窦杰 (教授)

教授 博士生导师 硕士生导师

曾获荣誉:湖北省高层次人才计划
地大“百人计划”学科骨干人才
日本学术振兴会(JSPS)特别研究员
日本第17届地震工程大会- "Early Career Award"
日本文部省博士研究生国家奖学金

性别:男

毕业院校:东京大学

学历:博士研究生

学位:理学博士学位

在职信息:在职

所在单位:教育部长江三峡库区地质灾害研究中心

入职时间:2020-09-30

办公地点:湖北省武汉市鲁磨路388号 三峡中心-307室

联系方式:Tel: 15926324688; WeChat: douj888

Email:

   

个人简历

窦杰,男,籍贯江苏徐州,博士,日本学术振兴会(JSPS)研究员、博士生导师、博士后合作导师、教授,入选湖北省高层次人才计划、“地大百人计划”学科骨干人才。

东京大学博士,先后任东京大学空间情报中心博士后,日本国家国立研究開発法人土木研究所研究员,長岡技術科学大学研究员。从事人工智能,数值模拟和遥感与GIS在降雨-地震-人工诱发的地质灾害相关的预防预警研究工作。作为项目负责人(PI)主持并领导了4项科研项目,主要是受日本国土交通(MLIT)部和日本文部省的资助,还负责土木研究所火山小组雷达的研究工作(由日本宇航天局签署的雷达影像在防灾中的应用)。迄今已发国际刊物、书章和会议100余篇,其中SCI 54余篇,第一作者及通讯21篇,发表在 Earth-Science Reviews, Water Research, Landslides, Journal of Hydrology, Science of The Total Environment, Remote sensing of EnvironmentEnvironmental Modelling & Software, Nature Scientific Reports, Remote Sensing & Natural hazards 等多个国际学术刊物上,两篇文章分别入选2019年百篇顶级自然科学报告和SCI-TAO杂志最多引用奖,10ESI 1%高被引,2ESI 0.1%热点论文,Google scholar引用近3000次,受邀为30多个国际SCI期刊审稿,担任Geocarto International Geomatics, Natural Hazards and Risk, Journal Mountain of Science等四个国际期刊编委,担任Remote Sensing主题编辑和Frontiers in Earth Science前沿编辑,此外,在日本地球惑星科学会议和第五届世界滑坡论坛上被作为邀请嘉宾作报告。


个人主页

Google Scholar 主页 Research Gate 主页 三峡中心主页

 

研究方向与兴趣

主要从事人工智能大数据,数和遥感与GIS在降雨-水库-地震-人工诱发的地灾害相关的预测预报研究工作。具体包括:

1)基于机器学习识别多源海量遥感影像数据(星,航片,雷达SAR, 无人机UAV,激光雷达-LiDAR等)实现快速建立地灾害

2)基于多源地灾害体的料(地,地形地貌,气象水文等)耦合人工智能行地灾害风险评估;

3)基于灾害体或小尺度灾区域结合室内实验行物理过程数,探明灾害诱发机理和机制;

4)基于大数据耦合物理过程数值模拟的智能地质灾害预测预报,构建地灾快速响急预报模式。


招生与培养

 招生方向:3S与地灾害,地质资源与工程,地形地貌相关的专业

     海外生活学工作近10年期,与国上相关地灾害研究课题组建立了良好的合作关系,共同研究及表科研文。期招生具有良好的数学算机、数3S,水文地形地貌,地灾害基,勤好学,迎具有从事科学研究工作的情和抱博研究生、博士后加盟国家野外观测研究站和教育部985优势地质灾害平台,一起研究探索大自然灾害的奥秘!

