收稿：2025-12-08，
纸质出版：2026-04-07
移动端阅览
随着水利基础设施的投入运行，不少位于库区的斜坡在受到库水位的波动影响下往往会发生变形破坏，这严重影响到了水利设施的安全运行，并将可能带来更为严重的次生灾害。因此，开展精准的滑坡易发性评价对库区滑坡灾害的风险防控至关重要。为此，本研究以三峡库区秭归—巴东库岸段为研究区开展了精细化的动态滑坡易发性评价研究。首先，基于长期的滑坡野外调查以及历史资料分析构建起详细的滑坡数据库；其次，选取高程、坡度、地层岩性等16个影响因子构建滑坡的易发性评价指标体系并结合集成机器学习开展初步滑坡静态易发性评价。在此基础上，采用小基线集（SBAS）InSAR技术获取研究区的长时序的地表形变信息，并建立易发性等级评价结果和SBAS形变速率结果的优化矩阵，以此获取静态预测与动态形变信息相耦合的易发性评价结果。研究结果表明：（1）极高和高易发区主要集中分布在长江及其支流沿岸，高程、植被覆盖度、河流距离和降雨量是滑坡空间发育的主控因素；（2）相较于基础模型而言，集成学习模型可以有效的综合基础模型的优势，得到最优的建模精度（AUC=0.954）；（3）耦合时序InSAR的动态滑坡易发性结果可以有效修正静态易发性评价结果中存在的假阴性和假阳性误差。本研究有助于提高滑坡易发性建模的精确度与时效性，为水库滑坡灾害风险的动态管理提供新的参考。
With the operation of large-scale hydraulic infrastructures
many slopes located in reservoir areas are prone to deformation and failure under the influence of fluctuations in the reservoir water level
thereby seriously threatening the safe operation of hydraulic facilities and possibly leading to more severe secondary disasters. Therefore
conducting accurate landslide susceptibility assessment is of great significance for landslide risk prevention and mitigation in reservoir regions. In this study
a refined dynamic landslide susceptibility assessment was conducted for the Zigui-Badong reservoir bank section of the Three Gorges Reservoir area. First
a comprehensive landslide inventory was established on the basis of long-term field investigations and historical records. Subsequently
16 conditioning factors
including elevation
slope
and lithology
were selected to construct a landslide susceptibility evaluation index system
and an initial static susceptibility assessment was performed using ensemble machine learning methods. On this basis
long-term surface deformation information was retrieved using the small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) technique. An optimization matrix that integrates susceptibility classes and SBAS-derived deformation rates was developed to couple static predictions with dynamic deformation information
thereby obtaining dynamic landslide susceptibility results. (1) Very high- and high-susceptibility zones are mainly distributed along the Yangtze River and its tributaries
and elevation
vegetation coverage
distance to rivers
and rainfall are the dominant controlling factors for landslide spatial distribution; (2) compared with individual base models
the ensemble learning model more effectively integrates their advantages and achieves the highest prediction accuracy (AUC = 0.954); (3) the dynamic susceptibility results coupled with time-series InSAR data can effectively correct false-negative and false-positive errors in static susceptibility assessments. This study improves the accuracy and timeliness of landslide susceptibility modeling and provides a valuable reference for the dynamic management of landslide hazards in reservoir areas.
