Publications 2013

  1. Xu et al., 2013 Temperature and vegetation seasonality diminishment over northern lands. Nature Climate Change, doi: 10.1038/NCLIMATE1836
    Supplementary Information
    Prof. Snyder’s Commentary
  2. Peng et al., 2013 Asymmetric effects of daytime and night-time warming on Northern Hemisphere vegetation, Nature, 2013, doi:10.1038/nature12434
    Prof. Still’s “News and Views” item
  3. Knyazikhin et al., 2013 Reply to Ollinger et al.: Remote Sensing of Leaf Nitrogen and Emergent Ecosystem Properties, Proc. Natl. Acad. Sci. USA (www.pnas.org/cgi/doi/10.1073/pnas.1305930110)
  4. Knyazikhin et al., 2013 Reply to Townsend et al.: Decoupling contributions from canopy structure and leaf optics is critical for remote sensing leaf biochemistry. Proc. Natl. Acad. Sci. USA (www.pnas.org/cgi/doi/10.1073/pnas.1301247110)
  5. Fu et al., 2013 Increased dry-season length over southern Amazonia in recent decades and its implication for future climate projection, Proc. Natl. Acad. Sci. USA, doi: 10.1073/pnas.1302584110
  6. Wang et al., 2013 Variations in atmospheric CO2 growth rates coupled with tropical temperature, Proc. Natl. Acad. Sci. USA, doi: 10.1073/pnas.1219683110
  7. Ciais et al., 2013. Carbon and Other Biogeochemical Cycles, IPCC AR5 Chapter 6, 2013.
  8. Ichii et al., 2013 Recent changes in terrestrial gross primary productivity in Asia from 1982 to 2011, Remote Sens., doi: 10.3390/rs5116043
  9. Xin et al., 2013 A production efficiency model-based method for satellite estimates of corn and soybean yields in the midwestern US, Remote Sens., doi: 10.3390/rs5115926
  10. Tan et al., 2013 Using hyperspectral vegetation indices to estimate the fraction of photosynthetically active radiation absorbed by corn canopies, International J. Remote Sens. doi: 10.1080/01431161.2013.853143, 2013
  11. Yan et al., 2013 Diagnostic analysis of interannual variation of global land evapotranspiration over 1982–2011: Assessing the impact of ENSO, J. Geophys. Res., doi: 10.1002/jgrd.50693, 2013
  12. Barichivich et al., 2013 Large-scale variations in the vegetation growing season and annual cycle of atmospheric CO2 at high northern latitudes from 1950 to 2011, Global Change Biol., 2013, doi: 10.1111/gcb.12283
  13. Wang et al., 2013 Evaluation of CLM4 Solar Radiation Partitioning Scheme Using Remote Sensing and Site Level FPAR Datasets, Remote Sens. 2013, 5, 2857-2882; doi:10.3390/rs5062857
  14. Bi et al., 2013 Divergent Arctic-Boreal Vegetation Changes Between North America and Eurasia Over the Past 30 Years, Remote Sens., doi:10.3390/rs5052093
  15. Piao et al., 2013 Evaluation of Terrestrial Carbon Cycle Models for their Response to Climate Variability and to CO2 Trends, Global Change Biology, doi: 10.1111/gcb.12187
  16. Anav et al., 2013 Evaluating the Land and Ocean Components of the Global Carbon Cycle in the CMIP5 Earth System Models, J. Climate, doi:10.1175/JCLI-D-12-00417.1
  17. Fang et al., 2013 Characterization and Intercomparison of Global Moderate Resolution Leaf Area Index (LAI) Products: Analysis of Climatologies and Theoretical Uncertainties, J. Geophys. Res.Biogeosci., doi:10.1002/jgrg.20051
  18. Mohammat et al., 2013 Drought and Spring Cooling Induced Recent Decrease in Vegetation Growth in Inner Asia, Agric. For. Meteorol., http://dx.doi.org/10.1016/j.agrformet.2012.09.014
  19. Poulter et al., 2013 Recent Trends in Inner Asian Forest Dynamics to Temperature and Precipitation Indicate High Sensitivity to Climate Change, Agric. For. Meteorol., http://dx.doi.org/10.1016/j.agrformet.2012.12.006
  20. Mao et al., 2013 Global Latitudinal-Asymmetric Vegetation Growth Trends and Their Driving Mechanisms: 1982-2009, Remote Sens. 2013, 5, 1484-1497; doi:10.3390/rs5031484
  21. Zhu et al., 2013 Global Data Sets of Vegetation Leaf Area Index (LAI)3g and Fraction of Photosynthetically Active Radiation (FPAR)3g Derived from Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) for the Period 1981 to 2011, Remote Sens. 2013, 5, 927-948; doi:10.3390/rs5020927
    Supplementary Information
  22. Luo et al., 2013 Assessing Performance of NDVI and NDVI3g in Monitoring Leaf Unfolding Dates of the Deciduous Broadleaf Forest in Northern China, Remote Sens. 2013, 5, 845-861; doi:10.3390/rs5020845
  23. Fang et al., 2013 The Impact of Potential Land Cover Misclassification on MODIS Leaf Area Index (LAI) Estimation: A Statistical Perspective, Remote Sens. 2013, 5, 830-844; doi:10.3390/rs5020830
  24. Shi & Choi et al., 2013 Allometric Scaling and Resource Limitations Model of Tree Heights: Part 1. Model Optimization and Testing over Continental USA, Remote Sens. 2013, 5, 284-306; doi:10.3390/rs5010284
  25. Choi & Ni et al., 2013 Allometric Scaling and Resource Limitations Model of Tree Heights: Part 2. Site Based Testing of the Model, Remote Sens. 2013, 5, 202-223; doi:1