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1.中国地质大学(北京)土地科学技术学院,北京,100083
2.中国地质大学(北京)河北省空天信息与智能化测绘重点实验室,北京,100083
3.教育部深空探测联合研究中心,月球与行星探测国际合作研究分中心,北京,100083
4.桂林理工大学测绘地理信息学院,广西 桂林,541006
Received:14 September 2026,
Published:05 November 2026
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才谨豪,徐箫剑,康志忠,等.科学价值定量化的天问三号着陆区多参数智能选址方法[J].武汉大学学报(信息科学版),2026,51(11):2436-2455.
CAI Jinhao,XU Xiaojian,KANG Zhizhong,et al.A Multi-parameter Intelligent Landing-Site Selection Method for Tianwen-3 with Quantitative Scientific-Value Assessment[J].Geomatics and Information Science of Wuhan University,2026,51(11):2436-2455.
才谨豪,徐箫剑,康志忠,等.科学价值定量化的天问三号着陆区多参数智能选址方法[J].武汉大学学报(信息科学版),2026,51(11):2436-2455. DOI:10.13203/j.whugis20260343
CAI Jinhao,XU Xiaojian,KANG Zhizhong,et al.A Multi-parameter Intelligent Landing-Site Selection Method for Tianwen-3 with Quantitative Scientific-Value Assessment[J].Geomatics and Information Science of Wuhan University,2026,51(11):2436-2455. DOI:10.13203/j.whugis20260343
火星是探寻地外天体潜在生命痕迹的重要窗口,天问三号火星采样返回任务将探寻潜在生命痕迹、认识火星宜居环境演化作为主要科学任务。着陆区选址不仅关系工程安全性,还直接决定能否获取保存潜在生命痕迹的高科学价值样品。然而,火星宜居环境受多种地质条件控制,部分地貌成因存在多解性,仅靠单一遥感观测难以准确表征科学价值。针对上述问题,提出一种科学价值定量化的天问三号着陆区多参数智能选址方法。研究综合多源遥感数据,对撞击坑、沙丘、凹锥、方山等地貌类型进行系统编目,并采用“工程约束—科学评价”双阶段流程:依据任务需求配置地形条件、表面障碍物、热物理条件等工程约束识别可行区域并构建候选椭圆,利用地貌、地层和矿物进行地质背景与演化历史、物质组成多样性、液态水活动证据、宜居环境与生命标志保存潜力以及后期改造与地质记录保存状态5个科学维度进行可追溯的评价筛选。最终在伊希斯平原尼罗堑沟群、茅尔斯峡谷出口及祝融号着陆区周边3个研究区的工程可行域内绘制54个候选着陆椭圆,分别筛选出1个优选椭圆,并设计多层级敏感性实验评价方法的可靠性。优选椭圆在多维科学价值上表现出较高优先级,可为天问三号任务着陆区优选及后续高分辨率复核提供可追溯、可定量的空间决策依据,也可为后续火星探测任务选址智能化提供方法参考。
Objectives
2
Mars is a key target in the search for potential extraterrestrial life and preserves abundant geological records of past aqueous activity and environmental evolution. The Tianwen-3 Mars sample-return mission aims to search for potential biosignatures and investigate the habitability of Mars and its evolutionary history. Landing-site selection is therefore required to satisfy engineering safety constraints while maximizing the scientific value of the returned samples. In particular
candidate sites should contain geological materials capable of recording ancient aqueous environments and preserving potential biosignatures. However
Martian habitability is controlled by multiple geological factors
including geological age
aqueous activity
material composition
depositional setting
and post-formation modification. In addition
some geomorphological features may have multiple possible origins
making it difficult to assess scientific value from a single remote-sensing observation. To address these issues
a multi-parameter intelligent landing-site selection method with quantitative scientific-value evaluation is developed for the Tianwen-3 mission.
Methods
2
Multi-source orbital remote-sensing and thematic datasets are integrated to characterize terrain
surface hazards
geological context
mineralogy
and surface physical properties. Representative landforms
including impact craters
dunes
pitted cones
mesas
channels
scarps
lobate features
and buried craters
are systematically inventoried. A two-stage workflow consisting of engineering-constraint screening and scientific-value evaluation is then implemented. In the engineering stage
constraints related to topography
surface obstacles
impact-related hazards
and thermophysical properties are parameterized
configured according to mission requirements
and applied to identify feasible regions. Mission-scale landing ellipses are subsequently generated within the engineering-feasible domain. In the scientific stage
geomorphological
stratigraphic
and mineralogical evidence within each candidate ellipse is quantitatively and traceably evaluated in five dimensions: geological context and evolutionary history
diversity of material composition
evidence for liquid-water activity
habitability and biosignature-preservation potential
and post-formation modification and preservation of geological records. The resulting multidimensional scores are integrated to rank candidate ellipses within each study region.
Results
2
The method is applied to three candidate regions with contrasting geological settings: Isidis Planitia-Nili Fossae
the outlet region of Mawrth Vallis
and the surrounding area of the Zhurong landing site. A total of 54 engineering-feasible candidate landing ellipses are generated
including 12 in Isidis Planitia-Nili Fossae
12 in Mawrth Vallis
and 30 in the Zhurong landing-site region. One preferred ellipse is identified in each region. The preferred candidates show high priorities in the multidimensional scientific-value assessment
although the dominant geological evidence differs among the three regions. The stability of the evaluation results is further examined through sensitivity analysis of engineering parameters
adjustment of scientific-objective priorities
and perturbation of geomorphological inventory uncertainty.
Conclusions
2
The proposed method converts engineering requirements
geological evidence
and mission-oriented scientific preferences into an explicit and quantitative landing-site selection workflow. It is configurable and can incorporate mission requirements and expert knowledge. Engineering feasibility is treated as a prerequisite rather than as a factor that can be compensated for by high scientific value
while scientific ranking is performed only among engineering-feasible candidates. The integration of multiple geological evidence types reduces dependence on any single remote-sensing interpretation and enables the scientific ranking to be traced back to observable geomorphological
stratigraphic
and mineralogical features. The method therefore provides a quantitative and traceable spatial-decision framework for Tianwen-3 landing-site selection
supports subsequent high-resolution verification
and offers a transferable methodological reference for intelligent landing-site selection in future Mars sample-return and life-detection missions.
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