Personal Profile

陈泽强，教授，博导，GIS博士，湖北省楚天学子，地大学者（学科骨干），香港中文大学博士后，武汉大学博士后，美国乔治梅森大学访问学者，联合国国际电信联盟物联网与智慧城市标准组（ITU-T SG20）Q5副报告人，主要从事传感网和时空大数据智能研究及其在智慧流域和智慧城市中的应用及国际标准制订。主持国家重点研发计划项目和国家自然科学基金面上项目等国内外项目10余项；出版著作2部，发表SCI(E)/SSCI论文40余篇，制订国际标准4项（3项已发布）；获教育部自然科学一等奖和教育部科技进步一等奖各1项。

科研项目：

[1] 城市建成环境多源遥感智能监测关键技术与应用，国家重点研发计划项目(2024YFB3908600), 2025.4-2028.3, 参与

[2]    基于多源大数据的时空过程智能分析挖掘技术与软件，国家重点研发计划青年科学家项目(2021YFF0704400), 2021.12-2024.11, 主持

[3]     基于时空大数据和机器学习的长江中游洪涝灾害高精度模拟与预测，国家自然科学基金面上项目(41971351)，2020.1-2023.12，主持

[4]     卫星耦合传感网的长江中游洪涝灾害实时动态监测方法研究，国家自然科学基金面上项目(41771422)，2018.1-2021.12，主持

[5]     水环境异常事件信息表征与过滤方法研究，国家自然科学基金青年基金项目(41301441)， 2014.1-2016.12，主持

[6]     卫星、无人机耦合传感网的长江中游洪涝淹没范围提取方法研究，湖北省自然科学基金面上项目（2017CFB616），2017.1-2018.12，主持

[7]     卫星耦合传感网的海洋环境大数据处理，中央高校自主科研项目自然科学-学科交叉类(2042017kf0211)，2017.1-2018.12，主持

[8]     传感网环境下时空大数据联合挖掘交通拥堵事件，中国博士后科学基金特别资助项目（2015T80829），2015.9-2016.10，主持

[9]     传感网环境下应急事件时空分布监测：以交通拥堵为例，中国博士后科学基金面上项目（2014M562050），2014.9-2016.10，主持

[10]   位置感知的信息融合协同计算与服务，国家重点研发计划项目课题（2017YFB0503704），2017.7-2021.6，参与

[11]   区域遥感协同监测应急服务体系，国家重点研发计划项目课题（2016YFB0502601），2016.7-2019.6，参与

学术论文：

  [1]   Lei Xu,  Zhenni Ye, Jin Dai, Qi Li, Youting Hong, Yun Tao, Hongchu Yu, Chong Zhang, Zeqiang Chen*, Nengcheng Chen. Spatiotemporal Seamless Estimation of Global Surface Soil Moisture Using Triple Collocation, Machine Learning, and Data Assimilation. IEEE Transactions on Geoscience and Remote Sensing, 2025, 63, 4505216.

       [2]     Lei Xu, Xihao Zhang, Xi Zhang,Tingtao Wu, Hongchu Yu, Wenying Du, Zeqiang Chen*, Nengcheng Chen.Accurate sub-seasonal root-zone soil moisture prediction using attention-based autoregressive transfer learning and SMAP data.International Journal of Applied Earth Observation and Geoinformation, 2025, 139: 104532.

       [3]     Zhiqing Li, Zeqiang Chen*, Lai Chen, Xu Tang, Nengcheng Chen.SRFNet: Multimodal Based Selective Receptive Field Neural Network for Time Series Forecast of Flood Range.IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2025, 18:9340-9350.

       [4]     Yingxia Chen, Zhaoheng Liu, Zeqiang Chen*.AMS: A hyperspectral image classification method based on SVM and multi-modal attention network.Knowledge-Based Systems, 2025, 314: 113236.