Akgun A , Sezer E A , Nefeslioglu H A , Gokceoglu C and Pradhan B . 2012 . An easy-to-use MATLAB program (MamLand) for the assessment of landslide susceptibility using a Mamdani fuzzy algorithm . Computers and Geosciences , 38 ( 1 ): 23 - 34 [ DOI: 10.1016/j.cageo.2011.04.012 http://dx.doi.org/10.1016/j.cageo.2011.04.012 ]
Berardino P , Fornaro G , Lanari R and Sansosti E . 2002 . A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms . IEEE Transactions on Geoscience and Remote Sensing , 40 ( 11 ): 2375 - 2383 [ DOI: 10.1109/TGRS.2002.803792 http://dx.doi.org/10.1109/TGRS.2002.803792 ]
Cao W G , Fu Y , Dong Q Y , Wang H G , Ren Y , Li Z Y and Du Y Y . 2023 . Landslide susceptibility assessment in Western Henan Province based on a comparison of conventional and ensemble machine learning . China Geology , 6 ( 3 ): 409 - 419 [ DOI: 10.31035/cg2023013 http://dx.doi.org/10.31035/cg2023013 ]
Ciampalini A , Raspini F , Lagomarsino D , Catani F and Casagli N . 2016 . Landslide susceptibility map refinement using PSInSAR data . Remote Sensing of Environment , 184 : 302 - 315 . [ DOI: 10.1016/j.rse.2016.07.018 http://dx.doi.org/10.1016/j.rse.2016.07.018 ]
Dou J , Yunus A P , Bui D T , Merghadi A , Sahana M , Zhu Z F , Chen C W , Han Z and Pham B T . 2020 . Improved landslide assessment using support vector machine with bagging, boosting, and stacking ensemble machine learning framework in a mountainous watershed, Japan . Landslides , 17 ( 3 ): 641 - 658 [ DOI: 10.1007/s10346-019-01286-5 http://dx.doi.org/10.1007/s10346-019-01286-5 ]
Du T , Cao L X and Liu L P . 2025 . Evaluation of loess landslide susceptibility based on logistic regression model . Technology Innovation and Application , 15 ( 21 ): 85 - 88 , 92
杜婷 , 曹李祥 , 刘莉萍 . 2025 . 基于逻辑回归模型的黄土滑坡易发性评价 . 科技创新与应用 , 15 ( 21 ): 85- 88 , 92 [ DOI: 10.19981/j.CN23-1581/G3.2025.21.019 http://dx.doi.org/10.19981/j.CN23-1581/G3.2025.21.019 ]
Feng X J . 2024 . Identification of Landslide Hazards and Evaluation of Landslide Susceptibility in the Yunnan-Tibet Border Area Based on Time-Series InSAR Technology . Kunming : Yunnan University
冯显杰 . 2024 . 基于时序InSAR技术的滇藏交界区滑坡隐患识别与滑坡易发性评价 . 昆明 : 云南大学 [ DOI: 10.27456/d.cnki.gyndu.2024.002648 http://dx.doi.org/10.27456/d.cnki.gyndu.2024.002648 ]
Gao B H , He Y , Zhang L F , Yao S , Yang W , Chen Y , He X , Zhao Z A and Chen H S . 2023 . Dynamic evaluation of landslide susceptibility by CNN considering InSAR deformation: a case study of Liujiaxia reservoir . Chinese Journal of Rock Mechanics and Engineering , 42 ( 2 ): 450 - 465
高秉海 , 何毅 , 张立峰 , 姚圣 , 杨旺 , 陈毅 , 何旭 , 赵占骜 , 陈鹤升 . 2023 . 顾及InSAR形变的CNN滑坡易发性动态评估——以刘家峡水库区域为例 . 岩石力学与工程学报 , 42 ( 2 ): 450 - 465 [ DOI: 10.13722/j.cnki.jrme.2022.0266 http://dx.doi.org/10.13722/j.cnki.jrme.2022.0266 ]
