fundamental step for further investigations, providing the necessary conditions for studying caves, lava channels, craters and other interesting geophysical features. This would in turn provide useful information, helping the decision making process for human exploration and exploitation of resources .
At the time of this writing, the information we have on Mars altimetry is the one gathered by the Mars Orbiter Laser Altimeter (MOLA). This measurement does however have very low resolution at 128 ppdg (pixels per degree) for both latitude and longitude, which means that features smaller than 1 pixel (463 meters at the equator) are not seen.
On the other hand, we do have access to image data from the Thermal Emission Imaging System (THEMIS), which can look at both visible and infrared spectra of light and has image resolution varying around 600 ppdg at the equator (infrared) or around 3000 ppdg (visible).
Following Fernandes and Mosegaard’s work we are going to use an inverse problem for- mulation based on Tarantola’s works to combine the two datasets in order to obtain an estimate of topography at the resolution of THEMIS imagery. The method exploits the relationship between the incidence angle and shading to estimate surface gradients, and then uses these gradients (and the MOLA data as a constraint) to calculate the topography.
Censor: Christian Schiøtt, HESS Denmark