       [5]     Zeqiang Chen*, Xinghao Li, Xiang Zhang, Lei Xu,Wenying Du,Yan Zhang, Nengcheng Chen*. Global drought-flood adrubt alternation:Spatio-temporal patterns,drives and projections. The Innovation Geoscience, 2025, 3: 100113.

       [6]    Zeqiang Chen, Tongxu Zou, Zheng Xu, Yan Zhang*, Nengcheng Chen. SAGE-GSAN: A graph-based method for estimating urban taxi CO emissions using street view images.Journal of Cleaner Production, 2024, 474:143543.

       [7]    Sijia He,Wenying Du*,Yan Zhang,Lai Chen,Zeqiang Chen,Nengcheng Chen*. Next location prediction using heterogeneous graph-based fusion network with physical and social awareness.International Journal of Geographical Information Science, 2024, 38:1965-1990.

       [8]    Lai Chen, Zeqiang Chen*, Nengcheng Chen. PDFID: A high-resolution flood inundation dataset with a long time series. Journal of Hydrology:Regional Studies, 2024, 52:101715.

       [9]    Lei Xu, Xihao Zhang, Hongchu Yu  Zeqiang Chen, Wenying Du*, Nengcheng Chen. Incorporating spatial autocorrelation into deformable ConvLSTM for hourly precipitation forecasting.Computers & Geosciences, 2024, 52:105536.

       [10]    Zhang Jing, Deng Fan, Wang Yonghua, Gong Jie, Liu, Ziyang, Liu, Wenjun, Zeng, Yinmei, Chen, Zeqiang. DEPDet: A Cross-Spatial Multiscale Lightweight Network for Ship Detection of SAR Images in Complex Scenes.IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2024, 17:18182-18198.

       [11]    Jianlong Wang, Xiaoqi Duan , Peixiao Wang, Gen Qiu, Zeqiang Chen. Predicting urban signal-controlled intersection congestion events using spatio-temporal neural point process.International Journal of Digital Earth, 2024, 17:2376270.

       [12]    Lei Xu; Ruinan Cai; Hongchu Yu; Wenying Du; Zeqiang Chen; Nengcheng Chen. Monthly NDVI Prediction Using Spatial Autocorrelation and Nonlocal Attention Networks.IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2024, 17:3425-3437.

       [13]    Zeqiang Chen*,Dongyang Liu,Ke Wan,Wenzhe Huang,Nengcheng Chen. Estimation and Spatiotemporal Analysis of Surface Evaporation in the Yangtze River Basin from 2010 to 2019.Remote Sensing, 2024, 16(1):3425-3437.

       [14]   Yunbo Zhang,Jie Li*,Mu Duan,Wenjie Chen,Joaquin del Rio,Xiang Zhang,Ke Wang,Steve H.L. Liang,Zeqiang Chen,Nengcheng Chen,Chuli Hu*. Multi-sensor integration management in the earth observation sensor web: State-of-the-art and research challenges.International Journal of Applied Earth Observation and Geoinformation, 2023, 125:103601.

       [15]   Zeqiang Chen,Hui Lin,Gaoyun Shen*.TreeLSTM: A spatiotemporal machine learning model for rainfall-runoff estimation. Journal of Hydrology: Regional Studies, 2023, 48:101474.

       [16]   Lei Xu*,Hongchu Yu,Zeqiang Chen,Wenying Du,Nengcheng Chen,Min Huang.Hybrid Deep Learning and S2S Model for Improved Sub-Seasonal Surface and Root-Zone Soil Moisture Forecasting,Remote Sensing, 2023, 15(13):3410.

       [17]   Shuang Yao,Wenying Du*,Nengcheng Chen,Chao Wang, Zeqiang Chen. An integrated process-based framework for flood phase segmentation and assessment,International Journal of Geographical Information Science, 2023, 37:1315-1337.

       [18]   Lei Xu*,Hongchu Yu,Zeqiang Chen,Wenying Du,Nengcheng Chen, Chong Zhang. Monthly Ocean Primary Productivity Forecasting by Joint Use of Seasonal Climate Prediction and Temporal Memory,Remote Sensing, 2023, 15(5):1417.

