I am a Full Professor at the School of Remote Sensing and Information Engineering, Wuhan University. My primary research interests include quantitative remote sensing of surface radiation budget, data fusion of multiscale remote sensing datasets, and spatio-temporal analysis of long-term satellite products. I have been the PIs of projects funded by Natural Science Foundation of China, Ministry of Science and Technology of the People's Republic of China, Hubei Natural Science Foundation. I have published more 90 papers in SCI-indexed journals, including RSE, IEEE TGRS, and JGR.

Contact Information

taohers at whu.edu.cn

Education Background

2012, Doctor of Philosophy, Geography, University of Maryland, USA

2006, Bachelor of Engineering, Remote Sensing Science and Technology, Wuhan University, China

2006, Bachelor of Engineering, Computer Science and Technology, Wuhan University, China

Working Experiences

2017 - present, Full Professor, Wuhan University

2018 - present, Adjunct Professor, University of Maryland

2014 - 2016,    Assistant Research Professor, University of Maryland

2012 - 2014,    Research Associate, University of Maryland

Academic Services

Associate Editor, Science of Remote Sensing

Guest Editor, Remote Sensing

Some Recent Journal Publications

2023

[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

2022

[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] Lu, J., T. He, D.-X. Song, C. Wang, (2022). Land surface phenology retrieval through spectral and angular harmonization of Landsat-8, Sentinel-2 and Gaofen-1 data. Remote Sensing, 14(5), 1296, doi: 10.3390/rs14051296

[13] Ma, H., C. Xiong, S. Liang, Z. Zhu, J. Song, Y. Zhang, T. He, (2022). Determining the accuracy of the Landsat-based land continuous Variable Estimator. Science of Remote Sensing, 100054, doi: 10.1016/j.srs.2022.100054

[14] Zhang, Y., S. Liang, T. He, D. Wang, Y. Yu, H. Ma, (2022). Estimation of land surface incident shortwave radiation from geostationary Advanced Himawari Imager and Advanced Baseline Imager observations using an optimization method. IEEE Transactions on Geoscience and Remote Sensing, 60, 5600611, doi: 10.1109/TGRS.2020.3038829 

[15] Ding, A., H. Ma, S. Liang, T. He, (2022). Extension of the Hapke model to the spectral domain to characterize soil physical properties. Remote Sensing of Environment, 269, 112843, doi: 10.1016/j.rse.2021.112843

[16] Zhou, H., Z. Wang, W. Ma, T. He, H. Wan, J. Wang, S. Liang, (2022). Land surface albedo estimation with Chinese GF-1 WFV data in Northwest China. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 15, 849-861, doi: 10.1109/JSTARS.2021.3136852 

[17] Zhang, Y., S. Liang, Z. Zhu, H. Ma, T. He, (2022). Soil moisture content retrieval from Landsat 8 data using ensemble learning, ISPRS Journal of Photogrammetry and Remote Sensing, 185, 32-47, doi: 10.1016/j.isprsjprs.2022.01.005

[18] Ma, H., S. Liang, Z. Zhu, T. He, (2022). Developing a Land continuous Variable Estimator to generate daily land products from Landsat data. IEEE Transactions on Geoscience and Remote Sensing, 60, 4406619, doi: 10.1109/TGRS.2021.3121272

[19] Liang, T., S. Liang, L. Zou, L. Sun, B. Li, H. Lin, T. He, F. Tian, (2022). Estimation of aerosol optical depth at 30 m resolution using Landsat imagery and machine learning. Remote Sensing, 14(5), 1053, doi: 10.3390/rs14051053

[20] Xu, J., S. Liang, H. Ma, T. He, (2022). Generating 5 km resolution 1981–2018 daily global land surface longwave radiation products from AVHRR shortwave and longwave observations using densely connected convolutional neural networks. Remote Sensing of Environment, 280, 113223, doi: 10.1016/j.rse.2022.113223

[21] Zhang, G., H. Ma, S. Liang, A. Jia, T. He, D. Wang, (2022). A machine learning method trained by radiative transfer model inversion for generating seven global land and atmospheric estimates from VIIRS top-of-atmosphere observations. Remote Sensing of Environment, 279, 113132, doi: 10.1016/j.rse.2022.113132

[22] Shen, W., J. He, T. He, X. Hu, C. Huang, (2022). Biophysical effects of afforestation on land surface temperature in Guangdong Province, Southern China. Journal of Geophysical Research: Biogeosciences, 127, e2022JG006913, doi: 10.1029/2022JG006913

[23] Jin, H., A. Li, S. Liang, H. Ma, X. Xie, T. Liu, T. He, (2022). Generating high spatial resolution GLASS FAPAR product from Landsat images. Science of Remote Sensing, 6, 100060, doi: 10.1016/j.srs.2022.100060

2021

[1] Song, D-X., C. Huang, T. He, M. Feng, A. Li, S. Li, Y. Pang, H. Wu, A. R. M. Shariff, J. R. Townshend, (2021). Very rapid forest cover change in Sichuan province, China: 40 years of change using images from declassified spy satellites and Landsat. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14:10964–10976, doi: 10.1109/JSTARS.2021.3121260

[2] 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

[3] Chen, Y., S. Liang, H. Ma, B. Li, T. He, Q. Wang, (2021). An all-sky 1 km daily land surface air temperature product over mainland China for 2003–2019 from MODIS and ancillary data. Earth System Science Data, 13(8): 4241–4261, doi: 10.5194/essd-13-4241-2021

[4] Li, B., S. Liang, X. Liu, H. Ma, Y. Chen, T. Liang, T. He, (2021). Estimation of all-sky 1 km land surface temperature over the conterminous United States. Remote Sensing of Environment, 266, 112707, doi: 10.1016/j.rse.2021.112707

