A GIS-based spatial data structure for integrating multi-resolution terrain data from lunar orbiter and rover: Application to Lunar Rover Path Planning and Operation Soomin Kim(a), Jaeyoung Lee(a), Junho Gong(b), Taehoon Kim(b), Hyusung Shin(b), Sungchul Hong(a*)
a) Program in Smart City Engineering, Inha University, Incheon 22212, Republic of Korea
* schong[at]inha.ac.kr
b) Department of Future & Smart Construction Research, Korea Institute of Civil engineering and Building Technology, Goyang 10223, Republic of Korea
Abstract
The discovery of water-ice and rare resources on the lunar surface, particularly within the permanent shadowed regions, has increased international interest in robotic exploration, ultimately aiming at constructing the lunar base. Lunar exploration primarily relies on observation datasets collected by lunar orbiters, of which terrain data is used to support landing site selection and global path planning. However, the inherently insufficient resolution of orbital terrain data restricts their applicability for rover operations and infrastructure development. Therefore, to facilitate high-precision terrain analysis and to ensure the safe and efficient operation of rovers, it is essential to incorporate high-resolution terrain data acquired during rover traverses.
This study proposes a GIS-based spatial data structure that integrates both low- and high- resolution terrain data from lunar orbiters and rovers. The proposed structure is a quadtree-based 8-directional network that allows hierarchical integration of terrain data at different resolutions and provides a topological basis for fine-grained path planning. Each node stores elevation, and each link encodes distance and slope. Path planning is performed using the A* algorithm, and an initial route is generated from orbital data. As the rover progresses, high-resolution terrain data updates the terrain and path. Moreover, the network can be converted into a mesh, which supports 3D visualization of terrain and traversal paths and enhances interpretability.
The proposed structure was validated on a simulated lunar terrain. Using high-resolution terrain data acquired along the rover^s path, obstacles undetected in the low-resolution orbital terrain data were successfully identified, and the planned path was updated. Furthermore, the rover-based terrain data was confirmed to be integrated with the orbit-based terrain data. The proposed structure can incorporate additional observational datasets such as temperature and resource distribution. This capability is expected to support decision-making in unmanned rover navigation, lunar terrain modeling, and infrastructure development.
Keywords: spatial data structure, GIS, lunar exploration
