{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T04:27:30Z","timestamp":1784176050728,"version":"3.55.0"},"reference-count":59,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2024,9,29]],"date-time":"2024-09-29T00:00:00Z","timestamp":1727568000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2022YFF0503100"],"award-info":[{"award-number":["2022YFF0503100"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2024CX112"],"award-info":[{"award-number":["2024CX112"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2024CX108"],"award-info":[{"award-number":["2024CX108"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Graduate Innovation Fund of Jilin University","award":["2022YFF0503100"],"award-info":[{"award-number":["2022YFF0503100"]}]},{"name":"Graduate Innovation Fund of Jilin University","award":["2024CX112"],"award-info":[{"award-number":["2024CX112"]}]},{"name":"Graduate Innovation Fund of Jilin University","award":["2024CX108"],"award-info":[{"award-number":["2024CX108"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The safety of lunar landing sites directly impacts the success of lunar exploration missions. This study develops a data-driven predictive model based on machine learning, focusing on engineering safety to assess the suitability of lunar landing sites and provide insights into key factors and feature representations. Six critical engineering factors were selected as constraints for evaluation: slope, elevation, roughness, hillshade, optical maturity, and rock abundance. The XGBoost model was employed to simulate and predict the characteristics of landing areas and Bayesian optimization was used to fine-tune the model\u2019s key hyperparameters, enhancing its predictive performance. The results demonstrate that this method effectively extracts relevant features from multi-source remote sensing data and quantifies the suitability of landing zones, achieving an accuracy of 96% in identifying landing sites (at a resolution of 0.1\u00b0 \u00d7 0.1\u00b0), with AUC values exceeding 95%. Notably, slope was recognized as the most critical factor affecting safety. Compared to assessment processes based on Convolutional Neural Networks (CNNs) and Random Forest (RF) models, XGBoost showed superior performance in handling missing values and evaluating feature importance accuracy. The findings suggest that the BO-XGBoost model shows notable classification performance in evaluating the suitability of lunar landing sites, which may provide valuable support for future landing missions and contribute to optimizing lunar exploration efforts.<\/jats:p>","DOI":"10.3390\/rs16193632","type":"journal-article","created":{"date-parts":[[2024,9,30]],"date-time":"2024-09-30T05:45:27Z","timestamp":1727675127000},"page":"3632","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["A New Robust Lunar Landing Selection Method Using the Bayesian Optimization of Extreme Gradient Boosting Model (BO-XGBoost)"],"prefix":"10.3390","volume":"16","author":[{"given":"Shibo","family":"Wen","sequence":"first","affiliation":[{"name":"College of Geoexploration Science and Technology, Jilin University, Changchun 130026, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3093-7545","authenticated-orcid":false,"given":"Yongzhi","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Geoexploration Science and Technology, Jilin University, Changchun 130026, China"},{"name":"Institute of Integrated Information for Mineral Resources Prediction, Jilin University, Changchun 130026, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qizhou","family":"Gong","sequence":"additional","affiliation":[{"name":"College of Instrumentation and Electrical Engineering, Jilin University, Changchun 130061, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianzhong","family":"Liu","sequence":"additional","affiliation":[{"name":"Center for Lunar and Planetary Science, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China"},{"name":"CAS Center for Excellence in Comparative Planetology, Chinese Academy of Sciences, Hefei 230026, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoxi","family":"Kang","sequence":"additional","affiliation":[{"name":"Deep Space Exploration Laboratory, Beijing 100043, China"},{"name":"Lunar Exploration and Space Engineering Centre, China National Space Administration, Beijing 100190, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-5296-2938","authenticated-orcid":false,"given":"Hengxi","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Geoexploration Science and Technology, Jilin University, Changchun 130026, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rui","family":"Chen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Lunar and Planetary Sciences, Macau University of Science and Technology, Macau 999078, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3161-7508","authenticated-orcid":false,"given":"Kai","family":"Zhu","sequence":"additional","affiliation":[{"name":"Center for Lunar and Planetary Science, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China"},{"name":"CAS Center for Excellence in Comparative Planetology, Chinese Academy of Sciences, Hefei 230026, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-0214-8286","authenticated-orcid":false,"given":"Sheng","family":"Zhang","sequence":"additional","affiliation":[{"name":"Center for Lunar and Planetary Science, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China"},{"name":"CAS Center for Excellence in Comparative Planetology, Chinese Academy of Sciences, Hefei 230026, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2136","DOI":"10.1016\/j.scib.2024.04.051","article-title":"Return to the Moon: New perspectives on lunar exploration","volume":"69","author":"Lin","year":"2024","journal-title":"Sci. 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