Recent Publications

The list below provides links to electronic versions of recent papers published by group members and collaborators. Clicking on any of the links will take you to webpages where each publication can be downloaded from the publisher.

2021

  • Moon, M, Richardson, A.D., and M.A. Friedl (2021). Multiscale assessment of land surface phenology from harmonized Landsat 8 and Sentinel-2, PlanetScope, and PhenoCam imagery , Remote Sensing of Environment, 266 (2021) 112716, https://doi.org/10.1016/j.rse.2021.112716.
  • Young, A.M., Friedl, M.A., Seyednasrollah, B., Beamesderfer, E., Carrillo, C.M., Li, X., Moon, M.,  Arain, M.A., Baldocchi, D.D., Blanken, P.D., Bohrer, G., Burns, S.P., Chu, H., Desai, A.R., Griffis, T.J., Hollinger, D.Y., Litvak, M.E., Novick, K., Scott, R.L., Suyker, A.E., Verfaillie, J., Wood, J.D. and A.D. Richardson (2021), Seasonality in aerodynamic resistance across a range of North American ecosystems, Agricultural and Forest Meteorology, Volume 310, https://doi.org/10.1016/j.agrformet.2021.108613.
  • Wang, J.A., Baccini, A., Farina, M. R.,Randerson, J.T. and M.a. Friedl (2021). Disturbance suppresses the aboveground carbon sink in North American boreal forests. Nat. Clim. Chang. https://doi.org/10.1038/s41558-021-01027-4.
  • Moon, M., Seyednasrollah, B., Richardson, A.D. and M.A. Friedl (2021). Using time series of MODIS land surface phenology to model temperature and photoperiod controls on spring greenup in North American deciduous forests, Remote Sensing of Environment, 260 (2021), https://doi.org/10.1016/j.rse.2021.112466
  • Hu, Q., Yin, H., Friedl, M.A., You, L., Li, Z., Tang, H. and W. Wu (2021). Integrating coarse-resolution images and agricultural statistics to generate sub-pixel crop type maps and reconciled area estimates. Remote Sensing of Environment, https://doi.org/10.1016/j.rse.2021.112365.

2020

  • Elmes, A., Alemohammad, H., Avery, R., Caylor, K., Eastman, R.J., Fishgold, L., Friedl, M.A., Jain, M., Kohli, D., Bayas, J.C.L., Lunga, D., McCarty, J.L., Pontius, R.G., Reinman, A.B., Rogan, J., Song, L., Stoynova, H., Ye, S., Yi, Z.F. and L. Estes (2020), Accounting for training data errors in machine learning applied to Earth observations, Remote Sensing, 12(6), 1034: https://doi.org/10.3390/rs12061034
  • Seyednasrollah, B., Young, A.M., Li, X., Milliman, T., Ault, T., Frolking, S., Friedl, M., and A.D. Richardson, Sensitivity of deciduous forest phenology to environmental drivers for climate change impacts across North America, Geophysical Research Letters, 47, e2019GL086788. https://doi.org/10.1029/2019GL086788.
  • Bolton, D, K., Gray, J.M, Melaas, E.K., Moon, M., Eklundh, L. and M.A. Friedl (2020). Continental-scale land surface phenology from harmonized Landsat 8 and Sentinel-2 imagery, Remote Sensing of Environment, 240, https://doi.org/10.1016/j.rse.2020.111685.
  • Moon, M., Li, D., Liao, W., Rigden, A.J. andA. Friedl (2020). Modification of Surface Energy Balance During Springtime: The Relative Importance of Biophysical and Meteorological Changes, Agricultural and Forest Meteorology, 284, https://doi.org/10.1016/j.agrformet.2020.107905

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Other significant papers: