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Publications

2025

 

Books Edited

 

  1. Liang, S., (Editor), Global Land Climate Data Records: Production, amalysisand applications (in Chinese), Science Press, Beijing, expected to be published in August 2025.
     

  2. Liang, S. and H. Ma, (Editors), Handbook of Satellite Land Products, Elsevier, Dec. 2025. (expected)

 

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Edited journal special issues

 

  1. Zhang, X. P., et al., (2025), Artificial Intelligence for Smart Agriculture, IEEE Journal pf Special Topics on Signal Processing.
     

  2. 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. Li, R#., D. Wang, Z. Wang, S. Liang, Z. Li, Y. Xie, and J. He. (2025),Transformerapproach to nowcasting solar energy using geostationary satellite data." Applied Energy377: 124387.
     

  2. 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.
     

  3. 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.
     

  4. 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.
     

  5. 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.
     

  6. 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.
     

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

  8. Li, W*., Liang, S., Chen, K., Chen, Y., Ma, H., Xu, J., ... & Shi, Z. (2025). AgriFM: A Multi-source Temporal Remote Sensing Foundation Model for Crop Mapping. arXivpreprint arXiv:2505.21357.
     

  9. 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 Discussions, 2025, 1-39. 

2024

 

  1. 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. [link to article]
     

  2. Ding, A., Liang, S., Ma, H., He, T., Jia, A., & Wang, Q. (2024). Improved estimation of daily blue-sky snow shortwave albedo from MODIS data and reanalysis information. Science of Remote Sensing, 10, 100163. [link to article] [pdf]
     

  3. Fang, H., Liang, S., Chen, Y., Ma, H., Li, W., He, T., Tian, F., & Zhang, F. (2024). A comprehensive review of rice mapping from satellite data: Algorithms, product characteristics and consistency assessment. Science of Remote Sensing, 100172. [link to article] [pdf]
     

  4. 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. [link to article] [pdf]
     

  5. Guo, X., Yao, Y., Tang, Q., Liang, S., Shao, C., Fisher, J.B., Chen, J., Jia, K., Zhang, X., & Shang, K. (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. [link to article]
     

  6. 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, 100146. [link to article] [pdf]
     

  7. Jia, A., Liang, S., Wang, D., Mallick, K., Zhou, S., Hu, T., & Xu, S. (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, 218 – 260. [link to article]
     

  8. Li, B., Liang, S., Ma, H., Dong, G., Liu, X., He, T., & Zhang, Y. (2024a). Generation of global 1 km all-weather instantaneous and daily mean land surface temperatures from MODIS data. Earth System Science Data, 16, 3795-3819. [link to article] [pdf]
     

  9. Li, H., Zhou, Y., Zhao, X., Zhang, X., & Liang, S. (2024b). A dataset of 0.05-degree leaf area index in China during 1983-2100 based on deep learning network. Scientific Data, 11, 1122. [link to article] [pdf]
     

  10. Liang, H., Jiang, B., Liang, S., Wen, J., He, T., Zhang, X., Peng, J., Li, S., Han, J., & Yin, X. (2024a). 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. [link to article]
     

  11. Liang, S., He, T., Huang, J., Jia, A., Zhang, Y., Cao, Y., Chen, X., Chen, X., Cheng, J., & Jiang, B. (2024b). Advances in high-resolution land surface satellite products: A comprehensive review of inversion algorithms, products and challenges. Science of Remote Sensing, 100152. [link to article] [pdf]
     

  12. Liang, T., Tian, F., Zou, L., Jin, H., Tagesson, T., Rumpf, S., He, T., Liang, S., & Fensholt, R. (2024c). Global assessment of vegetation patterns along topographic gradients. International Journal of Digital Earth, 17, 2404232. [link to article] [pdf]
     

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

  14. Liu, X., Liang, S., Ma, H., Li, B., Zhang, Y., Li, Y., He, T., Zhang, G., Xu, J., & Xiong, C. (2024). Landsat-observed changes in forest cover and attribution analysis over Northern China from 1996-2020. Giscience & Remote Sensing, 61, 2300214. [link to article] [pdf]
     

  15. Ma, R., Zhang, Y., Ciais, P., Xiao, J., Xu, Y., Goll, D., & Liang, S. (2024a). Stepwise calibration of age-dependent biomass in the integrated biosphere simulator (IBIS) model. Journal of Advances in Modeling Earth Systems, 16, e2023MS004048. [link to article] [pdf]
     

  16. Ma, Y., He, T., Aguilar, C., Pimentel, R., Liang, S., McVicar, T.R., Hao, D., Xiao, X., & Liu, X. (2024b). 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. [link to article] [pdf]
     

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

  18. 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. [link to article]
     

  19. 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. [link to article]
     

  20. 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, 1194. [link to article] [pdf]
     

  21. 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. [link to article] [pdf]
     

  22. 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. [link to article]
     

  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. [link to article]
     

  24. 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. [link to article] [pdf]

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