(Alkama et al. 2022; Cao et al. 2022; Chen et al. 2022; Ding et al. 2022a; Ding et al. 2022b; Gao et al. 2022; Guo et al. 2022; Huang et al. 2022; Jia et al. 2022; Li et al. 2022; Liang et al. 2022; Lu et al. 2022; Ma and Liang 2022; Ma et al. 2022a; Ma et al. 2022b; Ma et al. 2022c; Song et al. 2021; Xiao et al. 2022; Xu et al. 2022; Zhan and Liang 2022; Zhang et al. 2022a; Zhang et al. 2022b; Zhang et al. 2022c; Zhang et al. 2022d; Zhang et al. 2022e)

Papers published in 2022

1) Alkama, R., Forzieri, G., Duveiller, G., Grassi, G., Liang, S., & Cescatti, A. (2022). Vegetation-based climate mitigation in a warmer and greener World. Nature Communications, 13:606, doi:610.1038/s41467-41022-28305-41469

2) Cao, Y., Liang, S., Sun, L., Liu, J., Cheng, X., Wang, D., Chen, Y., Yu, M., & Feng, K. (2022). Trans-Arctic shipping routes expanding faster than the model projections. Global Environmental Change, 73, 102488

3) Chen, J., He, T., & Liang, S. (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

4) Ding, A., Liang, S., & et al (2022a). Improving the asymptotic radiative transfer model to better characterize the pure snow hyperspectral bidirectional reflectance. IEEE Trans. Geosci. Remote Sens., 60, 4303916, doi:10.1109/TGRS.2022.3144831

5) Ding, A., Ma, H., Liang, S., & He, T. (2022b). Extension of the Hapke model to the spectral domain to characterize soil physical properties. Remote Sensing of Environment, 269, 112843

6) Gao, X., Liang, S., Wang, D., Li, Y., He, B., & Jia, A. (2022). Exploration of a novel geoengineering solution: lighting up tropical forests at night. Earth System Dynamics, 1-22

7) Guo, T., He, T., Liang, S., Roujean, J.-L., Zhou, Y., & Huang, X. (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

8) Huang, X., Zheng, Y., Zhang, H., Lin, S., Liang, S., Li, X., Ma, M., & Yuan, W. (2022). High spatial resolution vegetation gross primary production product: Algorithm and validation. Science of Remote Sensing, 100049

9) Jia, A., Wang, D., Liang, S., Peng, J., & Yu, Y. (2022). Global Daily Actual and Snow-Free Blue-Sky Land Surface Albedo Climatology From 20-Year MODIS Products. Journal of Geophysical Research: Atmospheres, 127, e2021JD035987

10) Li, R., Wang, D., Liang, S., Jia, A., & Wang, Z. (2022). Estimating global downward shortwave radiation from VIIRS data using a transfer-learning neural network. Remote Sensing of Environment, 274, 112999

11) Liang, T., Liang, S., Zou, L., Sun, L., Li, B., Lin, H., He, T., & Tian, F. (2022). Estimation of Aerosol Optical Depth at 30 m Resolution Using Landsat Imagery and Machine Learning. Remote Sensing, 14, 1053

12) Lu, J., He, T., Liang, S., & Zhang, Y. (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, 1-11，DOI: 10.1109/TGRS.2021.3067672

13) Ma, H., & Liang, S. (2022). Development of the GLASS 250-m leaf area index product (version 6) from MODIS data using the bidirectional LSTM deep learning model. Remote Sensing of Environment, 273, 112985

14) Ma, H., Liang, S., Zhu, Z., & He, T. (2022a). Developing a Land continuous Variable Estimator to generate daily land products from Landsat data. IEEE Transactions on Geoscience and Remote Sensing, 1-16

15) Ma, H., Xiong, C., Liang, S., Zhu, Z., Song, J., Zhang, Y., & He, T. (2022b). Determining the accuracy of the landsat-based land continuous Variable Estimator. Science of Remote Sensing, 100054

16) Ma, Y., He, T., Liang, S., Wen, J., Gastellu-Etchegorry, J.-P., Chen, J., Ding, A., & Feng, S. (2022c). Landsat Snow-Free Surface Albedo Estimation Over Sloping Terrain: Algorithm Development and Evaluation. IEEE Transactions on Geoscience and Remote Sensing, 60, 4408914, doi:4408910.4401109/TGRS.4402022.3149762

17) Song, Z., Liang, S., & Zhou, H. (2021). Top-of-Atmosphere Clear-Sky Albedo Estimation Over Ocean: Preliminary Framework for MODIS. IEEE Transactions on Geoscience and Remote Sensing，60, 4203409, doi:10.1109/TGRS.2021.3116620

18) Xiao, X., He, T., Liang, S., & Zhao, T. (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

19) Xu, J., Liang, S., & Jiang, B. (2022). A global long term (1981–2019) daily land surface radiation budget product from AVHRR satellite data using a residual convolutional neural network. Earth System Science Data, 14, doi:10.5194/ess-5114-5191-2022

20) Zhan, C., & Liang, S. (2022). Improved estimation of the global top-of-atmosphere albedo from AVHRR data. Remote Sensing of Environment, 269, 112836

21) Zhang, G., Ma, H., & Liang, S. (2022a). Estimating 250-m Land Surface and Atmospheric Variables From MERSI Top-of-Atmosphere Reflectance. IEEE Transactions on Geoscience and Remote Sensing

22) Zhang, Y., Liang, S., & al., e. (2022b). 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, DOI: 10.1109/TGRS.2020.3038829

23) Zhang, Y., Liang, S., Zhu, Z., Ma, H., & He, T. (2022c). Soil moisture content retrieval from Landsat 8 data using ensemble learning. ISPRS Journal of Photogrammetry and Remote Sensing, 185, 32-47

24) Zhang, Y., Liu, J., Liang, S., & Li, M. (2022d). A New Spatial–Temporal Depthwise Separable Convolutional Fusion Network for Generating Landsat 8-Day Surface Reflectance Time Series over Forest Regions. Remote Sensing, 14, 2199

25) Zhang, Y., Ma, J., Liang, S., Li, X., & Liu, J. (2022e). A stacking ensemble algorithm for improving the biases of forest aboveground biomass estimations from multiple remotely sensed datasets. Giscience & Remote Sensing, 1-16, doi:10.1080/15481603.15482021.12023842