                    常年招生1-3个博士后,1-2博士生,2-4硕士!也欢迎优秀本科生加入课题组积极参与科研活动。

                  欢迎咨询邮箱:doujie@cug.edu.cn


团队

      AI Geohazards-地质灾害智能管控团队,与日本东京大学、北海道大学、日本国土交通部技術政策综合研究所和土木研究所、美国East Carolina University、University of South-Eastern Norway等单位保持长期的合作关系,面向国际科学前沿和国家重大工程的科学问题,立足于三峡于库区,开展地质灾害智能减灾防灾的研究工作。

目前在读:
博士二名
硕士七名
一名特任教授和两名博士后在申请中。

学生指导情况

1.2021.11:2020硕士生罗万褀、2021届王锐、何雨健、马豪分别获得第三届巴东国际地质灾害学术论坛,BIGS2021 Poster二等奖、三等奖及优秀奖,向子林并在国际大会BIGS2021做口头报告

2.2021.11: 2021届向子林博士生分别获得三峡中心、中国地质大学2021年科技论文报告会一等奖和二等奖,2020硕士生罗万褀获得三等奖

 

教育背景

2012-2015京大学新成科学研究科 博士学位

2006-2009中国科学院地球科学院 士学位

2002-2006 青岛农业大学资环学院 学士学位

 

工作履历

2020-至今  中国地质大学(武汉) 教育部江三峡区地灾害研究中心

2019- 2020 日本学 研究

2016-2019  日本国立研究开法人 土木研究所 研究

2015-2016  京大学空中心 博士后

2011-2012  日本アカデミック エクスプレス株式会社 助理工程

2010-2011  中国赴日本国留学生范大学预备学校日训 

2009-2010  广州奥格公司

 

学术兼职

学会任

日本滑坡学会会、日本砂防学会会、日本地球行星科学連合会和国工程地会(IAEG)会、美国地球物理学会(AGU)会、欧洲地球科学学会(EGU)会员、中国地震学会地震灾害链专业委员会委员。

期刊

Geomatics, Natural Hazards and RiskJournal Mountain of Science, Remote Sensing, Journal of Geography and Geology, NaturalHazards, Theoretical and Applied Climatology, GeoscienceMachine Learning and Knowledge Extraction Remote sensing IF>4)专题主编; 

地质科技通报

 

国际期刊审稿

Geomorphology, Engineering Geology, Geoscience Frontiers, Science of The Total Environment, CATENA, Nature scientific report, Natural hazards, Remote sensing, Journal of Mountain Science, Theoretical and Applied Climatology, Arabian Journal of Geosciences, Geocarto International, Journal of African Earth Sciences, Human and Ecological Risk Assessment, International Journal of Digital Earth, Geoscience, ISPRS International Journal of Geo-Information, The Egyptian Journal of Remote Sensing and Space Sciences, International Journal of Disaster Risk Science, Mathematical and Computational Applications, Engineering with Computers, The Professional Geographer, Advances in Space Research, Geosciences,Machine Learning and Knowledge Extraction40SCI稿人。

 

主持

1.  动水驱动型滑坡启滑机制与判据课题(第二负责人),国家自然科学基金重大项目(2021-2025

2.  Coupling ensemble machine learning with physical parameters framework for landslide evaluation四川大学水力学与山区河流开发保护国家重点实验室基金资助项目(2021-2022

3.  人工智能灾害减灾防灾,中央高校高次人才科研经费2020-2025

4.   基于深度学山区流域多源地灾害链预测研究,四川大学水力学与山区河流开国家重点实验室基金目(2020-2021

5.  Cognitive modeling for dynamic long-term landslide assessment associated with extreme events in emergency preparedness and disaster management日本学会(2019-2020

6.    基于地地形因素地表崩塌的生与价研究日本国土交通部 2015-2018

7.    滑坡监测观测研究,日本国土交通部萌芽 2016-2018

8.    基于地灾害移损伤预测监视的开研究,日本国土交通部重点2015-2019

9.    广省地灾害数据建 广省科技2006-2009

 

近年主要 *代表通#共同一作)

    1. Dou, Jie*, Yunus, A.P., Tien Bui, D., Merghadi, A., Sahana, M., Zhu, Z., Chen, C.-W., Khosravi, K., Yang, Y., Pham, B.T., 2020. Different sampling strategies for predicting landslide susceptibilities are deemed less consequential with deep learning. Science of the Total Environment https://doi.org/10.1016/j.scitotenv.2020.137320 (SCI=7.963 -ESI 1% 高被引)

    2. Abdelaziz Merghadi1#, Ali P. Yunus2#, Dou Jie#*, Jim Whiteley, Binh Thai Pham. Machine learning methods for landslide susceptibility studies: a comparative overview of algorithm performance, Earth-Science Reviews, 207 (August): 103225. https://doi.org/10.1016/j.earscirev.2020.103225. (SCI=12.41 ESI 1% 高被引及热点论文)