Golub G H and Van Loan C F . 1996 . Matrix Computations. 3rd ed . Baltimore : Johns Hopkins University Press
Guo G B , Tian T , Zhou Z G and Li S . 2025 . Research progress and prospect of disaster mechanism and risk control of reservoir landslide . Haihe Water Resources , ( 4 ): 85 - 90
郭广彬 , 田婷 , 周忠国 , 李涑 . 2025 . 水库滑坡致灾机理及风险防控研究进展与展望 . 海河水利 , ( 4 ): 85 - 90 [ DOI: 10.3969/j.issn.1004-7328.2025.04.017 http://dx.doi.org/10.3969/j.issn.1004-7328.2025.04.017 ]
Han W , Zhang X H , Wang Y , Wang L Z , Huang X H , Li J , Wang S , Chen W T , Li X J , Feng R Y , Fan R Y , Zhang X Y and Wang Y W . 2023 . A survey of machine learning and deep learning in remote sensing of geological environment: challenges, advances, and opportunities . ISPRS Journal of Photogrammetry and Remote Sensing , 202 : 87 - 113 [ DOI: 10.1016/j.isprsjprs.2023.05.032 http://dx.doi.org/10.1016/j.isprsjprs.2023.05.032 ]
Huang F M , Chen J , Yang Y , Chen Q , Zhou C B , Jiang B C and Guo F . 2025 . A review and prospect of disaster-causing environmental factors related to landslide susceptibility prediction . Bulletin of Geological Science and Technology , 44 ( 2 ): 14 - 37
黄发明 , 陈杰 , 杨阳 , 陈茜 , 周创兵 , 江炳辰 , 郭飞 . 2025 . 滑坡易发性相关致灾环境因子研究的综述与展望 . 地质科技通报 , 44 ( 2 ): 14 - 37 [ DOI: 10.19509/j.cnki.dzkq.tb20240766 http://dx.doi.org/10.19509/j.cnki.dzkq.tb20240766 ]
Huang L , Sun Q and Hu J . 2022 . Landslide sensitivity assessment and error correction based on InSAR and random forest method . Bulletin of Surveying and Mapping , ( 10 ): 13 - 20
黄龙 , 孙倩 , 胡俊 . 2022 . 基于InSAR与随机森林的滑坡敏感性评价与误差改正 . 测绘通报 , ( 10 ): 13 - 20 [ DOI: 10.13474/j.cnki.11-2246.2022.0288 http://dx.doi.org/10.13474/j.cnki.11-2246.2022.0288 ]
Jiang B D , Li X C , Luo H Y and Song Y W . 2023 . A comparative analysis of heterogeneous ensemble learning methods for landslide susceptibility assessment . China Civil Engineering Journal , 56 ( 10 ): 170 - 179
江宝得 , 李秀春 , 罗海燕 , 宋雨薇 . 2023 . 异质集成学习在滑坡易发性评价中的对比研究 . 土木工程学报 , 56 ( 10 ): 170 - 179 [ DOI: 10.15951/j.tmgcxb.22060553 http://dx.doi.org/10.15951/j.tmgcxb.22060553 ]
Jiang J F . 2025 . Analysis of hydrodynamic pressure landslide instability under the condition of reservoir water level drop . Water Conservancy Science and Technology and Economy , 31 ( 2 ): 22 - 25 , 31
蒋家发 . 2025 . 库水位下降条件下动水压力型滑坡失稳的分析 . 水利科技与经济 , 31 ( 2 ): 22- 25 , 31 [ DOI: 10.3969/j.issn.1006-7175.2025.02.005 http://dx.doi.org/10.3969/j.issn.1006-7175.2025.02.005 ]
Jin B J , Yin K L , Gui L , Zhao B B , Guo B R and Zeng T R . 2024b . Susceptibility assessment of land subsidence of transmission line towers in the Salt Lake Area based on remote sensing interpretation . Earth Science , 49 ( 2 ): 538 - 549
