科研项目: [1]教育部海外博士后引才专项计划,基于人工智能的空天遥感高山峡谷区复合地质灾害智能识别与监测预测,93万,2023.11-2024.11; [2]中国地质科公司地质力学研究所横向委托项目,巨型长大堰塞带演化识别评价研究,80万,2025.05-2027.05; [3]国家重点研发计划项目子课题项目,超高位超远程流域性地质灾害链动态识别与灾害评估-高陡浓雾山区崩滑灾害InSAR与光学遥感早期识别技术研究,300万,2024.12-2027.12; [4]甘肃省青年基金,综合遥感黄河中上游地质灾害广域精准识别与三维动态监测,4万元,2023.07-2025.07; [5]甘肃省科技重大专项计划项目课题项目,黄河上游黄土滑坡智能识别与多因素耦合灾变机理研究-黄土滑坡卫星遥感高精度形变监测方法,35万,2023.11-2026.11; [6]兰州市科学技术局,基于人工智能的雷达遥感兰州市地质灾害识别与监测预警研究,2.0万,2025.01-2027.01; [7]湖北长江三峡滑坡国家野外科学观测研究站,基于人工智能的多源遥感三峡库区滑坡动态早期识别研究,3.5万,2024.10-2026.09; [8]金年会官方网站入口红柳优青,人工智能地质灾害早期识别与监测预警,24万,2024.01-2027.01; [9]金年会官方网站入口青年教师学科交叉研究培育项目,AI大模型驱动空天遥感地质灾害动态识别与预测预报研究,10万,2025.07-2026.06。 学术成果: 1.学术论文 [1]Liu X, Tomás R, Zhao C, et al. Millimeter ground deformation retrieving from high-resolution PAZ SAR images with a combined correction of unwrapping and long-wavelength errors: A case study in Alcoy, Spain[J]. Remote Sensing of Environment, 2025, 328: 114876. (SCI,中科院一区,地学及遥感TOP期刊,遥感及影像科学领域全球排名第1,影响因子13.850) [2]刘晓杰,赵超英,李滨,等.基于InSAR技术的甘肃积石山震区活动滑坡识别与动态形变监测.武汉大学学报(信息科学版), 2025, 50(2): 297-312. (EI,领军期刊) [3]Bin Li,Xiaojie Liu*, Chaoying Zhao, et al. Deep Learning-Based InSAR Phase Gradient Stacking Method for Mapping Active Geohazards in the Lower Yarlung Tsangpo, China. Acta Geologica Sinica-English Edition, 2025. [4]Liu Xiaojie, Zhao Chaoying, Yin Yueping, Tomás Roberto, Zhang Jing, Zhang Qin, Wei Yunjie, Wang Meng, M. Lopez-Sanchez, Juan. Refined InSAR method for mapping and classification of active landslides in a high mountain region: Deqin County, southern Tibet Plateau, China, Remote Sensing of Environment, 2024, 304: 114030. (SCI,中科院一区,地学及遥感TOP期刊,遥感及影像科学领域全球排名第1,影响因子13.850) [5]Jiang Z, Zhao C,Liu X, et al. The regional differentiation on the spatial distribution and influencing factors of potential landslides across the entire Loess Plateau, China based on InSAR and sub-region XGBoost-SHAP model[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2024. [6]Yan M, Zhao C,Liu X, et al. Sequential SBAS-InSAR Backward Estimation of Deformation Time Series[J]. IEEE Geoscience and Remote Sensing Letters, 2023, 21: 1-5. [7]Chen X, Zhao C,Liu X, et al. An Embedding Swin Transformer Model for Automatic Slow-moving Landslides Detection based on InSAR Products[J]. IEEE Transactions on Geoscience and Remote Sensing, 2024. [8]Tang, G., Dai, K., Deng, J.,Liu, X., Liu, C., Liu, T., ... & Fan, X. (2025). An enhanced neighborhood differential method for potential landslide identification from stacking-InSAR results. Measurement, 242, 115921. [9]Wang, B., Li, W., Zhao, C., Zhang, Q., Li, G.,Liu, X., ... & Zheng, S. (2024). L 2-Norm Quasi 3-D Phase Unwrapping Assisted Multitemporal InSAR Deformation Dynamic Monitoring for the Cross-Sea Bridge.IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. [10]Liu Xiaojie, Zhao Chaoying, Zhang Qin, Yin Yueping, Lu Zhong, et al., 2021. Three-dimensional and long-term landslide displacement estimation by fusing C- and L-band SAR observations: A case study in Gongjue County, Tibet, China. Remote Sensing of Environment 267, 