The exploration of the Solar system from Earth in search of new living spaces will provide new options and possibilities for the survival and development of humankind, where the understanding of their environment, and their resource utilization are essential stages to develop. In the future, when space technology is highly developed and the cost of interplanetary transportation is greatly reduced, planets such as Saturn, Mars and Jupiter will become the "islands" in the Solar system for human settlements. The identification of such resources usually done through exploration, monitoring with sensors and spectral analysis is needed. The development of techniques for satellite surveying to organize the surface of such celestial bodies to generate maps with resource information is part of the first steps for the exploration. For the purpose of a highly accurate 3D modeling of the celestial body and a flat 2D map presentation, the surface structure of the celestial body should be understood by using geometry as well as different types of map projection methods, that will be exploited by the satellites. Different geometrical models and algorithms together with information from sensing systems can be used as much as possible in order to accurately locate the position of on-surface vehicles that could perform in-situ analysis of surface samples. Thus, the combination of the 2D/3D techniques with localization information obtained from sensors, and its use through the satellites, creates a map of the distribution of the celestial body resources. In this article, a projection method based on such a combination and other conventional techniques to achieve better accuracy and efficiency during the process of mapping and projection of a celestial body surface is presented.
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Celestial body surface mapping for resource discovery by using satellites
Published: 15 November 2023 by MDPI in 10th International Electronic Conference on Sensors and Applications session Sensor Networks, IoT and Structural Health Monitoring
https://doi.org/10.3390/ecsa-10-15998 (registering DOI)
Keywords: Projection mapping; Localization algorithm; Surface construction