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，研究方向为时空预测、时空大数据分析、时空统计、环境遥感等，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 50余篇，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，主持

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

湖北省自然科学基金面上项目，因果学习和物理模型耦合的长江流域降水短期预测方法研究，主持

科研论文：      

1.  Xu, L., Tao, Y., Yu, H., Du, W., Chen, Z. and Chen, N., 2026. Geographically weighted regression with convolutional neural networks to integrate attribute similarity and spatial proximity. International Journal of Geographical Information Science, pp.1-26.

2.  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

3.  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.

4.  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.

5.  Xu, L., Zhang X., Yu H., Chen Z., Du W. and Chen N., Incorporating spatial autocorrelation into Deformable ConvLSTM for hourly precipitation forecasting, Computers and Geosciences, 2024

6.  Xu, L., Zhang, X., Wu, T., Yu, H., Du, W., Zhang, C., & Chen, N. (2024). Global prediction of flash drought using machine learning. Geophysical Research Letters, 51(21), e2024GL111134.

7.  Xu, L., Ye, Z., Dai, J., Li, Q., Hong, Y., Tao, Y., ... & Chen, N. (2025). Spatiotemporal seamless estimation of global surface soil moisture using triple collocation, machine learning and data assimilation. IEEE Transactions on Geoscience and Remote Sensing.

8.  Xu, L., Zhang, X., Zhang, X., Wu, T., Yu, H., Du, W., ... & Chen, N. (2025). 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, 139, 104532.

9.  Cai, R., Xu, L.^*, Lv, Y., Wu, T., Li, X., Pan, Z., Yu, H., Du, W. and Chen, N., 2024. Geographically weighted convolutional long short-term memory neural networks: a geospatial deep learning model for monthly NDVI prediction. IEEE Transactions on Geoscience and Remote Sensing.