金必晶 , 殷坤龙 , 桂蕾 , 赵斌滨 , 郭宝瑞 , 曾韬睿 . 2024 . 基于遥感解译的盐湖地区输电线路杆塔地面沉降易发性评价 . 地球科学 , 49 ( 2 ): 538 - 549 [ DOI: 10.3799/dqkx.2022.109 http://dx.doi.org/10.3799/dqkx.2022.109 ]
Jin B J , Zeng T R , Gui L , Yin K L , Zhu Y H and Liu Y . 2024a . Mapping the landslide susceptibility considering future land use dynamics scenario . Journal of Geo-Information Science , 26 ( 6 ): 1486 - 1499
金必晶 , 曾韬睿 , 桂蕾 , 殷坤龙 , 朱宇航 , 刘洋 . 2024 . 考虑未来土地利用动态情景的滑坡易发性制图 . 地球信息科学学报 , 26 ( 6 ): 1486 - 1499 [ DOI: 10.12082/dqxxkx.2024.240009 http://dx.doi.org/10.12082/dqxxkx.2024.240009 ]
Li R , Zhou C , Zhu Y H , Zhang J and Li X . 2026 . Exploring association rules between urban land use and landslide spatial development in mountainous areas: a case study of Yunyang County in the Three Gorges Reservoir Area [J/OL ] . Earth Science , 1 - 19 . https://link.cnki.net/urlid/42.1874.P.20260210.0849.008 https://link.cnki.net/urlid/42.1874.P.20260210.0849.008
李蕊 , 周超 , 朱宇航 , 张婧 , 李喜 . 2026 . 山区城镇土地利用与滑坡空间发育的关联规则挖掘: 以三峡库区云阳县为例 [J/OL ] . 地球科学 , 1 - 19 . https://link.cnki.net/urlid/42.1874.P.20260210.0849.008 https://link.cnki.net/urlid/42.1874.P.20260210.0849.008 [ DOI: 10.3799/dqkx.2026.034 http://dx.doi.org/10.3799/dqkx.2026.034 ]
Ma P F , Chen L , Yu C , Zhu Q , Ding Y L , Wu Z R , Li H S , Tian C Y and Fan X M . 2025 . Dynamic landslide susceptibility mapping over last three decades to uncover variations in landslide causation in subtropical urban mountainous areas . Remote Sensing of Environment , 326 : 114800 [ DOI: 10.1016/j.rse.2025.114800 http://dx.doi.org/10.1016/j.rse.2025.114800 ]
Pham B T , Bui D T , Prakash I and Dholakia M B . 2017 . Hybrid integration of Multilayer Perceptron Neural Networks and machine learning ensembles for landslide susceptibility assessment at Himalayan area (India) using GIS . CATENA , 149 ( Pt 1 ): 52 - 63 [ DOI: 10.1016/j.catena.2016.09.007 http://dx.doi.org/10.1016/j.catena.2016.09.007 ]
Pham Q B , Chandra Pal S , Chakrabortty R , Saha A , Janizadeh S , Ahmadi K , Khedher K M , Anh D T , Tiefenbacher J P and Bannari A . 2022 . Predicting landslide susceptibility based on decision tree machine learning models under climate and land use changes . Geocarto International , 37 ( 25 ): 7881 - 7907 [ DOI: 10.1080/10106049.2021.1986579 http://dx.doi.org/10.1080/10106049.2021.1986579 ]
Wang Q , Xue Y , Zhang W , Long Y H and Zhou S L . 2021 . Landslide susceptibility mapping based on support vector machine models . Journal of Hunan City University (Natural Science) , 30 ( 1 ): 22 - 28
王倩 , 薛云 , 张维 , 龙岳红 , 周松林 . 2021 . 基于支持向量机的滑坡易发性评价 . 湖南城市学院学报(自然科学版) , 30 ( 1 ): 22 - 28 [ DOI: 10.3969/j.issn.1672-7304.2021.01.0005 http://dx.doi.org/10.3969/j.issn.1672-7304.2021.01.0005 ]
