Research on Key Technologies and Applications of Feature Extraction and Knowledge Mining in Planetary Exploration

doi:10.11871/jfdc.issn.2096-742X.2025.04.001

Abstract

Abstract:

[Purpose] This article focuses on the demand for deep mining and intelligent feature extraction of planetary exploration data. It investigates key technologies and applications for extracting feature information and knowledge mining from massive remote sensing data obtained during various planetary explorations. [Method] This study breaks through the challenges of reconstructing, fusing, and visualizing multi-source and heterogeneous planetary data, addressing the limitations of insufficient imaging information from single sensor to generate high-quality remote sensing images rich in spatial and spectral information. Spectral characteristic parameters of lunar and martian minerals are extracted from visible near-infrared spectroscopic data, enabling the inversion of the content and distribution of elements and minerals on the lunar and martian surface. Additionally, microwave and radar data are utilized to obtain information regarding the thickness and physical properties of lunar regolith, along with the subsurface structure of typical regions on the Moon and Mars. By employing images and elevation data of the Moon and Mars, multi-scale terrain factors on the surface are calculated, and typical morphological features are automatically extracted using deep learning techniques. [Results] Finally, an integrated platform for displaying and analyzing morphological features, material composition information, and subsurface structures has been established. Furthermore, a planetary data analysis and mining software tool with independent intellectual property rights is developed, which will be released by National Space Science Data Center and Planetary Data System (PDS) Laboratory of Shandong University at Weihai, to support planetary data mapping and geological evolution researches.

Key words: planetary exploration data, knowledge mining, chemical and mineralogical composition, subsurface structure, morphological features, visualization, reconstruction and fusion

LING Zongcheng, LI Bo, WEI Guangfei, GUO Dijun, LYU Yingbo, LIU Changqing, ZHU Kai, CHEN Jian, ZHAO Qiang, LI Jing, HU Guoping, WANG Jiao, LIU Jianzhong. Research on Key Technologies and Applications of Feature Extraction and Knowledge Mining in Planetary Exploration[J]. Frontiers of Data and Computing, 2025, 7(4): 3-19, https://cstr.cn/32002.14.jfdc.CN10-1649/TP.2025.04.001.

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光谱参数名称	光谱参数物理意义
BD_1330	斜长石Fe²⁺吸收参数
LCPINDEX	低钙辉石参数
HCPINDEX	高钙辉石参数
OLINDEX	橄榄石参数
BD_2265	黄钾铁矾、水铝矿、绿脱石
BD_2290	Mg/Fe-OH或CO₂冰
BD_2355	绿泥石、葡萄石、绿纤石
MIN_2200	高岭石
MIN_2250	蛋白石
BD_2100	一水硫酸盐中的H₂O
BD_2230	羟基硫酸铁
SINDEX	含水硫酸盐
BD_2265	黄钾铁矾、水铝矿、酸性淋滤的绿脱石
BD_2500	碳酸镁
MIN_2295_2480	碳酸镁
MIN_2345_2537	碳酸钙/铁
BD_1400	H₂O和-OH
BD_1750	H₂O
BD_1900	H₂O
BD_1500	H₂O冰
BD_1435	CO₂冰
BD_2290	Mg/Fe-OH或CO₂冰
BD_2165	Al-OH
BD_2190	Al-OH
BD_2210	Al-OH
BD_2250	Al-OH和Si-OH
BD_2250	Al-OH和Si-OH