Publications

  • Arévalo, P., Bullock, E. L., Woodcock, C. E., & Olofsson, P. (2020). A Suite of Tools for Continuous Land Change Monitoring in Google Earth Engine. Frontiers in Climate, 2, 576740. https://doi.org/10.3389/fclim.2020.576740
  • 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
  • Friedl M.A., Woodcock C.E., Olofsson P., Zhu Z., Loveland T., Stanimirova R., Arevalo P., Bullock E., Hu K.T., Zhang Y., Turlej K., Tarrio K., McAvoy K., Gorelick N., Wang J.A., Barber C.P., and C. Souza (2022). Medium Spatial Resolution Mapping of Global Land Cover and Land Cover Change Across Multiple Decades From Landsat, Frontiers in Remote Sensing, 3, https://doi.org/10.3389/frsen.2022.894571
  • Graesser, J., R. Stanimirova, K. Tarrio, E.J. Copati, J.N. Volante, S.R. Verón, S. Banchero, H. Elena, D. de Abelleyra and Mark A. Friedl (2022). Temporally-Consistent Annual Land Cover from Landsat Time Series in the Southern Cone of South America, Remote Sensing 14, no. 16: 4005. https://doi.org/10.3390/rs14164005
  • Graesser, J., Stanimirova, R. and M. A. Friedl (2022) “Reconstruction of satellite time series with a dynamic smoother,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 1803-1813, http://doi.org/10.1109/JSTARS.2022.3146081
  • Stanimirova, R., Graesser, J., Olofsson, P., & Friedl, M. A. (2022). Widespread changes in 21st century vegetation cover in Argentina, Paraguay, and Uruguay. Remote Sensing of Environment, 282, 113277. https://doi.org/10.1016/j.rse.2022.113277
  • 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
  • Wang, J.A. and M.A. Friedl (2019). The role of land cover change in Arctic-Boreal greening and browning trends. Environmental Research Letters, 14 125007, https://doi.org/10.1088/1748-9326/ab5429
  • Wang, J.A., Sulla-Menashe, D., Woodcock, C.E., Sonnentag, O., Keeling, R.F. and M.A. Friedl (2019). Extensive land cover change across Arctic–Boreal Northwestern North America from disturbance and climate forcing, Global Change Biology; https://doi.org/10.1111/gcb.14804
  • Zhang, Y., Woodcock, C. E., Arévalo, P., Olofsson, P., Tang, X., Stanimirova, R., Bullock, E., Tarrio, K. R., Zhu, Z., & Friedl, M. A. (2022). A Global Analysis of the Spatial and Temporal Variability of Usable Landsat Observations at the Pixel Scale. Frontiers in Remote Sensing, 3, https://doi.org/10.3389/frsen.2022.894618
  • Zhang, Y., Woodcock, C.E., Chen.S., Wang, J.A., Sulla-Menashe, D., Zuo, Z., Olofsson, P. Wang, Y and M.A. Friedl (2022). Mapping causal agents of disturbance in boreal and Arctic ecosystems of North America using time series of Landsat data, Remote Sensing of Environment, 272, https://doi.org/10.1016/j.rse.2022.112935