Wang Y , Cao Y , Xu F D , Zhou C , Yu L B , Wu L X , Wang Y and Yin K L . 2024 . Reservoir landslide susceptibility prediction considering non-landslide sampling and ensemble machine learning methods . Earth Science , 49 ( 5 ): 1619 - 1635
王悦 , 曹颖 , 许方党 , 周超 , 余蓝冰 , 吴立星 , 汪洋 , 殷坤龙 . 2024 . 考虑非滑坡样本选取和集成机器学习方法的水库滑坡易发性预测 . 地球科学 , 49 ( 5 ): 1619 - 1635 [ DOI: 10.3799/dqkx.2022.407 http://dx.doi.org/10.3799/dqkx.2022.407 ]
Wang Z Y , Li S M , Yuan L W and Le W P . 2025 . Landslide susceptibility evaluation considering the importance selection of influencing factors and soil moisture content . Hydrogeology and Engineering Geology , 52 ( 3 ): 211 - 221
王中羽 , 李素敏 , 袁利伟 , 乐伟鹏 . 2025 . 考虑影响因子重要性选择和土壤含水率的滑坡易发性评价 . 水文地质工程地质 , 52 ( 3 ): 211 - 221 [ DOI: 10.16030/j.cnki.issn.1000-3665.202309009 http://dx.doi.org/10.16030/j.cnki.issn.1000-3665.202309009 ]
Wei Y D , Qiu H J , Liu Z J , Huangfu W C , Zhu Y R , Liu Y , Yang D D and Kamp U . 2024 . Refined and dynamic susceptibility assessment of landslides using InSAR and machine learning models . Geoscience Frontiers , 15 ( 6 ): 101890 [ DOI: 10.1016/j.gsf.2024.101890 http://dx.doi.org/10.1016/j.gsf.2024.101890 ]
Wu H Y , Zhou C , Liang X , Wang Y , Yuan P C and Wu L X . 2024 . Evaluation of landslide susceptibility based on sample optimization strategy . Geomatics and Information Science of Wuhan University , 49 ( 8 ): 1492 - 1502
吴宏阳 , 周超 , 梁鑫 , 王悦 , 袁鹏程 , 吴立星 . 2024 . 基于样本优化策略的滑坡易发性评价 . 武汉大学学报(信息科学版) , 49 ( 8 ): 1492 - 1502 [ DOI: 10.13203/j.whugis20220527 http://dx.doi.org/10.13203/j.whugis20220527 ]
Wu H Y , Zhou C , Liang X , Yuan P C and Yu L B . 2023 . Assessment of landslide susceptibility mapping based on XGBoost model: a case study of Yanshan Township . The Chinese Journal of Geological Hazard and Control , 34 ( 5 ): 141 - 152
吴宏阳 , 周超 , 梁鑫 , 袁鹏程 , 余蓝冰 . 2023 . 基于XGBoost模型的三峡库区燕山乡滑坡易发性评价与区划 . 中国地质灾害与防治学报 , 34 ( 5 ): 141 - 152 [ DOI: 10.16031/j.cnki.issn.1003-8035.202206020 http://dx.doi.org/10.16031/j.cnki.issn.1003-8035.202206020 ]
Xiao H P , Wan J H , Chen L L , Fan Y C and Chen L . 2024 . Landslide susceptibility assessment by fusing InSAR deformation features under the support of weighted information volume . Journal of Geodesy and Geodynamics , 44 ( 7 ): 718 - 724
肖海平 , 万俊辉 , 陈兰兰 , 范永超 , 陈磊 . 2024 . 加权信息量支持下融合InSAR形变特征的滑坡易发性评价 . 大地测量与地球动力学 , 44 ( 7 ): 718 - 724 [ DOI: 10.14075/j.jgg.2023.10.168 http://dx.doi.org/10.14075/j.jgg.2023.10.168 ]
Xiao S R , Liu D F and Hu Z Y . 2010 . Engineering geologic study of three actual dip bedding rockslides associated with reservoirs in the world . Journal of Engineering Geology , 18 ( 1 ): 52 - 59