[5] Lin, H., S. Li, J. Xing, T. He, J. Yang, Q. Wang, (2021). High resolution aerosol optical depth retrieval over urban areas from Landsat-8 OLI images. Atmospheric Environment, 261, 118591, doi: 10.1016/j.atmosenv.2021.118591

[6] Liu, X., S. Liang, B. Li, H. Ma, T. He, (2021). Mapping 30 m fractional forest cover over China’s Three-North Region from Landsat-8 data using ensemble machine learning methods. Remote Sensing, 13(13): 2592, doi: 10.3390/rs13132592

[7] 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

[8] Song, D., C. Huang, J.O. Sexton, T. He, A. Li, and J.R. Townshend, (2021). Improved modeling and analysis of the patch size–frequency distribution of forest disturbances in China based on a Landsat forest cover change product. International Journal of Digital Earth,14(2):181-201, doi: 10.1080/17538947.2020.1810337 

2020

[1] Zhang, Y., S. Liang, T. He, D. Wang, Y. Yu, (2020). Estimation of land surface incident and net shortwave radiation from Visible Infrared Imaging Radiometer Suite (VIIRS) using an optimization method. Remote Sensing, 12(24), 4153, doi: 10.3390/rs12244153

[2] Huang, G., X. Li, N. Lv, X. Wang, T. He, (2020). A general parameterization scheme for the estimation of incident Photosynthetically Active Radiation under cloudy skies. IEEE Transactions on Geoscience and Remote Sensing, 58(9): 6255-6265, doi: 10.1109/TGRS.2020.2976103

[3] 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

[4] Campana, P. E., T. Landelius, S. Andersson, L. Lundström, E. Nordlander, T. He, J. Zhang, B. Stridh, J. Yan, (2020). A gridded optimization model for photovoltaic applications. Solar Energy, 202, 465-484, doi: 10.1016/j.solener.2020.03.076

[5] Zhang, X., Z. Jiao, Y. Dong, T. He, A. Ding, S. Yin, H. Zhang, L. Cui, Y. Chang, J. Guo, and R. Xie, (2020). Development of the direct-estimation albedo algorithm for snow-free Landsat TM albedo retrievals using field flux measurements. IEEE Transactions on Geoscience and Remote Sensing, 58(3), 1550-1567, doi: 10.1109/TGRS.2019.2946598

[6] Brown, M., S. Skakun, T. He, and S. Liang, (2020). Intercomparison of machine-learning methods for estimating surface shortwave and photosynthetically active radiation. Remote Sensing, 12(3), 372, doi:10.3390/rs12030372

[7] 梁顺林，白瑞，陈晓娜，程洁，范闻捷，何涛，贾坤，江波，蒋玲梅，焦子锑，刘元波，倪文俭，邱凤，宋柳霖，孙林，唐伯惠，闻建光，吴桂平，谢东辉，姚云军，袁文平，张永光，张玉珍，张云腾，张晓通，赵天杰，赵祥. (2020). 2019年中国陆表定量遥感发展综述. 遥感学报，24(6)：618-671 [DOI：10.11834/jrs.20209476]

2019

[1] Wang, Y., B. Jiang, S. Liang, D. Wang, T. He, Q. Wang, X. Zhao, and J. Xu, (2019). Surface shortwave net radiation estimation from Landsat TM/ETM+ data using four machine learning algorithms. Remote Sensing, 11(23), 2847, doi: 10.3390/rs11232847

[2] 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

[3] Roujean, J.-L., S. Liang, T. He, (2019). Editorial for Special Issue: “Remotely Sensed Albedo”. Remote Sensing, 11(19), 1941, doi: 10.3390/rs11161941

[4] Li, X., R. Ma, Q. Zhang, D. Li, S. Liu, T. He, L. Zhao, (2019). Anisotropic characteristic of artificial light at night - systematic investigation with VIIRS DNB multi-temporal observations. Remote Sensing of Environment, 233, 111357, doi: 10.1016/j.rse.2019.111357

[5] Shen, W., M. Li, C. Huang, T. He, X. Tao, A. Wei, (2019). Local land surface temperature change induced by afforestation based on satellite observations in Guangdong plantation forests in China. Agricultural and Forest Meteorology, 276-277, 107641, doi: 10.1016/j.agrformet.2019.107641

[6] Liang, S., D. Wang, T. He, Y. Yu, (2019). Remote sensing of Earth’s energy budget: synthesis and review. International Journal of Digital Earth, 12(7), 737-780, doi: 10.1080/17538947.2019.1597189

[7] Zhang, X., D. Wang , Q. Liu, Y. Yao, K. Jia, T. He, B. Jiang, Y. Wei, H. Ma, X. Zhao, W. Li, and S. Liang, (2019). An operational approach for generating the global land surface downward shortwave radiation product from MODIS data. IEEE Transactions on Geoscience and Remote Sensing, 57(7), 4636-4650, doi: 10.1109/TGRS.2019.2891945

[8] 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

[9] Zhou, H., S. Liang, T. He, J. Wang, Y. Bo, and D. Wang, (2019).Evaluating the spatial representativeness of the MODerate Resolution Image Spectroradiometer albedo product (MCD43) at AmeriFlux sites. Remote Sensing, 11(5), 547, doi: 10.3390/rs11050547

[10] Huang, X., J. Xia, R. Xiao, and T. He, (2019). Urban expansion patterns of 291 Chinese cities, 1990–2015. International Journal of Digital Earth, 12(1), 62-77, doi: 10.1080/17538947.2017.1395090