112745. (SCI,中科院一区,地学及遥感TOP期刊,遥感及影像科学领域全球排名第1,影响因子13.850) [11]Liu Xiaojie, Zhao Chaoying, Zhang Qin, Lu Zhong, Li Zhenhong, et al., 2021. Integration of Sentinel-1 and ALOS/PALSAR-2 SAR datasets for mapping active landslides along the Jinsha River corridor, China. Engineering Geology 284, 106033. (SCI, ESI 1%高被引论文,中科院一区,地学TOP期刊,工程地质领域全球排名第2,影响因子6.902) [12]Liu Xiaojie, Zhao Chaoying, Zhang Qin, Lu Zhong, Li Zhenhong, 2020. Deformation of the Baige Landslide, Tibet, China, Revealed Through the Integration of Cross‐Platform ALOS/PALSAR‐1 and ALOS/PALSAR‐2 SAR Observations. Geophysical Research Letters 47, e2019GL086142. (SCI,中科院一区,地学TOP期刊,自然指数(Nature Index)期刊,影响因子5.58) [13]Liu Xiaojie, Zhao Chaoying, Zhang Qin, Yang Chengsheng, Zhu Wu, 2020. Heifangtai loess landslide type and failure mode analysis with ascending and descending Spot-mode TerraSAR-X datasets. Landslides 17, 205-215. (SCI,中科院小类一区,地学TOP期刊,影响因子6.153) [14]Liu Xiaojie, Zhao Chaoying, Zhang Qin, Yang Chengsheng, Zhang Jing, 2019. Characterizing and Monitoring Ground Settlement of Marine Reclamation Land of Xiamen New Airport, China with Sentinel-1 SAR Datasets. Remote Sensing 11, 585. (SCI,中科院二区,工程技术TOP期刊,影响因子5.349) [15]Liu Xiaojie, Zhao Chaoying, Zhang Qin, Peng Jianbing, Zhu Wu, Lu Zhong, 2018. Multi-Temporal Loess Landslide Inventory Mapping with C-, X- and L-Band SAR Datasets—A Case Study of Heifangtai Loess Landslides, China. Remote Sensing 10, 1756. (SCI,中科院二区,工程技术TOP期刊,影响因子5.349) [16]Yin Yueping,Liu Xiaojie *, Zhao Chaoying, Tomás Roberto, Zhang Qin, et al., 2022. Multi-dimensional and long-term time series monitoring and early warning of landslide hazards with improved SAR offset-tracking method. Science China Technological Science. (SCI,中科院二区,中国工程院期刊,影响因子3.903) [17]Wei Yuming,Liu Xiaojie, Zhao Chaoying, Tomás Roberto, Jiang Zhuo, 2021. Observation of Surface Displacement Associated with Rapid Urbanization and Land Creation in Lanzhou, Loess Plateau of China with Sentinel-1 SAR Imagery. Remote Sensing 13, 3472. (SCI,中科院二区,工程技术TOP期刊,影响因子5.349) [18]Ma Zhangfeng, Liu Jihong,Liu Xiaojie, Hu Jia, et al., 2021. Go Extra Miles: An Additional Error Correction Procedure Aimed to Further Improve Phase Unwrapping Accuracy and Reduce Creep Model Uncertainty. Journal of Geophysical Research: Solid Earth 127, e2021JB022478. (SCI,中科院一区,地学TOP期刊,自然指数(Nature Index)期刊,影响因子4.39) [19]Hu Liuru, Navarro-Hernandez María I.,Liu Xiaojie, Tomas Roberto, et al., 2022. Analysis of regional large-gradient land subsidence in the Alto Guadalentín Basin (Spain) using open-access aerial LiDAR datasets. Remote Sensing of Environment 280, 113218. (SCI,中科院一区,地学及遥感TOP期刊,遥感及影像科学领域全球排名第1,影响因子13.850) [20]Ma Zhangfeng, Liu Jihong, Aoki Yosuke, Wei Shengji,Liu Xiaojie, Cui Yan, et al., 2022. Towards big SAR data era: An effcient Sentinel-1 Near-Real-Time InSAR processing workflow with an emphasis on co-registration and phase unwrapping. ISPRS Journal of Photogrammetry and Remote Sensing 188, 286-300. (SCI,中科院一区,遥感TOP期刊,影响因子11.774) [21]Ma Zhangfeng, Wei Shengji, Li Xing, Aoki Yosuke, Liu Jihong,Liu Xiaojie, Mao Wenfei, et al., 