       [19]   Yan Zhang, Nengcheng Chen, Siqi Wang, Mengtian Wen, Zeqiang Chen*. Will carbon trading reduce spatial inequality? A spatial analysis of 200 cities in China,Journal of Environmental Management, 2023, 325:116402.

       [20]   Jingjing Liu, Nengcheng Chen*, Zeqiang Chen, Lei Xu, Wenying Du, Yan Zhang, Chao Wang. Towards sustainable smart cities: Maturity assessment and development pattern recognition in China,Journal of Cleaner Production, 2023, 370:133248.

       [21]   Lei Xu, Nengcheng Chen, Chao Yang, Hongchu Yu, Zeqiang Chen. Quantifying the uncertainty of precipitation forecasting using probabilistic deep learning,Hydrology and Earth System Sciences, 2022, 26:2923-2938.

       [22]   Yingbing Liu; Yuqin Wu; Zeqiang Chen; Min Huang; Wenying Du; Nengcheng Chen*. A Novel Impervious Surface Extraction Method Based on Automatically Generating Training Samples From Multisource Remote Sensing Products: A Case Study of Wuhan City, China,IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022, 15:6766-6780.

       [23]Yan Zhang, Zeqiang Chen, Xiang Zheng, Nengcheng Chen*, Yongqiang Wang. Extracting the location of flooding events in urban systems and analyzing the semantic risk using social sensing data,Journal of Hydrology, 2021, 603:127053.

[24]     Zeqiang Chen, Yi Zeng, Gaoyun Shen, Changjiang Xiao, Lei Xu, Nengcheng Chen. Spatiotemporal characteristics and estimates of extreme precipitation in the Yangtze River Basin using GLDAS data. International Journal of Climatology, 2021, 41: E1812-E1830.

[25]     Jin Luo, Zeqiang Chen*, Nengcheng Chen. Distinguishing different subclasses of water bodies for long-term and large-scale statistics of lakes: A case study of the Yangtze River basin from 2008 to 2018. International Journal of Digital Earth, 2021, 14(2): 202-230.

[26]     Wei Wang, Hui Lin, Hui, Nengcheng Chen, Zeqiang Chen*. Evaluation of multi-source precipitation products over the Yangtze River Basin. Atmospheric research, 2021, 249, 105287.

[27]     Gaoyun Shen, Nengcheng Chen*, Wei Wang, Zeqiang Chen*. WHU-SGCC: a novel approach for blending daily satellite (CHIRP) and precipitation observations over the Jinsha River basin. Earth System Science Data, 2019, 11: 1711-1744.

[28]     Changjiang Xiao, Nengcheng Chen, Chuli Hu, Ke Wang, Jianya Gong, Zeqiang Chen*. Short and mid-term sea surface temperature prediction using time-series satellite data and LSTM-AdaBoost combination approach. Remote Sensing of Environment, 2019, 233: 111358.

[29]     Lei Xu, Nengcheng Chen*, Xiang Zhang, Zeqiang Chen*, C. Hu, C. Wang. Improving the North American multi-model ensemble (NMME) precipitation forecasts at local areas using wavelet and machine learning. Climate Dynamics, 2019, 53: 601–615.

[30]     Zeqiang Chen, Jin Luo, Nengcheng Chen*, Ren Xu, Gaoyun Shen. RFim: A Real-Time Inundation Extent Model for Large Floodplains Based on Remote Sensing Big Data and Water Level Observation. Remote Sensing, 2019, 11: 1585.

[31]     Zeqiang Chen, Nengcheng Chen*, W. Du, J. Gong. An Active Monitoring Method for Flood Events. Computers & Geosciences, 2018, 116: 42-52.

[32]     Jianya Gong, Jing Geng, Zeqiang Chen*. Real-time GIS data model and sensor web service platform for environmental data management, International Journal of Health Geographics, 2015, 14.

