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Mineral Detection Based on Hyperspectral Remote Sensing Imagery on
Mars: From Detection Methods to Fine Mapping |
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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. 1.Methods for Martian mineral detection We survey and analyze nearly 20 years of methods to explore their core contributions. As is shown in table 1, we summarize the Martian mineral detection methods based on hyperspectral remote sensing into two main categories: methods based on pixel-level detection and methods based on subpixel detection.
2.Experiment We used a set of synthetic data and some CRISM images to verify and analyze the performance of the Martian mineral detection methods based on hyperspectral remote sensing. The identification results for this experiment are listed in Table 2. The abundance results for two images for the comparison are shown in Fig. 1. It is apparent that the effects of VCA-FCLS and FAHU are relatively good. The estimated abundance value of FAHU is higher, and it can correspond well to the spatial distribution of the minerals.
3.Applications By collecting nearly 150 published papers related to the detection of Martian minerals based on hyperspectral remote sensing from 2004 to 2023, we classified the detection results into 31 categories, as shown in in Fig. 2, based on the classification standard of the MICA library.
4.Download We provide download links of the data and source code in this experiment. You can click the link below to download them: ● Baidu Drive: download ● Google Drive: download 5.Copyright The copyright belongs to Intelligent Data Extraction, Analysis and Applications of Remote Sensing(RSIDEA) academic research group, State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing (LIESMARS), Wuhan University, China. The data and source code only can be used for academic purposes and need to cite the following paper, but any commercial use is prohibited. Any form of secondary development, including annotation work, is strictly prohibited for this dataset. Otherwise, RSIDEA of Wuhan University reserves the right to pursue legal responsibility. Tian Ke, Yanfei Zhong, Mi Song, Xinyu Wang, Liangpei Zhang. Mineral Detection Based on Hyperspectral Remote Sensing Imagery on Mars: From Detection Methods to Fine Mapping[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2024 (Under Review). 6.Contact If you have any the problem or feedback, please contact: Ms. Tian Ke: ketian@whu.edu.cn Prof. Yanfei Zhong: zhongyanfei@whu.edu.cn |
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