2022. Challenges and Prospects to Time Series Burst Overlap Interferometry (BOI): Some Insights from a New BOI Algorithm Test over the Chaman Fault. IEEE Transactions on Geoscience and Remote Sensing 60, 1-19. (SCI,中科院二区,影响因子8.125) [22]Dai Keren, Li Zhenhong, Xu Qiang, Burgmann Roland, G. Milledge David, Tomás Roberto, Fan Xuanmei, Zhao Chaoying,Liu Xiaojie, Peng Jianbing, et al., 2020. Entering the Era of Earth Observation Based Landslide Warning Systems A novel and exciting framework. IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE, 136-153. (SCI,中科院一区,地学TOP期刊,影响因子13.925) [23]Chen Liquan, Zhao Chaoying, Li Bin, He Kai, Ren Chaofeng,Liu Xiaojie, Liu Donglie, 2021. Deformation monitoring and failure mode research of mining-induced Jianshanying landslide in karst mountain area, China with ALOS/PALSAR-2 images. Landslides 18, 2739-2750. (SCI,中科院小类一区,地学TOP期刊,影响因子6.153) [24]Yang Liye, Lu Zhong, Zhao Chaoying, Jinwoo Kim, Yang Chengsheng, Wang Baohang,Liu Xiaojie, Wang Zhe, 2022. Analyzing the triggering factors of glacial lake outburst floods with SAR and optical images: a case study in Jinweng Co, Tibet, China. Landslides 19, 855-864. (SCI,中科院小类一区,地学TOP期刊,影响因子6.153) [25]Li Guangrong, Zhao Chaoying, Wang Baohang,Liu Xiaojie, Chen Hengyi, 2022. Land subsidence monitoring and dynamic prediction of Reclaimed Islands with Multi-Temporal InSAR Techniques in Xiamen and Zhangzhou Cities, China. Remote Sensing, 14, 2930. (SCI,中科院二区,工程技术TOP期刊,影响因子5.349) [26]Jiang Z, Zhao C, Yan M, Wang B H,Liu X J, et al. The Early Identification and Spatio-Temporal Characteristics of Loess Landslides with SENTINEL-1A Datasets: A Case of Dingbian County, China[J]. Remote Sensing, 2022, 14(23): 6009. [27]Liu Xiaojie, Zhao Chaoying, Wang Baohang, Zhu Wenfeng, 2018. MT-InSAR landslide monitoring with the aid of homogeneous pixels filter. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3, 1135-1139. (EI) [28]Zhao Chaoying,Liu Xiaojie, Zhu Wu, Zhu Wenfeng, 2018. Two-dimensional loess landslide deformation monitoring with multidimensional small baseline subset (MSBAS) - a case study of Xinyuan No.2 landslide, Gansu, China. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3, 2341-2345. (EI) [29]Liu Xiaojie, Zhao Chaoying, Zhang Qin, Lu Zhong, Dai Fuchu, 2019. Investigating the deformation history and failure mechanism of Heifangtai loess landslide, China with Multi-source SAR data. 2019 IEEE International Geoscience and Remote Sensing Symposium. (EI) [30]Zhao Chaoying,Liu Xiaojie, Zhang Qin, Yang Chengsheng, Chen Liquan, 2019. InSAR application to Baige landslide event, China, from fast rescue to catchment investigation. 