Abstract
We demonstrate an end-to-end application of the in-house deep learning-based surface modelling system, called MADNet, to produce three large area 3D mapping products from single images taken from the ESA Mars Express’s High Resolution Stereo Camera (HRSC), the NASA Mars Reconnaissance Orbiter’s Context Camera (CTX), and the High Resolution Imaging Science Experiment (HiRISE) imaging data over the ExoMars 2022 Rosalind Franklin rover’s landing site at Oxia Planum on Mars. MADNet takes a single orbital optical image as input, provides pixelwise height predictions, and uses a separate coarse Digital Terrain Model (DTM) as reference, to produce a DTM product from the given input image. Initially, we demonstrate the resultant 25 m/pixel HRSC DTM mosaic covering an area of 197 km × 182 km, providing fine-scale details to the 50 m/pixel HRSC MC-11 level-5 DTM mosaic. Secondly, we demonstrate the resultant 12 m/pixel CTX MADNet DTM mosaic covering a 114 km × 117 km area, showing much more detail in comparison to photogrammetric DTMs produced using the open source in-house developed CASP-GO system. Finally, we demonstrate the resultant 50 cm/pixel HiRISE MADNet DTM mosaic, produced for the first time, covering a 74.3 km × 86.3 km area of the 3-sigma landing ellipse and partially the ExoMars team’s geological characterisation area. The resultant MADNet HiRISE DTM mosaic shows fine-scale details superior to existing Planetary Data System (PDS) HiRISE DTMs and covers a larger area that is considered difficult for existing photogrammetry and photoclinometry pipelines to achieve, especially given the current limitations of stereo HiRISE coverage. All of the resultant DTM mosaics are co-aligned with each other, and ultimately with the Mars Global Surveyor’s Mars Orbiter Laser Altimeter (MOLA) DTM, providing high spatial and vertical congruence. In this paper, technical details are presented, issues that arose are discussed, along with a visual evaluation and quantitative assessments of the resultant DTM mosaic products.
Highlights
Large area, high-resolution, three-Dimensional (3D) mapping of the Martian surface is essential for performing key science investigations of the generation and evolution of the planet’s surface, and critical for supporting existing and future surface robotic missions as well as human exploration
The 25 m/pixel High Resolution Stereo Camera (HRSC) MADNet Digital Terrain Model (DTM) mosaic
The 12 m/pixel CTX MADNet DTM mosaic
Summary
High-resolution, three-Dimensional (3D) mapping of the Martian surface is essential for performing key science investigations of the generation and evolution of the planet’s surface, and critical for supporting existing and future surface robotic missions as well as human exploration. The large area lower-resolution 3D mapping work usually uses the Mars Express’s. High Resolution Stereo Camera (HRSC) data at 12.5–50 m/pixel [1] producing photogrammetric digital terrain models (DTMs) at 50–150 m/pixel [2,3,4,5,6,7], or uses the Mars Reconnaissance Orbiter (MRO) Context Camera (CTX) data at 6 m/pixel [8] producing DTMs at. The small area high-resolution 3D mapping work usually employs the MRO High Resolution Imaging Science Experiment (HiRISE) data at. Trace Gas Orbiter (TGO) Colour and Stereo Surface Imaging System (CaSSIS) data at 4–6 m/pixel [21] producing DTMs at 12–18 m/pixel using photogrammetry [22] or at 4 m/pixel using photoclinometry (at the pixel-level) or at 1 m/pixel using superresolution restoration assisted photoclinometry [23] (at the sub-pixel level). Lower-resolution data such as HRSC has better stereo coverage as it is inherently a stereo mapping instrument, whereas the main high-resolution data to date (HiRISE) is only capable of targeted stereo
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