许磊，男，国家地理信息系统工程技术研究中心特任教授，地图学与地理信息系统专业，博士毕业于武汉大学测绘遥感信息工程国家重点实验室，长期从事地理时空预测、时空大数据分析、不确定性建模研究，目前在Earth-Science Reviews、Remote Sensing of Environment、Geophysical Research Letters、Water Resources Research、Journal of Geophysical Research: Atmospheres等期刊发表SCI论文 30 余篇（其中第一作者 15篇），参与国家重点研发计划、国家自然科学基金重大项目多项。

招生方向：

欢迎对时空智能预测、时空大数据挖掘、人工智能、深度学习、遥感大数据分析、水文气象、灾害预测预警、空间统计与分析、地理学、资源与环境遥感等研究方向感兴趣的学生报考

科研项目：

国家自然科学基金青年基金项目，42201509 , 强降水人工智能短期预测可靠性传播分析方法研究，2023-2025

博士后面上基金，数据驱动的短时降水预测可靠性建模方法研究，2022M722930

科研成果：

[1]. Xu, L., Chen, N., Chen, Z., Zhang C., Yu H. (2021). Spatiotemporal forecasting in earth system science: Methods, uncertainties, predictability and future directions. Earth-Science Reviews, 103828. doi: 10.1016/j.earscirev.2021.103828

[2]. Xu, L., Chen N.C., Zhang, X., Moradkhani H., Zhang, C., Hu C. (2021). In-situ and triple-collocation based evaluations of eight global root zone soil moisture products, Remote Sensing of Environment.（高被引论文）

[3]. Xu, L., Abbaszadeh, P., Moradkhani, H., Chen, N., & Zhang, X. (2020). Continental drought monitoring using satellite soil moisture, data assimilation and an integrated drought index. Remote Sensing of Environment, 250, 112028.

[4]. Xu, L., Chen, N., Yang, C., Yu, H., and Chen, Z. Quantifying the uncertainty of precipitation forecasting using probabilistic deep learning, Hydrology and Earth System Sciences, 26, 2923–2938, https://doi.org/10.5194/hess-26-2923-2022, 2022.

[5]. Xu, L., Chen, N., Yang C., Zhang C., Yu H. (2021). A parametric multivariate drought index for drought monitoring and assessment under climate change. Agricultural and Forest Meteorology, 310, 108657. doi: 10.1016/j.agrformet.2021.108657

[6]. Xu, L., Zhang, C., Chen N.C., Moradkhani H., Chu P.S., Zhang, X. Potential precipitation predictability decreases under future warming, Geophysical Research Letters, 2020.

[7]. Xu, L., Chen, N., Moradkhani, H., Zhang, X., & Hu, C. (2020). Improving Global Monthly and Daily Precipitation Estimation by Fusing Gauge Observations, Remote Sensing, and Reanalysis Data Sets. Water Resources Research, 56(3), e2019WR026444. 

[8]. Xu, L., Chen, N., Zhang, X. and Chen, Z., 2019. Spatiotemporal changes in China's terrestrial water storage from GRACE satellites and its possible drivers. Journal of Geophysical Research: Atmospheres, 124(22), pp.11976-11993. 

[9]. Xu, L., Chen, N., Zhang, X., Chen, Z., Hu, C. and Wang, C., 2019. Improving the North American multi-model ensemble (NMME) precipitation forecasts at local areas using wavelet and machine learning. Climate Dynamics, 53(1-2), pp.601-615. 

[10].         Xu, L., Chen, N., Zhang, X. and Chen, Z., 2020. A data-driven multi-model ensemble for deterministic and probabilistic precipitation forecasting at seasonal scale. Climate Dynamics, pp.1-20. 

[11].         Xu, L., Chen, N., Zhang, X. and Chen, Z., 2018. An evaluation of statistical, NMME and hybrid models for drought prediction in China. Journal of Hydrology, 566, pp.235-249. 

[12].         Xu, L., Chen, N. and Zhang, X., 2018. A comparison of large-scale climate signals and the North American Multi-Model Ensemble (NMME) for drought prediction in China. Journal of Hydrology, 557, pp.378-390. 

[13].         Xu, L., Chen, N. and Chen, Z., 2017. Will China make a difference in its carbon intensity reduction targets by 2020 and 2030?. Applied Energy, 203, pp.874-882. 

[14].         Xu, L., Chen, N. and Zhang, X., 2019. Global drought trends under 1.5 and 2 C warming. International Journal of Climatology, 39(4), pp.2375-2385. 

