(Cao et al. 2024; Ding et al. 2024; Fang et al. 2024; Guan et al. 2024; Guo et al. 2024; Huang et al. 2024; Jia et al. 2024; Li et al. 2024a; Li et al. 2024b; Liang et al. 2024a; Liang et al. 2024b; Liang et al. 2024c; Lin et al. 2024; Liu et al. 2024; Ma et al. 2024a; Ma et al. 2024b; Ma et al. 2024c; Peng et al. 2024; Song et al. 2024; Wang et al. 2024; Xiao et al. 2024; Xu et al. 2024; Zhang et al. 2024; Zheng et al. 2024)

Papers published in 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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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) 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