    3. Dou, Jie*, Yunus, A.P., Tien Bui, D., Merghadi, A., Sahana, M., Zhu, Z., Chen, C.-W., Khosravi, K., Yang, Y., Pham, B.T., 2019. Assessment of advanced random forest and decision tree algorithms for modeling rainfall-induced landslide susceptibility in the Izu-Oshima Volcanic Island, Japan. Science of the Total Environment 662, 332–346. doi: 10.1016/j.scitotenv.2019.01.221 (SCI=7.963 -ESI 1% 高被引)

    4. Dou Jie*, Yunus, A.P., Bui, D.T., Merghadi, A., Sahana, M., Zhu, Z., Chen, C.-W., Han, Z., Pham, B.T., 2019. Improved landslide assessment using support vector machine with bagging, boosting, and stacking ensemble machine learning framework in a mountainous watershed, Japan. Landslides. https://doi.org/10.1007/s10346-019-01286-5 (SCI=6.578-ESI 0.1% 热点论文)

    5. Dou, Jie*, et.al. Evaluating GIS-Based Multiple Statistical Models and Data Mining for Earthquake and Rainfall-Induced Landslide Susceptibility Using the LiDAR DEM. Remote Sensing 2019, 11, doi:10.3390/rs11060638. (SCI=4.509 -ESI 1% 高被引)

    6. Dou Jie*, Chang K-T*, Chen S, et al. 2015. Automatic Case-Based Reasoning Approach for Landslide Detection: Integration of Object-Oriented Image Analysis and a Genetic Algorithm. Remote Sensing 7:4318–4342. doi: 10.3390/rs70404318 (SCI=4.509)

    7. Dou Jie*, Yunus, A.P., Xu, Y., Zhu, Z., Chen, C.-W., Sahana, M., Khosravi, K., Yang, Y., Pham, B.T., 2019. Torrential rainfall-triggered shallow landslide characteristics and susceptibility assessment using ensemble data-driven models in the Dongjiang Reservoir Watershed, China. Natural Hazards 97, 579–609. https://doi.org/10.1007/s11069-019-03659-4 (SCI=2.427)

    8. Chang, K.-T., Merghadi, A., Yunus, A.P., Pham, B.T., Dou Jie*. Evaluating scale effects of topographic variables in landslide susceptibility models using GIS-based machine learning techniques. Nature Scientific report vol. 9, no. 1, 2019, p. 12296, doi:10.1038/s41598-019-48773-2. (SCI=4.2, Selected as Top 100 rank )

    9. Dou, Jie*, Li, Xia, Yunus, Ali P., et al. (2015). An Integrated Artificial Neural Network Model for the Landslide Susceptibility Assessment of Osado Island, Japan. Natural    Hazards, 1–28. doi:10.1007/s11069-015-1799-2. (SCI=2.319)

    10. Dou Jie*, Tien Bui, Dieu, P. Yunus, Ali et al (2015). Optimization of Causative Factors for Landslide Susceptibility Evaluation using Remote Sensing and GIS data in parts of Niigata, Japan, Plos one, 10.1371/journal.pone.0133262 (SCI=3.53)

    11. Dou Jie*, Li X, Yunnus Ali, et al. (2015). Automatic detection of sinkhole collapses at finer resolutions using a multi-component remote sensing approach, Natural hazards DOI: 10.1007/s11069-015-1756-0. (SCI=2.427)

    12. Hai-bo Li#, Yue-ren Xu#, Jia-wen Zhou#, Xie-kang Wang#, Hiromitsu Yamagishi,  Dou, Jie#*. Preliminary analyses of a catastrophic landslide occurred on July 23, 2020, in Guizhou Province, China. Landslides. https://doi.org/10.1007/s10346-019-01334-0 (SCI=6.578)

    13. Han, Zheng, Bin Su, Yange Li,  Dou Jie, Weidong Wang, and Lianheng Zhao. Modeling the Progressive Entrainment of Bed Sediment by Viscous Debris Flows Using the Three-Dimensional SC-HBP-SPH Method, Water Research, 182,116031. https://doi.org/10.1016/j.watres.2020.116031(SCI =9.130

