Publications

2025

 

Books Edited

 

1. Liang, S.,  (Editor-in-Chief), Comprehensive Remote Sensing, nine volumes, Elsevier, 2nd edition (Sept. 2025), ISBN: 9780443132209
    

2. Liang, S., (Editor), Earth’s Energy Budget, Vol. 5 in Comprehensive Remote Sensing, Elsevier, Sept. 2025

 

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Edited journal special issues

 

1. Zhang, H., G. Camps-Valls, S. Liang, G. Tuia, Z. Zhu (Guest editors), special issue “Advancing deep learning for time series analysis”, Remote Sensing of Environment, March, 2025

 

 

 

Articles in Refereed Journals

(*indicates the first author as a student, postdoc or team member under my primary supervision; # co-supervision) 

 

1. He, T., Han, J., Liang, S., Ma, Y., Zhang, X., Zhao, X., & Si, L. (2026). Estimation of 1 km all-sky erythemal ultraviolet radiation and daily dose based on MODIS data and ancillary information: algorithm development, global product generation, and accuracy assessment. Remote Sensing of Environment, 332, 115021
    

2. Li, R#., D. Wang, Z. Wang, S. Liang, Z. Li, Y. Xie, and J. He. (2025),Transformer approach to nowcasting solar energy using geostationary satellite data." Applied Energy 377: 124387.
    

3. Pataki, A., Bertalan, L., Pásztor, L., Nagy, L.A., Abriha, D., Liang, S., Singh, S.K., & Szabó, S. (2025). Soil Moisture Satellite Data Under Scrutiny: Assessing Accuracy Through Environmental Proxies and Extended Triple Collocation Analysis.,  Earth Syst Environ, DOI: 10.1007/s41748-025-00605-2
    

4. Zhang, Y#., He, T., Liang, S., Ma, Y., & Yao, Y. (2025). A novel approach for estimating evapotranspiration by considering topographic effects in radiation over mountainous terrain. Agricultural and Forest Meteorology, 366, 110468

5. Zhang, H., G. Camps-Valls, S. Liang, G. Tuia, Z. Zhu, (2025), Preface: Advancing deep learning for remote sensing time series data analysis, Remote Sensing of Environment, 322, 114711
    

6. Cui, D#., Frazier, A.E., Liang, S., Roehrdanz, P.R., Hurtt, G.C., Zhu, Z., Maitner, B.S., Moulatlet, G.M., & Wang, D. (2025). Projected climate zone shifts could undermine the effectiveness of global protected areas for biodiversity conservation by mid-to-late century. Global Environmental Change Advances, 5, 100017
    

7. Lin, S., Chen, X., Liang, S., Liu, Y., Li, Y., & Li, H. (2025), Monthly 0.05° winter months snow depth dataset for the Northern Hemisphere from 21 CMIP6 models, Scientific Data, 12(1), 603
    

8. Gao, X., et al., (2025), The Importance of Distinguishing Between Natural and Managed Tree Cover Gains in the Moist Tropics, Nature Communications, 16(1), 6092
    

9. Li, S., Jiang, B., Liang, S., Xiao, X., Peng, J., Liang, H., Han, J., & Yin, X. (2025). Estimation of surface all-wave net radiation from MODIS data using deep residual neural network based on limited samples. ISPRS Journal of Photogrammetry and Remote Sensing, 225, 131-143
    

10. Ma, Y*., S. Liang, T. He and W. Peng, (2025), Significant topographic impacts on moderate-resolution satellite products: Evidence from both geostationary and polar-orbiting satellites and model simulations,  IEEE Transactions on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2025.3572685
     

11. Chen, Y., Feng, X., Huang, Y., Liang, S., Wang, L., Ma, H., ... & Fu, B. (2025). Optimal spatiotemporal thinning schemes combined with wood vaulting could maximize the forest biomass carbon sink in China. Communications Earth & Environment, 6(366), 1-12.
     

12. Ma, Y*., S. Liang, et al., (2025), A universal physically-based topographic correction framework for high-resolution optical data, ISPRS Journal of Photogrammetry and Remote Sensing, 227, 459-480
     

13. Liang, H*., Liang, S., Jiang, B., He, T., Tian, F., Xu, J., ... & Fang, H. (2025). Generation of global 1 km daily land surface–air temperature difference and sensible heat flux products from 2000 to 2020. Earth System Science Data, 1-48.
     

