武汉大学遥感信息工程学院教授，博导。研究方向包括遥感反演地表短波辐射收支、多尺度遥感产品的数据融合、长时间序列遥感产品的时空分析等。主持国家自然科学基金重大项目课题、科技部重点研发项目课题、国家自然科学基金面上项目、湖北省自然科学基金杰出青年项目等。在RSE、IEEE TGRS、JGR等期刊发表SCI文章90余篇，合作撰写英文专著章节6章。获得“李小文遥感科学青年奖”、中国遥感应用协会青年科技奖特等奖，入选国家“万人计划”青年拔尖人才、湖北省“百人计划”青年项目、自然资源部“高层次科技创新人才工程”青年创新人才。担任Elsevier期刊Science of Remote Sensing副主编。

联系方式

taohers at whu.edu.cn

教育背景

2012，博士，地理学，美国马里兰大学

2006，学士，遥感科学与技术， 武汉大学

2006，学士，计算机科学与技术， 武汉大学

工作经历

2017 至今，武汉大学，教授

2018 至今，美国马里兰大学，兼职教授

2014-2016，美国马里兰大学，助理研究教授

2012-2014，美国马里兰大学，博士后

研究方向

• 辐射能量平衡参数的定量遥感反演

• 全球卫星定量遥感产品研发

• 多尺度遥感数据时空融合

• 遥感大数据挖掘与气候环境应用

科研项目

1.“高分辨率城市地表热环境关键要素定量遥感”，湖北省自然科学基金杰出青年项目, 2021-2024，负责人

2.“辐射能量平衡参量跨尺度智慧反演”, 国家自然科学基金重大项目课题，2021-2025，负责人

3.“山地生态系统全球变化关键参数产品研制与应用示范”，科技部重点研发项目课题, 2020-2025，负责人

4.“基于新一代静止卫星的地表反照率反演及中国区尺度效应研究”，国家自然科学基金面上项目，2018-2021，负责人

5.“基于多源数据的高时空分辨率地表反射率融合方法研究”，自然资源部地理国情监测重点实验室开放基金重点项目，2018-2019，负责人

近期论文 (星号为本人通讯作者，下划线为本人指导研究生）

2024年

[1] Ma, Y., T. He*, T. R. McVicar, S. Liang, T. Liu, W. Peng, D.-X. Song, F. Tian, (2024). Quantifying how topography impacts vegetation indices at various spatial and temporal scales. Remote Sensing of Environment, 312, 114311, doi: 10.1016/j.rse.2024.114311

[2] Xiao, X., T. He*, S. Liang, S. Liang, X. Liu, Y. Ma, J. Wan, (2024). Towards a gapless 1 km fractional snow cover via a data fusion framework. ISPRS Journal of Photogrammetry and Remote Sensing, 215, 419-441, doi: 10.1016/j.isprsjprs.2024.07.018

[3] Wang, C., T. He*, D.-X. Song, L. Zhang, P. Zhu, Y. Man, (2024). Comparison of change-based and shape-based data fusion methods in fine-resolution land surface phenology monitoring with Landsat and Sentinel-2 data. Science of The Total Environment, 927, 172014, doi: 10.1016/j.scitotenv.2024.172014

[4] Ma, Y., T. He*, C. Aguilar, R. Pimentel, S. Liang, T. R. McVicar, D. Hao, X. Xiao, X. Liu, (2024). Evaluating topographic effects on kilometer-scale satellite downward shortwave radiation products: A case study in mid-latitude mountains. IEEE Transactions on Geoscience and Remote Sensing, 62, 5609816, doi: 10.1109/TGRS.2024.3365865

[5] Zheng, Y., T. He*, S. Liang and Y. Ma, (2024). Deriving high resolution estimation of TOA net shortwave radiation over global land using data from multiple-geostationary satellites, IEEE Transactions on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2024.3440329

[6] Yang, X., T. He*, Y. Ma, Q. Huang, W. Zhang and N. Xu, (2024). A direct estimation method for daily mean albedo with multiple observations from FY-4A AGRI and Himawari-8 AHI, IEEE Transactions on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2024.3458178

[7] Liang H., B. Jiang, S. Liang, J. Wen, T. He, X. Zhang, J. Peng, S. Li, J. Han, and X. Yin, (2024). A novel terrain correction sinusoidal model for improving estimation of daily clear-sky downward shortwave radiation, IEEE Transactions on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2024.3452791

