Probabilistic Safe Landing Site Selection Based on Estimated Slope and Roughness Error

ABSTRACT Planetary safe landing site selection is essential for ensuring the success of landing missions, relying on hazard avoidance techniques to mitigate risks. This study examines the influence of terrain uncertainties on the safe landing site selection process, which will lead to potential threats during landing. Such errors can result in hazards being misidentified as safe, or safe areas being incorrectly classified as hazardous, particularly in complex terrains that have densely distributed hazards. To address these challenges, this study proposes a probabilistic method for safe landing site selection, incorporating the error estimation of slope and roughness through an error propagation framework. This approach eliminates the reliance on deterministic thresholds for hazard assessment related to slope and roughness, enhancing flexibility in safety requirements by allowing for the adjustment of search thresholds based on the probabilistic safety criteria established in this study. The methodology consists of three parts: calculating DEM positioning errors based on surveying error, propagating these errors to calculated slope and roughness, and computing the probability of safe landing using these estimated errors for safe landing site selection. Experiment results demonstrate that the proposed method effectively identifies hazards and ranks candidate safe landing sites, even in the presence of terrain surveying errors. The proposed method improves sensitivity to threshold values, helping to minimize false detections and omissions, thus enhancing the reliability of safe landing site selection.

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Publication Details

Journal
Transactions in GIS
Published
2025-09-01
DOI
https://doi.org/10.1111/tgis.70115
Primary Topic
Planetary Science and Exploration
Type
article
Field-Weighted Citation Impact
0.00

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article

Probabilistic Safe Landing Site Selection Based on Estimated Slope and Roughness Error

Huan Xie, Yongjiu Feng, Yanyun Qu, Sicong Liu et al.
Transactions in GIS
Planetary Science and Exploration
article

Probabilistic Safe Landing Site Selection Based on Estimated Slope and Roughness Error

Huan Xie, Yongjiu Feng, Yanyun Qu, Sicong Liu, Xiong Xu, Yanmin Jin, C. K. Xiao, Xiaohua Tong
article en

Abstract

ABSTRACT Planetary safe landing site selection is essential for ensuring the success of landing missions, relying on hazard avoidance techniques to mitigate risks. This study examines the influence of terrain uncertainties on the safe landing site selection process, which will lead to potential threats during landing. Such errors can result in hazards being misidentified as safe, or safe areas being incorrectly classified as hazardous, particularly in complex terrains that have densely distributed hazards. To address these challenges, this study proposes a probabilistic method for safe landing site selection, incorporating the error estimation of slope and roughness through an error propagation framework. This approach eliminates the reliance on deterministic thresholds for hazard assessment related to slope and roughness, enhancing flexibility in safety requirements by allowing for the adjustment of search thresholds based on the probabilistic safety criteria established in this study. The methodology consists of three parts: calculating DEM positioning errors based on surveying error, propagating these errors to calculated slope and roughness, and computing the probability of safe landing using these estimated errors for safe landing site selection. Experiment results demonstrate that the proposed method effectively identifies hazards and ranks candidate safe landing sites, even in the presence of terrain surveying errors. The proposed method improves sensitivity to threshold values, helping to minimize false detections and omissions, thus enhancing the reliability of safe landing site selection.

Transactions in GISVol. 29(6)
Tongji University (CN), Collaborative Innovation Centre for Advanced Ship and Deep-Sea Exploration (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 84%
Planetary Science and Exploration
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