[33]  Zeqiang Chen, Nengcheng Chen, Chao Yang, Liping Di. Cloud Computing Enabled Web Processing Service for Earth Observation Data Processing. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2012, 5(6): 1637-1649.

发明专利：

     [1]  陈泽强,李志庆, 陈能成, 陈来.基于SRFNet的洪涝灾害过程分析方法、介质及设备, CN202411140193.0, 2024

  [2]  陈泽强,许政,徐鸿飞, 周继新,刘栋阳, 陈能成.城市街道场景典型犯罪事件风险评估方法、介质及设备, CN202410886551.6, 2024

  [3]  陈泽强,李嘉舜,刘栋阳,唐国轩,陈能成.一种基于混沌映射的任务自适应分发方法、设备及介质, CN202410722074.X, 2024

        [4]  陈泽强,唐旭,陈能成.一种基于Transformer和大核卷积的时空过程预测方法及系统, CN202410507032.4, 2024

        [5]  陈泽强,刘杰,陈添苗,万可,段昱韩,陈康耀,李鹏翔,陈能成.一种基于大数据技术的中国智慧城市评估方法及系统, CN202410153300.7, 2024

        [6]  陈泽强,刘杰,李星昊,万可,陈添苗,吴磊,李鹏翔,陈能成.一种基于大数据技术的数字航道快速成图方法及系统, CN202410146528.3, 2024

        [7]  陈泽强,刘栋阳, 陈能成.基于通信频率优化和误差补偿机制的分布式深度学习方法, CN202310862810.7, 2023

        [8]  陈泽强, 陈来, 陈能成, 陈添苗.洪涝淹没数据集制作方法及系统, CN202310683064.5, 2023

        [9]  陈泽强,邹童旭, 张岩,陈能成.一种城市街道机动车碳排放预测和可视化方法及装置, CN202310613105.3, 2023

        [10] 陈泽强,李嘉舜, 陈能成. 一种时空过程深度学习模型实时流数据增量学习方法, CN202310037734.6, 2023

        [11] 陈泽强, 唐旭,陈来,陈能成.基于堆叠时空记忆单元的时空过程模拟方法及系统, CN202211377100.7, 2022

        [12] 陈泽强, 潘慧文, 邹童旭, 陈能成.基于多源大数据的时空过程智能分析挖掘方法与系统, CN202211018917.5, 2022

        [13] 陈泽强,陈能成.基于长短期记忆神经网络的降雨-径流时空关系模拟方法, CN202110901370.2, 2021

学术著作：

[1]     陈能成，王伟，王超，陈泽强，胡楚丽. 智慧城市综合管理，科学出版社，2015.

[2]     陈能成，陈泽强，何杰，闵敏. 对地观测传感网信息服务的模型与方法，武汉大学出版社，2013.

荣誉奖励：

[1]     楚天学子，湖北省教育厅，2014

[2]     联合国国际电信联盟物联网与智慧城市和社区标准组（ITU-T SG20）标准制订奖，ITU-T SG20，2024

[3]     湖北省自然科学技术二等奖（排名3），湖北省人民政府，2024

[4]     中国水运建设行业协会科学技术二等奖（排名4），中国水运建设行业协会，2024

[5]     测绘科学技术特等奖（排名9），中国测绘学会，2022

[6]     中国水运建设行业协会科技进步二等奖（排名14），中国水运建设行业协会，2022

[7]     高等学校科技进步科学奖一等奖（排名16），教育部，2016

[8]     高等学校自然科学奖一等奖（排名4），教育部，2014

[9]     测绘科技进步奖二等奖（排名9），中国测绘地理信息协会，2014

学生招生：

硕士招生学科：

0705|地理学-->070500|地理学

0854|电子信息-->085400|电子信息

0857|资源与环境-->085700|资源与环境

博士招生学科：

081600|测绘科学与技术

人才招聘【常年招聘】：

国家地理信息系统工程技术研究中心诚聘海内外优秀人才