[8] Liang, S., T. He, J. Huang, A. Jia, Y. Zhang, Y. Cao, X. Chen, X. Chen, J. Cheng, B. Jiang, H. Jin, A. Li, S. Li, X. Li, L. Liu, X. Liu, H. Ma, Y. Ma, D.-X. Song, L. Sun, L. Song, (2024). Advancements in high-resolution land surface satellite products: A comprehensive review of inversion algorithms, products and challenges, Science of Remote Sensing, 10, 100152, doi: 10.1016/j.srs.2024.100152

2023年

[1] Zhang, Y., T. He*, S. Liang, Z. Zhao, (2023). A framework for estimating actual evapotranspiration through spatial heterogeneity-based machine learning approaches. Agricultural Water Management, 289, 108499, doi: 10.1016/j.agwat.2023.108499

[2] Liu, X., T. He*, S. Liang, R. Li, X. Xiao, R. Ma, Y. Ma, (2023). A monthly 1° resolution dataset of daytime cloud fraction over the Arctic during 2000–2020 based on multiple satellite products. Earth System Science Data, 15(8), 3641-3671, doi: 10.5194/essd-15-3641-2023

[3] Ma, Y., T. He*, S. Liang, T. R. McVicar, D. Hao, T. Liu, B. Jiang, (2023). Estimation of fine spatial resolution all-sky surface net shortwave radiation over mountainous terrain from Landsat 8 and Sentinel-2 data. Remote Sensing of Environment, 285, 113364, doi: 10.1016/j.rse.2022.113364

[4] Liu, T., T. He*, Y. Ma, X. Zhang, (2023). Evaluation and intercomparison of multiple satellite-derived and reanalysis downward shortwave radiation products in China. International Journal of Digital Earth, 16(1), 1853-1884, doi: 10.1080/17538947.2023.2212918

[5] Xu, J., S. Liang, H. Ma, T. He, Y. Zhang, G. Zhang, (2023). A daily 5-km all-sky sea-surface longwave radiation product based on statistically modified deep neural network and spatiotemporal analysis for 1981–2018. Remote Sensing of Environment, 290, 113550, doi: 10.1016/j.rse.2023.113550

[6] Shen, W., Q. Liu, M. Ji, J. He, T. He, C. Huang, (2023). Impacts of urban forests and landscape characteristics on land surface temperature in two urban agglomeration areas of China. Sustainable Cities and Society, 99, 104909, doi: 10.1016/j.scs.2023.104909

[7] Zou, L., F. Tian, T. Liang, L. Eklundh, X. Tong, T. Tagesson, Y. Dou, T. He, S. Liang, R. Fensholt, (2023). Assessing the upper elevational limits of vegetation growth in global high-mountains. Remote Sensing of Environment, 286, 113423, doi: 10.1016/j.rse.2022.113423

[8] Jiang, B., J. Han, H. Liang, S. Liang, X. Yin, J. Peng, T. He, Y. Ma, (2023). The Hi-GLASS all-wave daily net radiation product: Algorithm and product validation. Science of Remote Sensing, 7, 100080, doi: 10.1016/j.srs.2023.100080

[9] Zhang, Y., S. Liang, H. Ma, T. He, Q. Wang, B. Li, J. Xu, G. Zhang, X. Liu, C. Xiong, (2023). Generation of global 1 km daily soil moisture product from 2000 to 2020 using ensemble learning. Earth System Science Data, 15, 2055–2079, doi: 10.5194/essd-15-2055-2023

[10] Wang, Z., D.-X. Song, T. He, J. Lu, C. Wang, D. Zhong, (2023). Developing spatial and temporal continuous fractional vegetation cover based on Landsat and Sentinel-2 data with a deep learning approach. Remote Sensing, 15(11), 2948, doi: 10.3390/rs15112948

2019-2022年部分论文

[1] Ma, Y., T. He*, S. Liang, X. Xiao, (2022). Quantifying the impacts of DEM uncertainty on clear-sky surface shortwave radiation estimation in typical mountainous areas. Agricultural and Forest Meteorology, 327, 109222, doi: 10.1016/j.agrformet.2022.109222

[2] Liu, X., T. He*, L. Sun, X. Xiao, S. Liang, S. Li, (2022). Analysis of daytime cloud fraction spatio–temporal variation over the Arctic during 2000–2019 from multiple satellite products. Journal of Climate, 35(23), 3995–4023, doi: 10.1175/JCLI-D-22-0007.1

