(He et al. 2026; Xu et al. 2026; Chen et al. 2026; Ma et al. 2026; Zhang et al. 2026; Qiao et al. 2026; Li et al. 2026; Fang et al. 2026; Li et al. 2026; Jiang et al. 2026; Parisouj et al. 2026; Liu et al. 2026; Xiao et al. 2026; Chen et al. 2026; Ma et al. 2026; Liu et al. 2026; Zhao et al. 2026; Ma et al. 2026; Li et al. 2026; Tian et al. 2026; Zhang et al. 2026)

Papers published in 2026

  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. Xu*, J., Liang, S., Ma, H., Chen, Y., Li, W., Ma, Y., Zhao, X., Jiang, B., Zhang, X., & Guan, S. (2026). Joint estimation of global daily 1 km surface radiation budget components from MODIS observations (2000-2023) using conservation-constrained deep neural networks. Remote Sensing of Environment, 333, 11513
  3. Chen*, Y., Liang, S., Liu, H., Sucharitakul, P., Leng, X., Fang, H., ... & Yin, L. (2026). Monitoring sub-canopy inundation dynamics in global croplands: An unexplored application of SWOT satellite data. Agricultural Water Management, 323, 110075.
  4. Ma*, Y., Liang, S., Ma, H., He, T., Shi, X., Li, W., Cai, D., Xiao, X., Guan, S., Liu, W., Xu, J., Chen, Y., & Zhang, Y. (2026). An integrated atmospheric-topographic correction framework for land surface reflectance estimation using a spatial-spectral Attention U-Net model. Remote Sensing of Environment, 334, 115188
  5. Zhang*, F., S. Liang, et al., (2026), A review of crop yield estimation on pixel and field scales from remotely sensed data, Scoemce of Remote Sensing, 100342
  6. Qiao, Y., Jin, H., He, T., Liang, S., Tian, F., Zhao, W., & Liu, Z. (2026). High spatial resolution GLASS FAPAR (version 2) product from Landsat imagery: Algorithm development using a knowledge transfer strategy. International Journal of Applied Earth Observation and Geoinformation, 146, 105051
  7. Li,* W., Liang, S., Chen, K., Chen, Y., Ma, H., Xu, J., Ma, Y., Zhang, Y., Guan, S., Fang, H., & Shi, Z. (2026). AgriFM: A multi-source temporal remote sensing foundation model for Agriculture mapping. Remote Sensing of Environment, 334, 115234
  8. Fang*, H., Liang, S., Li, W., Chen, Y., Ma, H., Xu, J., Ma, Y., He, T., Tian, F., Zhang, F., & Liang, H. (2026). Generating an annual 30 m rice cover product for monsoon Asia (2018-2023) using harmonized Landsat and Sentinel-2 data and the NASA-IBM geospatial foundation model. Remote Sensing of Environment, 335, 115256
  9. Li,* W., S. Liang, Chen, Y., Ma, H., Xu, J., Ma, Y., Chen, Z., Fang, H., & Zhang, F. (2026). A CNN-Transformer Hybrid Framework for Mapping Annual Wheat Fractional Cover from 2001-2023 using MODIS Satellite Data over Asia. IEEE Journal of Selected Topics in Signal Processing, 20(2), 153-167. DOI: 10.1109/JSTSP.2026.3660045
  10. Jiang, Q., et al., (2026), Promoting Sustainable Development Worldwide in the Metacoupled Anthropocene, Nature Communications, 17, 1491
  11. Parisouj, P., Jun, C., Bateni, S. M., & Liang, S.. (2026), Innovative Optimization-Driven Machine Learning Models for Hourly Streamflow Forecasting, Knowledge-Based Systems, 115487
  12. Liu, Z., Feng, Y., Cao, X., Peñuelas, J., Descals, A., Yang, D., Cheung, K.K., Liu, S., Lin, Z., Liu, X., Wu, X., Ma, H., Li, W., Xia, H., Jin, S., Liang, S., Liu, L., Liu, L., Su, Y., Chen, J., & Wu, J. (2026). Integrating very-high-resolution imagery, Sentinel-2 time-series data, and machine learning to map shrub fractional abundance across arid and semi-arid ecosystems in China. Remote Sensing of Environment, 335, 115300
  13. Xiao, Z., Li, R., Song, X., Ding, M., & Liang, S. (2026). Integrating spatiotemporal similarity for robust gap-filling in continuous surface water mapping with uncertainty quantification. ISPRS Journal of Photogrammetry and Remote Sensing, 234, 134-150
  14. Chen*, Y., S. Liang, et al., (2026), Mapping paddy rice cropping intensity and planting dates in Monsoon Asia at 20 m resolution during 2018-2021 from multi-source satellite data, Journal of Remote Sensing, 6, 1045
  15. Ma, Y., T. He, S. Liang, et al., (2026), Estimating downward shortwave radiation incorporating topographic effects using a hybrid physical and data-driven method: Algorithm development and long-term global product generation, Remote Sensing of Environment, 340, 115402
  16. Liu, Z., et al. (2026), China's Net Zero Budget, Nature Reviews Earth and Environment, 1628, 18, DOI: 10.1038/s43017-026-00791-1
  17. Zhao, Y., Jiang, B., Liang, S., Li, A., He, T., Miao, G., Zhang, Z., Yin, X., Chen, Y., Zhao, X., Zhang, X., Yao, Y., & Tan, X. (2026). A new model for estimating topography-modulated daily net radiation under all-sky conditions. IEEE Transactions on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2026.3685283
  18. Ma*, Y., S Liang, et al. (2026), Mitigating Topographic Effects in Optical Remote Sensing: From Surface Reflectance to High-Level Products, IEEE Geoscience and Remote Sensing Magazine, DOI: 10.1109/MGRS.2026.3690171
  19. Li, W., Liang, S., Zhang, Y., Liu, L., Chen, K., Chen, Y., Ma, H., Xu, J., Ma, Y., Guan, S., & Shi, Z. (2026). Fine-grained hierarchical crop type classification from integrated hyperspectral EnMAP data and multispectral sentinel-2 time series: A large-scale dataset and dual-stream transformer method. Remote Sensing of Environment, 344, 115525
  20. Tian, Jie, Xiaojuan Huang, Huilin Chen, Jing Ming Chen, Philippe Ciais, Maarten Krol, Shunlin Liang et al. (2026), "The size of tropical vegetation gross primary production." Nature 654, no. 8117.
  21. Zhang, Y., Li, W., Zhang, M., Han, J., Tao, R., & Liang, S. (2026). SpectralX: Parameter-efficient domain generalization for spectral remote sensing foundation models.. ISPRS Journal of Photogrammetry and Remote Sensing, 239: 774-792