Mineral detection based on hyperspectral remote sensing imagery on Mars: From detection methods to fine mapping

Abstract

Hyperspectral remote sensing is a commonly used technical means for mineral detection on the Martian surface, which has important implications for the study of Martian geological evolution and the study for potential biological signatures. The increasing volume of Martian remote sensing data and complex issues such as the intimate mixture of Martian minerals make research on Martian mineral detection challenging. This paper summarizes the existing achievements by analyzing the papers published in recent years and looks forward to the future research directions. Specifically, this paper introduces the currently used hyperspectral remote sensing data of Mars and systematically analyzes the characteristics and distribution of Martian minerals. The existing methods are then divided into two groups, according to their core idea, i.e., methods based on pixels and methods based on subpixels. In addition, some applications of Martian mineral detection at global and local scales are analyzed. Furthermore, the various typical methods are compared using synthetic and real data to assess their performance. The conclusion is drawn that approach based on spectral unmixing is more applicable to areas with limited and unknown mineral categories than pixel-based methods. Among them, the fully autonomous hyperspectral unmixing method can improve the overall accuracy in real CRISM images and has great potential for Martian mineral detection. The development trends are analyzed from three aspects. Firstly, in terms of data, a more complete spectral library, covering more spectral information of the Martian surface minerals, should be constructed to assist with mineral detection. Secondly, in terms of methods, spectral unmixing methods based on a nonlinear mixing model and a new generation of data-driven detection paradigms guided by Mars mineral knowledge should be developed. Finally, in terms of application, the global mapping of Martian minerals toward a more intelligent, global scale, and refined direction should be targeted in the future. The data and source code in the experiment are available at http://rsidea.whu.edu.cn/Martian_mineral_detection.htm.