14. Maddah, S., Khosravi, K., Jun, C., Bateni, S.M., Kim, D., & Liang, S. (2025). Assessment of a family of recurrent neural network models for flood susceptibility Mapping: An explainable glass-box approach. Engineering Applications of Artificial Intelligence, 160, 111867
     

15. Zhang, Y*., Liang, S., Ma, H., He, T., Tian, F., Zhang, G., & Xu, J. (2025). A seamless global daily 5 km soil moisture product from 1982 to 2021 using AVHRR satellite data and an attention-based deep learning model. Earth System Science Data, 17, 5181-5207
     

16. Zhang, Y., W. Li, W. Jia, M. Zhang, R. Tao and S. Liang, Cross-domain Hyperspectral Image Classification based on Bi-directional Domain Adaptation, IEEE Transactions on Circuits and Systems for Video Technology, doi: 10.1109/TCSVT.2025.3586282
     

17. Liang, S., et al., (2025), An overview of the High-resolution Global LAnd Surface Satellite (Hi-GLASS) products, Science of Remote Sensing, 12，100263
     

18. Jia, A., Wang, D., Peng, J., Ma, Z., & Liang, S. (2025). Dynamic parameterization of global land surface albedo components: Bare soil, non-photosynthetic vegetation, and photosynthetic vegetation. Remote Sensing of Environment, 329, 114943
     

19. Zhang, L., Yang, N., Zhao, B., Xie, J., Sun, X., Liang, S., Shao, H., & Wu, J. (2025). Remote Sensing and Critical Slowing Down Modeling Reveal Vegetation Resilience in the Three Gorges Reservoir Area, China. Remote Sensing, 17, 2297
     

20. Zhang, Y., H. Tang; P. Zhang; K. Yu; S. Liang, (2025), Adaptive Transformer for Multi-Temporal Thick Cloud Reconstruction with Low-Intensity Reference, IEEE Transactions on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2025.3610645
     

21. Ma, H., Wang, Q., Li, W., Chen, Y., Xu, J., Ma, Y., Huang, J., & Liang, S. (2025). The first gap-free 20 m 5-day LAI/FAPAR products over China (2018–2023) from integrated Landsat-8/9 and Sentinel-2 Analysis Ready Data. Remote Sensing of Environment, 331, 115048
     

22. Ren, B., Cao, Y., Tian, J., Liang, S., & Yu, M. (2025). Generating the 500 m Global Satellite Vegetation Productivity Phenology Product from 2001 to 2020. Remote Sensing, 17(19), 3352.
     

23. Zhang, G*., Liang, S., Ma, H., He, T., Yin, G., Xu, J., Liu, X., & Zhang, Y. (2024). Simultaneous estimation of five temporally regular land variables at seven spatial resolutions from seven satellite data using a multi-scale and multi-depth convolutional neural network. Remote Sensing of Environment, 301, 113928
     

24. Liu*, X., Liang, S., Ma, H., Li, B., Zhang, Y., Li, Y., ... & Teng, J. (2024). Landsat-observed changes in forest cover and attribution analysis over Northern China from 1996‒2020. GIScience & Remote Sensing, 61(1), 2300214.
     

25. Ma, Y#, He, T., Aguilar, C., Pimentel, R., Liang, S., McVicar, T.R., Hao, D., Xiao, X., & Liu, X. (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, 1-16
     

26. Guo, X., Yao, Y., Tang, Q., Liang, S., Shao, C., Fisher, J.B., Chen, J., Jia, K., Zhang, X., Shang, K., Yang, J., Yu, R., Xie, Z., Liu, L., Ning, J., & Zhang, L. (2024). Multimodel ensemble estimation of Landsat-like global terrestrial latent heat flux using a generalized deep CNN-LSTM integration algorithm. Agricultural and Forest Meteorology, 349, 109962
     

27. Cao, Y., Yin, M., Tian, J., & Liang, S. (2024). Increased summertime wildfire as a major driver of the clear-sky dimming in the Siberian Arctic from 2000 to 2020. Atmospheric Research, 306, 107458
     

28. Song, J., Huang, J., Huang, H., Xiao, G., Li, X., Li, L., Su, W., Wu, W., Yang, P., & Liang, S. (2024). Improving crop yield estimation by unified model parameters and state variable with Bayesian inference. Agricultural and Forest Meteorology, 355, 110101
     

29. Ma, R*., Zhang, Y., Ciais, P., Xiao, J., Xu, Y., Goll, D., & Liang, S. (2024). Stepwise Calibration of Age-Dependent Biomass in the Integrated Biosphere Simulator (IBIS) Model. Journal of Advances in Modeling Earth Systems, 16, e2023MS004048
     

