Publications 2023

  1. Zuo et al., 2023. Simulating Potential Tree Height for Beech–Maple–Birch Forests in Northeastern United States on Google Earth Engine, J. Remote Sens., 2023;3:Article 0084. https://doi.org/10.34133/remotesensing.0084
  2. Cao et al., 2023. Spatiotemporally consistent global dataset of the GIMMS leaf area index (GIMMS LAI4g) from 1982 to 2020, Earth Syst. Sci. Data, 15, 4877–4899, 2023, https://doi.org/10.5194/essd-15-4877-2023
  3. Pan et al., 2023. Climate-driven land surface phenology advance is overestimated due to ignoring land cover changes, Env. Res. Lett., 18 044045, https://doi.org/10.1088/1748-9326/acca34.
  4. Li et al., 2023. Spatiotemporally consistent global dataset of the GIMMS Normalized Difference Vegetation Index (PKU GIMMS NDVI) from 1982 to 2022, Earth Syst. Sci. Data, 15, 4181–4203, https://doi.org/10.5194/essd-15-4181-2023, 2023.
  5. Zeng et al., 2023. Structural complexity biases vegetation greenness measures. Nat Ecol Evol (2023). https://doi.org/10.1038/s41559-023-02187-6
  6. Gao et al., 2023. Evaluating the saturation effect of vegetation indices in forests using 3D radiative transfer simulations and satellite observations. Remote Sens. Environ., doi: 10.1016/j.rse.2023.113665
  7. Zhang et al., 2023. Autumn canopy senescence has slowed down with global warming since the 1980s in the Northern Hemisphere. Comm. Earth and Environ., doi: 10.1038/s43247-023-00835-0
  8. Wang et al., 2023. Improving the Quality of MODIS LAI Products by Exploiting Spatiotemporal Correlation Information. IEEE Trans. Geosci. Remote Sens., doi: 10.1109/TGRS.2023.3264280
  9. Meng et al., 2023. Climate change increases carbon allocation to leaves in early leaf green-up. Ecol. Lett., doi: 10.1111/ele.14205
  10. Tucker et al., 2023. Sub-continental-scale carbon stocks of individual trees in African drylands. Nature, doi: 10.110.1038/s41586-022-05653-6
  11. Pu et al., 2023. Improving the MODIS LAI compositing using prior time-series information. Remote Sens.Env.,doi: 10.1016/j.rse.2023.113493
  12. Dong et al., 2023. A method for retrieving coarse-resolution leaf area index for mixed biomes using a mixed-pixel correction factor. IEEE Trans. Geosci. Remote Sens.,doi: 10.1109/TGRS.2023.3235949
  13. Li et al., 2023.A Novel Inversion Approach for the Kernel-Driven BRDF Model for Heterogeneous Pixels. J. Remote Sens., doi: 10.34133/remotesensing.0038