(Li et al. 2025; Pataki et al. 2025; Zhang et al. 2025; Zhang et al. 2025; Cui et al. 2025; Lin et al. 2025; Gao et al. 2025; Li et al. 2025; Ma et al. 2025; Chen et al. 2025; Ma et al. 2025; Liang et al. 2025; Maddah et al. 2025; Li et al. 2025; Zhang et al. 2025; Zhang et al. 2025; Liang et al. 2025; Jia et al. 2025; Zhang et al. 2025; Zhang et al. 2025; Ma et al. 2025; Ren et al. 2025; Xu et al. 2025)

Papers published in 2025

1) 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.

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, 16(1), 6092

8) 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

9) 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

10) 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.

11) 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

12) 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, 17, 5571-5600

13) 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

14) 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. arXiv preprint arXiv:2505.21357.

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) Xu, J., S. Liang, et al., (2025), Global Daily 1 km Surface Radiation Budget Components from MODIS Observations (2000-2023) Using Conservation-Constrained Deep Neural Networks, Remote Sensing of Environment.