30. Jia*, A., S. Liang， et al., (2024), Advances in Methodology and Generation of All-Weather Land Surface Temperature Products from Polar-Orbiting and Geostationary Satellites: A Comprehensive Review, IEEE Geoscience and Remote Sensing Magazine， 12（4）： 218-260
     

31. Huang, J., Song, J., Huang, H., Zhuo, W., Niu, Q., Wu, S., Ma, H., & Liang, S. (2024). Progress and perspectives in data assimilation algorithms for remote sensing and crop growth model. Science of Remote Sensing, 10, 100146
     

32. Ma#, Y., He, T., McVicar, T.R., Liang, S., Liu, T., Peng, W., Song, D.-X., & Tian, F. (2024). Quantifying how topography impacts vegetation indices at various spatial and temporal scales. Remote Sensing of Environment, 312, 114311
     

33. Xiao#, X., He, T., Liang, S., Liang, S., Liu, X., Ma, Y., & Wan, J. (2024). Towards a gapless 1 km fractional snow cover via a data fusion framework. ISPRS Journal of Photogrammetry and Remote Sensing, 215, 419-441
     

34. Liang, S., He, T., Huang, J., Jia, A., Zhang, Y., Cao, Y., Chen, X., Chen, X., Cheng, J., Jiang, B., Jin, H., Li, A., Li, S., Li, X., Liu, L., Liu, X., Ma, H., Ma, Y., Song, D.-X., Sun, L., Yao, Y., Yuan, W., Zhang, G., Zhang, Y., & Song, L. (2024). Advances in high-resolution land surface satellite products: A comprehensive review of inversion algorithms, products and challenges. Science of Remote Sensing, 10, 100152
     

35. Li*, B., S. Liang, Ma, H., Dong, G., Liu, X., He, T., and Zhang, Y.: (2024),Generation of global 1 km all-weather instantaneous and daily mean land surface temperatures from MODIS data, Earth Syst. Sci. Data, 16, 3795–3819, https://doi.org/10.5194/essd-16-3795-2024
     

36. Zheng#, Y., He, T., Liang, S., & Ma, Y. (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
     

37. Peng, D., Xie, X., Liang, S., Wang, Y., Tursun, A., Liu, Y., Jia, K., Ma, H., & Chen, Y. (2024). Improving evapotranspiration partitioning by integrating satellite vegetation parameters into a land surface model. Journal of Hydrology, 643, 131928. doi:https://doi.org/10.1016/j.jhydrol.2024.131928
     

38. Li, H., Zhou, Y., Zhao, X., Zhang, X., & Liang, S. (2024). A dataset of 0.05-degree leaf area index in China during 1983–2100 based on deep learning network. Scientific Data, 11, 1122
     

39. Liang, H#., Jiang, B., Liang, S., Wen, J., He, T., Zhang, X., Peng, J., Li, S., Han, J., & Yin, X. (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
     

40. Lin, S., X. Huang, C. Wang, T. He, X. Zhang, R. Shen, Q. Peng, Y. Zheng, X. Chen, J. Dong, S. Liang, and W. Yuan,  (2024), A 30-m gross primary production dataset from 2016 to 2020 in China, Scientific Data , 11, 1065
     

41. Ding *A, S, Liang, et al.,  (2024), Improved estimation of daily blue-sky snow shortwave albedo from MODIS data and reanalysis information, 10, 100163
     

42. Guan, S., Zhang, X., Zhao, W., Duan, Y., Han, X., Lv, L., Li, M., Jiang, B., Yao, Y., & Liang, S. (2024). Estimation of Near-surface Ozone Concentration across China and its Spatiotemporal Variations during the COVID-19 Pandemic. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 17, 18444-18455, DOI  - 10.1109/JSTARS.2024.3468918
     

43. Fang*, H., S. Liang, et al., (2024), A comprehensive review of rice mapping from satellite data: Algorithms, product characteristics and consistency assessment, Science of Remote Sensing  , 10, 100172
     

44. Wang, D., Peng, Q., Li, X., Zhang, W., Xia, X., Qin, Z., Ren, P., Liang, S., & Yuan, W. (2024). A long-term high-resolution dataset of grasslands grazing intensity in China. Scientific Data, 11, 119
     

45. Xu, S#., Wang, D., Liang, S., Jia, A., Li, R., Wang, Z., & Liu, Y. (2024). A novel approach to estimate land surface temperature from landsat top-of-atmosphere reflective and emissive data using transfer-learning neural network. Science of the Total Environment, 955, 176783