    14. Ali P.Yunus; Xuanmei Fan, Xiaolu Tang; Dou Jie, Qiang Xu, Runqiu Huang. Decadal vegetation succession from MODIS reveals the spatiotemporal evolution of    post-seismic landsliding after the 2008 Wenchuan earthquake, Remote Sensing of  Environment, 2020 (SCI=9.085)

    15. Yunus AP, Dou, Jie*, Song X, Avtar R (2019) Improved Bathymetric Mapping of  Coastal and Lake Environments Using Sentinel-2 and Landsat-8 Images. Sensors 19:2788. https://doi.org/10.3390/s19122788 (SCI=3.23)

    16. Dou Jie, Paudel U, Oguchi T, et al (2015). Differentiation of shallow and deep-seated landslides using support vector machines: a case study of the Chuetsu area, Japan (SCI) Terrestrial, Atmospheric and Oceanic Sciences. doi: 10.3319/TAO.2014.12.02.07(EOSI) (SCI=1.1)

    17. Chen, Y.*, Irfan, M., Uchimura, T., Meng, Q., Dou Jie*, 2020. Relationship between water content, shear deformation, and elastic wave velocity through unsaturated soil slope. Bulletin of Engineering Geology and the Environment. https://doi.org/10.1007/s10064-020-01841-8 (SCI=3.040)

    18. Dou Jie, Qian, J., Chen, S., & Zhen, X. (2010). Object-based and case-based reasoning method for ground collapses detection. Journal of Image and Graphics, 1 5(6), 900–910. (In Chinese)

    19. LV, Y., Le, Q., Bui, H.-B., Bui, X., Nguyen, H., Nguyen-Thoi, T., Dou Jie*, Song, X., 2020. A Comparative Study of Different Machine Learning Algorithms in Predicting the Content of Ilmenite in Titanium Placer. Appl. Sci. 10, 635.  (SCI=2.217)

    20. Zhu, Z., Wang, H., Peng, D., Dou, Jie*, 2019. Modeling the hindered settling  velocity of a falling particle in a particle-fluid mixture by the Tsallis entropy theory.  Entropy  (SCI=2.305)

    21. Shariati, M., Mafipour, M.S., Mehrabi, P., Bahadori, A., Zandi, Y., Salih, M.N.A., Nguyen, H., Dou Jie*, Song, X., Poi-Ngian, S. Application of a Hybrid Artificial Neural Network-Particle Swarm Optimization (ANN-PSO) Model in Behavior Prediction of Channel Shear Connectors Embedded in Normal and High-Strength Concrete. Appl. Sci. 9, 5534. https://doi.org/10.3390/app9245534 (SCI=2.217)

    22. Khosravi, K., Shahabi, H., Pham, B.T.*, Adamowski, J., Shirzadi, A., Pradhan, B., Dou, Jie*, Ly, H.-B., Gróf, G., Ho, H.L., Hong, H.*, Chapi, K., Prakash, I.A Comparative Assessment of Flood Susceptibility Modeling Using Multi-Criteria Decision-Making Analysis and Machine Learning Methods, 2019-Journal of Hydrology- (SCI=4.405 -ESI 1% 高被引)

    23. Shariati, M.; Mafipour, M.S.; Mehrabi, P.; Bahadori, A., Zandi, Y.; Salih, M.N.A.; Nguyen, H*.,   Dou, Jie*; Song, X.; Poi-Ngian, S. Application of a Hybrid Artificial Neural Network-Particle Swarm Optimization (ANN-PSO) Model in Behavior Prediction of Channel Shear Connectors Embedded in Normal and High-Strength Concrete. Appl. Sci. 2019, 9, 5534. ( SCI=2.217)

    24. Dou Jie*. et al (2018). A Comparative Study of the Binary Logistic Regression (BLR) and Artificial Neural Network (ANN) Models for GIS-Based Spatial Predicting  Landslides at a Regional Scale. Landslide Dynamics: ISDR-ICL Landslide Interactive Teaching Tools: Volume 1: Fundamentals, Mapping and Monitoring (eds. Sassa, K. et al.) 139–151 (Springer International Publishing, 2018). doi:10.1007/978-3-319-57774-6_10