[3] Xiao, X., T. He*, S. Liang, X. Liu, Y. Ma, S. Liang, X. Chen, (2022). Estimating fractional snow cover in vegetated environments using MODIS surface reflectance data. International Journal of Applied Earth Observation and Geoinformation, 114, 103030, doi: 10.1016/j.jag.2022.103030

[4] Zhang, Y., S. Liang, T. He*, (2022). Estimation of land surface downward shortwave radiation using spectral-based convolutional neural network methods: a case study from the Visible Infrared Imaging Radiometer Suite (VIIRS) Images. IEEE Transactions on Geoscience and Remote Sensing, 60, 4414415, doi: 10.1109/TGRS.2022.3210990

[5] Guo, T., T. He*, S. Liang, J.-L. Roujean, Y. Zhou, X. Huang, (2022). Multi-decadal analysis of high-resolution albedo changes induced by urbanization over contrasted Chinese cities based on Landsat data. Remote Sensing of Environment, 269, 112832, doi: 10.1016/j.rse.2021.112832

[6] Lu, J., T. He*, S. Liang, Y. Zhang, (2022). An automatic radiometric cross-calibration method for wide-angle medium-resolution multispectral satellite sensor using Landsat data. IEEE Transactions on Geoscience and Remote Sensing, 60, 5604011, doi: 10.1109/TGRS.2021.3067672

[7] Chen, J., T. He*, S. Liang, (2022). Estimation of daily all-wave surface net radiation with multispectral and multitemporal observations from GOES-16 ABI. IEEE Transactions on Geoscience and Remote Sensing, 60, 4407916, doi: 10.1109/TGRS.2022.3140335

[8] Ma, Y., T. He*, S. Liang, J. Wen, J-P. Gastellu-Etchegorry, J. Chen, A. Ding, S. Feng, (2022). Landsat snow-free surface albedo estimation over sloping terrain: Algorithm development and evaluation. IEEE Transactions on Geoscience and Remote Sensing, 60, 4408914, doi: 10.1109/TGRS.2022.3149762

[9] Xiao, X., T. He*, S. Liang, T. Zhao, (2022). Improving fractional snow cover retrieval from passive microwave data using a radiative transfer model and machine learning method. IEEE Transactions on Geoscience and Remote Sensing, 60, 4304215, doi: 10.1109/TGRS.2021.3128524

[10] Zhao, R., T. He*, (2022). Estimation of 1-km resolution all-sky instantaneous erythemal UV-B with MODIS data based on a deep learning method. Remote Sensing, 14(2), 384, doi: 10.3390/rs14020384

[11] Song, D.-X., Z. Wang, T. He*, H. Wang, S. Liang, (2022). Estimation and validation of 30 m fractional vegetation cover over China through integrated use of Landsat 8 and Gaofen 2 data. Science of Remote Sensing, 100058, doi: 10.1016/j.srs.2022.100058

[12] Ma, Y., T. He*, A. Li, S. Li, (2021). Evaluation and intercomparison of topographic correction methods based on Landsat images and simulated data. Remote Sensing, 13(20): 4120, doi: 10.3390/rs13204120

[13] Xiao, X., S. Liang, T. He*, D. Wu, C. Pei, J. Gong, (2021). Estimating fractional snow cover from passive microwave brightness temperature data using MODIS snow cover product over North America. The Cryosphere, 15(2): 835–861, doi:10.5194/tc-15-835-2021

[14] Chen, J., T. He*, B. Jiang, S. Liang, (2020). Estimation of all-sky all-wave daily net radiation at high latitudes from MODIS data. Remote Sensing of Environment, 245, 111842, doi: 10.1016/j.rse.2020.111842

[15] He, T.*, Y. Zhang, S. Liang, Y. Yu, and D. Wang, (2019). Developing land surface directional reflectance and albedo products from geostationary GOES-R and Himawari data: Theoretical basis, operational implementation, and validation. Remote Sensing, 11(22), 2655, doi: 10.3390/rs11222655

[16] He, T.*, F. Gao, S. Liang, and Y. Peng, (2019). Mapping climatological bare soil albedo over the contiguous United States using MODIS data. Remote Sensing,11(6), 666, doi: 10.3390/rs11060666