2019 IEEE International Geoscience and Remote Sensing Symposium. (EI) [31]Xun Zhangyuan, Zhao Chaoying,Liu Xiaojie, 2019. Automatic identification of potential landslides by integrating remote sensing, DEM and deformation map. 2019 IEEE International Geoscience and Remote Sensing Symposium. (EI) [32]Xun Z, Zhao C, Kang Y,Liu X J, et al. Automatic extraction of potential landslides by integrating an optical remote sensing image with an InSAR-derived deformation map[J]. Remote Sensing, 2022, 14(11): 2669. [33]Zhang T, Yin Y, Li B,Liu X J, et al. Characteristics and dynamic analysis of the February 2021 long-runout disaster chain triggered by massive rock and ice avalanche at Chamoli, Indian Himalaya[J]. Journal of Rock Mechanics and Geotechnical Engineering, 2023, 15(2): 296-308. [34]Tomás R, Díaz E, Szeibert W T,Liu X J,et al. Geomorphological characterization, remote sensing monitoring, and modeling of a slow-moving landslide in Alcoy (Southern Spain)[J]. Landslides, 2023, 20(6): 1293-1301. [35]Tomás R, Zeng Q, Lopez-Sanchez J M, Zhao C Y, Li Z H,Liu X J, et al. Advances on the investigation of landslides by space-borne synthetic aperture radar interferometry[J]. Geo-spatial Information Science, 2023: 1-22. [36]Zhang, T., Gao, Y., Li, B., Yin, Y.,Liu, X., Gao, H., & Yang, W. Characteristics of rock-ice avalanches and geohazard-chains in the Parlung Zangbo Basin, Tibet, China. Geomorphology, 2023, 422, 108549. [37]Gao, Y., Li, J.,Liu, X., Wu, W., Zhang, H., & Liu, P. Deformation Monitoring and Dynamic Analysis of Long-Runout Bedding Landslide Based on InSAR and Particle Flow Code. Remote Sensing, 2023, 15(21), 5105. [38]Zhao, C., Chen, L., Yin, Y.,Liu, X., Li, B., Ren, C., & Liu, D. Failure process and three-dimensional motions of mining-induced Jianshanying landslide in China observed by optical, LiDAR and SAR datasets. GIScience & Remote Sensing, 2023, 60(1), 2268367. [39]Gao, H., Yin, Y., Li, B., Gao, Y., Zhang, T.,Liu, X., & Wan, J. Geomorphic evolution of the Sedongpu Basin after catastrophic ice and rock avalanches triggered by the 2017 Ms6. 9 Milin earthquake in the Yarlung Zangbo River area, China. Landslides, 2023, 1-15. [40]Wang, B., Zhao, C., Zhang, Q.,Liu, X., Lu, Z., Liu, C., & Zhang, J. Sequential DS-ISBAS InSAR Deformation Parameter Dynamic Estimation and Quality Evaluation. Remote Sensing, 2023, 15(8), 2097. [41]赵超英,刘晓杰,张勤,彭建兵,许强,2019.甘肃黑方台黄土滑坡InSAR识别、监测与失稳模式研究.武汉大学学报信息科学版 7 (44),996-1007. (EI) [42]王哲,赵超英,刘晓杰,李滨, 2021.西藏易贡滑坡演化光学遥感分析与InSAR形变监测.武汉大学学报信息科学版46(10), 1569-1578. [43]刘晓杰,赵超英,康亚,张勤,2019.茂县滑坡形变的Sentinel-1数据分析.测绘科学44(4), 55-71. (中文核心) [44]康亚,赵超英,张勤,刘晓杰,2018. InSAR滑坡探测技术研究-以金沙江乌东德水电站段为例.大地测量与地球动力学38(10), 1053-1057. (中文核心) [45]殷跃平,李滨,张田田,王猛,万佳威,刘晓杰,高杨,朱赛楠,2021.印度查莫利“2·7”冰岩山崩堵江溃决洪水灾害链研究.中国地质灾害与防治学报, 2021 32(3), 1-8. [46]李壮,李滨,高杨,王猛,赵超英,刘晓杰,2021.雅鲁藏布江下游色东普沟高位地质灾害发育特征遥感解译.中国地质灾害与防治学报, 2021 32(3), 33-41. [47]赵志男,李滨,高杨,赵超英,刘晓杰,王猛,2021.西藏然乌湖口高位地质灾害变形特征分析.中国地质灾害与防治学报, 2021 32(3), 25-32. [48]张田田,殷跃平,李滨,贺凯,王猛,赵超英,刘晓杰,2021.西藏波密茶隆隆巴曲高位地质灾害类型及发育特征.中国地质灾害与防治学报, 2021 32(3), 9-16. [49]卫童瑶,殷跃平,李滨,褚宏亮,高杨,王猛,赵超英,刘晓杰,2021.西藏笨多高位变形体遥感解译与危险性预测分析.中国地质灾害与防治学报, 2021 32(3), 17-24. [50]李军,褚宏亮,李滨,高杨,王猛,赵超英,刘晓杰,2021.基于高分影像与InSAR解译的西藏林芝则隆弄高位链式地质灾害发育特征分析.中国地质灾害与防治学报, 2021 32(3), 42-50. 2.授权专利 [1] 一种附加DEM约束的SAR偏移量三维形变估计方法及系统,国家发明专利; [2] 融合SAR与光学偏移量技术的地表三维形变计算方法及系统,国家发明专利; [3] 一种融合DEM、光学遥感和形变信息的潜在滑坡识别方法,国家发明专利; [4] 一种InSAR干涉相位真值确定及差分干涉测量方法,国家发明专利; [5] 一种地面沉降信息的黄土滑坡早期识别方法,国家发明专利; [6] 一种InSAR时序DEM误差估计方法,国家发明专利。 3.专著 殷跃平,朱赛楠,李滨等.青藏高原高位远程地质灾害[M].科学出版社,2021. |