    25. Zhu, Z. & Dou Jie* (2018). Current status of reclaimed water in China: An overview. Journal of Water Reuse and Desalination jwrd2018070. doi:10.2166/wrd.2018.070 (SCI=1.538)

    26. Daniela Castro Camilo, Luigi Lombardoa, Martin Maib, Dou Jie, Raphaël Huser, 2017. Handling high predictor dimensionality in slope-unit-based landslide susceptibility models through LASSO-penalized Generalized Linear Model, 97:145-156. Environmental Modelling & Software. doi: 10.1016/j.envsoft.2017.08.003 (SCI=4.807)


 头报

1. Estimating scale effects of multiple DEMs for landslide geohazard map using GIS-based artificial intelligence models, AGU, 2019, SanFrancisco, USA

2. GeohazardstriggeredbydeadlyHokkaidoIburi-TobuEarthquake(September 6, 2018, Mw6.7), Hokkaido, Japan,12thARCof IAEG,2019, Jeju, SouthKorean

3. EstimationofDistributionofTephraFallDepositUsingtheInterpolationMethodBased on Multi-observation Data, Interpraevent2018Toyama,Japan

4.High predictor dimensionality in slope-unit-based landslide susceptibility models throughLASSO-penalized Generalized Linear Model,2017,EGU General Assembly, Vienna, Austria

5.Ellipse-approximated isopach(EAI) approach forassessing ashfall deposit at the active Sakurajima volcano, Japan,2016,Cities onVolcanoes9,Puerto Varas,Chile

6.  Spatial resolution effects of digital terrain models on landslide susceptibility analysis,2016,Prague, CzechRepublic

7.  Analysis of the landslides in Hiroshima caused by the typhoon based on bivariate statistical landslide susceptibility,2015, JpGU, Makuhahri, Japan

8.  Shallow and Deep-Seated Landslide Differentiation Using Support Vector Machines: A Case Study of the Chuetsu Area, Japan, 2014, ICEO&SI, Taiwan, Taiwan

9. GIS-Based Landslide Susceptibility Mapping Using a Certainty Factor Model and Its Validation in the Chuetsu Area, Central Japan, 2014, The Third World Landslide Forum, Beijing, China

10.  Back propagation (BP) model optimized by genetic algorithms (GA) for predicting landslides, IGU 2013 - Kyoto regional conference, Japan

11.  Using Back-Propagation networks to predict the landslides based on 2m Lidar DEM, 2013, JpGU, Makuahri, Japan

12. Application of Support Vector Machines to predict landslides based on Lidar DEM: the Chuetsu earthquake case study, Japan, 2013, ICEO&SI, Taiwan.


软件著作权

         1.三峡库区地质灾害实时监测系统软件[简称:地灾监测系统]  V1.0, 2021.9.25


得荣誉

1.2021年入选湖北省高层次人才计划、2020年中国地质大学百人计划

2. 2018日本学(JSPS)特研究基金 

3. 2021年获获得日本第17届地震工程大会- "Early Career Award"

4. 2011日本政府(文部科学省-MEXT)博士生学金

5.  2014京大学新成科学研究科科学研究基金

6.  2019年,“Shallow and Deep-Seated Landslide Differentiation Using Support Vector Machines: A Case Study of the Chuetsu Area, Japan” published in TAO Journal has won the Most Cited Article Award in 2019。入SCITAO最多引用

7.  2020,“Evaluating scale effects of topographic variables in landslide susceptibility models using GIS-based machine learning techniques”。入百篇自然科学-Top 100 Nature Scientific Reports paper

8.  2008年中科院学术报告一等



研究方向

  • [1]   从事人工智能,大数据,数值模拟和遥感与GIS在降雨-地震-人工诱发的地质灾害相关的预防预警研究工作

  • 联系方式

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  • [2]  传真:

  • [3]  通讯/办公地址:

  • [4]  办公室电话:

  • [5]  移动电话:

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  • 团队成员

    AI Geohazards-地质灾害智能管控

    常年招生1-2博士生,2-4硕士,1-3个博士后!
    目前在读:
    博士二名
    硕士七名
    一名特任教授和两名博士后在申请中。