[15].         Xu L, Yu H, Chen Z, Du W, Chen N, Zhang C. Monthly Ocean Primary Productivity Forecasting by Joint Use of Seasonal Climate Prediction and Temporal Memory. Remote Sensing. 2023; 15(5):1417. https://doi.org/10.3390/rs15051417

[16].         Chen, N., Xu, L. and Chen, Z., 2017. Environmental efficiency analysis of the Yangtze River Economic Zone using super efficiency data envelopment analysis (SEDEA) and tobit models. Energy, 134, pp.659-671. 

[17].         Chen N , Xu L . Relationship between air quality and economic development in the provincial capital cities of China[J]. Environmental Science & Pollution Research, 2017. 

[18].         Phan, P., Chen, N., Xu, L., & Chen, Z.  (2020). Using multi-temporal modis ndvi data to monitor tea status and forecast yield: a case study at tanuyen, laichau, vietnam. Remote Sensing, 12(11), 1814. 

[19].         Chen, Z., Zeng, Y., Shen, G., Xiao, C., Xu, L. and Chen, N., 2020. Spatiotemporal characteristics and estimates of extreme precipitation in the Yangtze River Basin using GLDAS data. International Journal of Climatology. 

[20].         Xiao, C., Chen, N., Hu, C., Wang, K., Xu, Z., Cai, Y., Xu, L., Chen, Z. and Gong, J., 2019. A spatiotemporal deep learning model for sea surface temperature field prediction using time-series satellite data. Environmental Modelling & Software, 120, p.104502. 

[21].         Zhang C, Duan Q, Yeh P J F, Pan Y, Gong H, Hamid M, Gong W, Liao W, Lei X, Xu L, Huang Z, Zheng L, Guo X. Sub-regional groundwater storage recovery in North China Plain after the South-to-North water diversion project[J]. Journal of Hydrology, 2021: 126156. 

[22].         Phan, P., Chen, N., Xu, L., Dao, D. M., & Dang, D. (2021). NDVI Variation and Yield Prediction in Growing Season: A Case Study with Tea in Tanuyen Vietnam. Atmosphere, 12(8), 962.

[23].         Yu, H., Meng, Q., Fang, Z., Liu, J. and Xu, L., 2023. A review of ship collision risk assessment, hotspot detection and path planning for maritime traffic control in restricted waters. The Journal of Navigation, pp.1-27.

[24].         Liu, J., Chen, N., Chen, Z., Xu, L., Du, W., Zhang, Y. and Wang, C., 2022. Towards sustainable smart cities: Maturity assessment and development pattern recognition in China. Journal of Cleaner Production, 370, p.133248.

[25].         Huang, S., Zhang, X., Chen, N., Ma, H., Fu, P., Dong, J., Gu, X., Nam, W.H., Xu, L., Rab, G. and Niyogi, D., 2022. A Novel Fusion Method for Generating Surface Soil Moisture Data With High Accuracy, High Spatial Resolution, and High Spatio‐Temporal Continuity. Water Resources Research, 58(5), p.e2021WR030827.

[26].         Deb, P., Moradkhani, H., Han, X., Abbaszadeh, P. and Xu, L., 2022. Assessing irrigation mitigating drought impacts on crop yields with an integrated modeling framework. Journal of Hydrology, 609, p.127760.

[27].         Liu, J., Xu, L. and Chen, N., 2022. A spatiotemporal deep learning model ST-LSTM-SA for hourly rainfall forecasting using radar echo images. Journal of Hydrology, 609, p.127748.

[28].         Zhang, C., Abbaszadeh, P., Xu, L., Moradkhani, H., Duan, Q. and Gong, W., 2021. A Combined Optimization‐Assimilation Framework to Enhance the Predictive Skill of Community Land Model. Water Resources Research, 57(12), p.e2021WR029879.

[29].         Huang, S., Zhang, X., Chen, N., Li, B., Ma, H., Xu, L., Li, R. and Niyogi, D., 2021. Drought propagation modification after the construction of the Three Gorges Dam in the Yangtze River Basin. Journal of Hydrology, 603, p.127138.

[30].         Wang, Y., Li, B. and Xu, L., 2022. Monitoring Land-Use Efficiency in China’s Yangtze River Economic Belt from 2000 to 2018. Land, 11(7), p.1009.

[31].         Wang, X., Zhang, S., Zhao, X., Shi, S. and Xu, L., 2023. Exploring the Relationship between the Eco-Environmental Quality and Urbanization by Utilizing Sentinel and Landsat Data: A Case Study of the Yellow River Basin. Remote Sensing, 15(3), p.743.

[32].         Zhou, S.; Xu, L.; Chen, N. Rice Yield Prediction in Hubei Province Based on Deep Learning and the Effect of Spatial Heterogeneity. Remote Sensing. 2023, 15, 1361. https://doi.org/10.3390/rs15051361