肖诗荣 , 刘德富 , 胡志宇 . 2010 . 世界三大典型水库型顺层岩质滑坡工程地质比较研究 . 工程地质学报 , 18 ( 1 ): 52 - 59 [ DOI: 10.3969/j.issn.1004-9665.2010.01.007 http://dx.doi.org/10.3969/j.issn.1004-9665.2010.01.007 ]
Xue Y F , Ma P H , Li Z K , Han N , Chen L S , Jiao Q X , Zhang Y T and Wang J Y . 2025 . Multi-model comparison for landslide susceptibility evaluation in Qingyang Area of Gansu, China . Journal of Earth Sciences and Environment , 47 ( 4 ): 600 - 617
薛一凡 , 马鹏辉 , 李泽坤 , 韩宁 , 陈立森 , 焦其宪 , 张永涛 , 王竟晔 . 2025 . 基于多模型对比的甘肃庆阳地区滑坡易发性评价 . 地球科学与环境学报 , 47 ( 4 ): 600 - 617 [ DOI: 10.19814/j.jese.2025.03031 http://dx.doi.org/10.19814/j.jese.2025.03031 ]
Yang J T . 2019 . Research on Landslide Susceptibility Evaluation Modeling Based on Hierarchical Bayesian Method . Chengdu : Southwest Petroleum University
杨锦涛 . 2019 . 基于层次贝叶斯方法的滑坡易发性评价建模研究 . 成都 : 西南石油大学 [ DOI: 10.27420/d.cnki.gxsyc.2019.000230 http://dx.doi.org/10.27420/d.cnki.gxsyc.2019.000230 ]
Zeng T R , Wu L Y , Jin B J , Yin K L , Chen Y T and Chen H . 2023 . Landslide dynamic susceptibility mapping based on stacking ensemble strategy and SBAS-InSAR . Chinese Journal of Rock Mechanics and Engineering , 42 ( 9 ): 2266 - 2282
曾韬睿 , 邬礼扬 , 金必晶 , 殷坤龙 , 陈熠婷 , 陈虹 . 2023 . 基于stacking集成策略和SBAS-InSAR的滑坡动态易发性制图 . 岩石力学与工程学报 , 42 ( 9 ): 2266 - 2282 [ DOI: 10.13722/j.cnki.jrme.2022.1089 http://dx.doi.org/10.13722/j.cnki.jrme.2022.1089 ]
Zhang J R , Wang Y , Feng X , Li Y Y , Jing B J , Zhou C , Zhang X and Deng Y . 2024 . Analysis of spatial-temporal variations in landslide susceptibility assess-ment considering surface deformation and land use dynamics . Bulletin of Geological Science and Technology , 43 ( 06 ): 184 - 195
张锦瑞 , 汪洋 , 冯霄 , 李远耀 , 金必晶 , 周超 , 张鑫 , 邓扬 . 2024 . 考虑地表形变和土地利用变更的滑坡时空易发性差异分析 . 地质科技通报 , 43 ( 06 ): 184 - 195 [ DOI: 10.19509/j.cnki.dzkq.tb20240195 http://dx.doi.org/10.19509/j.cnki.dzkq.tb20240195 ]
Zhao H Z , Li S M , Guo Q and Wang Z Y . 2024 . Application of ensemble learning model based on sample optimization in landslide susceptibility evaluation . Science of Surveying and Mapping , 49 ( 12 ): 132 - 141
赵恒梓 , 李素敏 , 郭庆 , 王中羽 . 2024 . 样本优化的集成学习模型在滑坡易发性评价中的应用 . 测绘科学 , 49 ( 12 ): 132 - 141 [ DOI: 10.16251/j.cnki.1009-2307.2024.12.013 http://dx.doi.org/10.16251/j.cnki.1009-2307.2024.12.013 ]
Zheng Y X , Zhou K K , Hu S W , Zhang H C , Yu G Q , Xu L K and Peng H . 2025 . Landslide susceptibility evaluation based on integrated learning and considering landslide negative samples . Yellow River , 47 ( 7 ): 116 - 123
郑元勋 , 周康康 , 胡少伟 , 张海超 , 于国卿 , 徐路凯 , 彭浩 . 2025 . 基于集成学习和考虑滑坡负样本的滑坡易发性评价 . 人民黄河 , 47 ( 7 ): 116 - 123 [ DOI: 10.3969/j.issn.1000-1379.2025.07.019 http://dx.doi.org/10.3969/j.issn.1000-1379.2025.07.019 ]
Zhou C . 2018 . Landslide Identification and Prediction with the Application of Time Series InSAR . Wuhan : China University of Geosciences
周超 . 2018 . 集成时间序列InSAR技术的滑坡早期识别与预测研究 . 武汉 : 中国地质大学
Zhou C , Cao Y , Hu X , Yin K L , Wang Y and Catani F . 2022 . Enhanced dynamic landslide hazard mapping using MT-InSAR method in the Three Gorges Reservoir Area . Landslides , 19 ( 7 ): 1585 - 1597 [ DOI: 10.1007/s10346-021-01796-1 http://dx.doi.org/10.1007/s10346-021-01796-1 ]
Zhou C , Gan L L , Cao Y , Wang Y , Segoni S , Shi X G , Motagh M and Singh R P . 2025 . Landslide susceptibility assessment of the Wanzhou district: merging landslide susceptibility modelling (LSM) with InSAR-derived ground deformation map . International Journal of Applied Earth Observation and Geoinformation , 136 : 104365 [ DOI: 10.1016/j.jag.2025.104365 http://dx.doi.org/10.1016/j.jag.2025.104365 ]
Zhou C , Gan L L , Wang Y , Wu H Y , Yu J , Cao Y and Yin K L . 2023 . Landslide susceptibility prediction based on non-landslide samples selection and heterogeneous ensemble machine learning . Journal of Geo-Information Science , 25 ( 8 ): 1570 - 1585
周超 , 甘露露 , 王悦 , 吴宏阳 , 喻进 , 曹颖 , 殷坤龙 . 2023 . 综合非滑坡样本选取指数与异质集成机器学习的区域滑坡易发性建模 . 地球信息科学学报 , 25 ( 8 ): 1570 - 1585 [ DOI: 10.12082/dqxxkx.2023.220934 http://dx.doi.org/10.12082/dqxxkx.2023.220934 ]
Zhou C , Yin K L , Cao Y and Li Y Y . 2020 . Landslide susceptibility assessment by applying the coupling method of radial basis neural network and adaboost: a case study from the Three Gorges Reservoir Area . Earth Science , 45 ( 6 ): 1865 - 1876
周超 , 殷坤龙 , 曹颖 , 李远耀 . 2020 . 基于集成学习与径向基神经网络耦合模型的三峡库区滑坡易发性评价 . 地球科学 , 45 ( 6 ): 1865 - 1876 [ DOI: 10.3799/dqkx.2020.071 http://dx.doi.org/10.3799/dqkx.2020.071 ]
Zhou W Z , Xu F , Kong R , Zhang G P and Miao C J . 2025 . Landslide susceptibility evaluation in Yunan district based on Bagging PU-learning and integrated learning . remote sensing information , 40 ( 3 ): 1 - 10
周武召 , 徐峰 , 孔润 , 张高鹏 , 苗超杰 . 2025 . 基于Bagging PU-learning和集成学习的云安区滑坡易发性评价 . 遥感信息 , 40 ( 3 ): 1 - 10 [ DOI: 10.20091/j.cnki.1000-3177.2025.03.001 http://dx.doi.org/10.20091/j.cnki.1000-3177.2025.03.001 ]
Zhu Y , Zhang Q , Wen H J , Ji Q , Zhu X , Zhang T B , Sun D L , Tang Y H , Zhao J J and Li C M . 2025 . Integrating time-series InSAR deformation and LightGBM for landslide susceptibility assessment . Journal of Beijing Normal University (Natural Science) , 61 ( 4 ): 551 - 562
朱颖 , 张强 , 文海家 , 冀琴 , 朱星 , 张廷斌 , 孙德亮 , 唐云辉 , 赵建军 , 李长明 . 2025 . 融合时序InSAR形变和LightGBM的滑坡易发性评价 . 北京师范大学学报(自然科学版) , 61 ( 4 ): 551 - 562 [ DOI: 10.12202/j.0476-0301.2024267 http://dx.doi.org/10.12202/j.0476-0301.2024267 ]
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