Satellite-Derived Phenology Intercomparison and Validation References
Tian et al., 2021. Calibrating vegetation phenology from Sentinel-2 using eddy covariance, PhenoCam, and PEP725 networks across Europe. RSE, 260, 112456
Moon et al., 2021. Multiscale assessment of land surface phenology from harmonized Landsat 8 and Sentinel-2, PlanetScope, and PhenoCam imagery. RSE, 266, 112716
Peng, D., Zhang, X., Wu, C., Huang, W., Gonsamo, A., Huete, A. R., ... & Zhang, B. (2017). Intercomparison and evaluation of spring phenology products using National Phenology Network and AmeriFlux observations in the contiguous United States. Agricultural and Forest Meteorology, 242, 33-46.
Melaas, E. K., Sulla-Menashe, D., Gray, J. M., Black, T. A., Morin, T. H., Richardson, A. D., & Friedl, M. A. (2016). Multisite analysis of land surface phenology in North American temperate and boreal deciduous forests from Landsat. Remote Sensing of Environment, 186, 452-464.
Rodriguez-Galiano, V.F., Dash, J., & Atkinson, P.M. (2015). Intercomparison of satellite sensor land surface phenology and ground phenology in Europe. Geophysical Research Letters, 42, 2253-2260
Klosterman, S., Hufkens, K., Gray, J., Melaas, E., Sonnentag, O., Lavine, I., Mitchell, L., Norman, R., Friedl, M., and Richardson, A. (2014). Evaluating remote sensing of deciduous forest phenology at multiple spatial scales using PhenoCam imagery. Biogeosciences Discussions, 11, 2305-2342
Coops, N.C., Hilker, T., Bater, C.W., Wulder, M.A., Nielsen, S.E., McDermid, G., & Stenhouse, G. (2012). Linking ground-based to satellite-derived phenological metrics in support of habitat assessment. Remote Sensing Letters, 3, 191-200
Atkinson, P.M., Jeganathan, C., Dash, J., & Atzberger, C. (2012). Inter-comparison of four models for smoothing satellite sensor time-series data to estimate vegetation phenology. Remote Sensing of Environment, 123, 400-417
Hufkens, K., Friedl, M., Sonnentag, O., Braswell, B.H., Milliman, T., & Richardson, A.D. (2012). Linking near-surface and satellite remote sensing measurements of deciduous broadleaf forest phenology. Remote Sensing of Environment, 117, 307-321
Liang, L., Schwartz, M.D., & Fei, S. (2011). Validating satellite phenology through intensive ground observation and landscape scaling in a mixed seasonal forest. Remote Sensing of Environment, 115, 143-157
Garrity, S.R., Bohrer, G., Maurer, K.D., Mueller, K.L., Vogel, C.S., & Curtis, P.S. (2011). A comparison of multiple phenology data sources for estimating seasonal transitions in deciduous forest carbon exchange. Agricultural and Forest Meteorology, 151, 1741-1752
White, M.A., Beurs, D., Kirsten, M., Didan, K., Inouye, D.W., Richardson, A.D., Jensen, O.P., O'Keefe, J., Zhang, G., and Nemani, R.R. (2009). Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982–2006. Global Change Biology, 15, 2335-2359
Morisette, J.T., Richardson, A.D., Knapp, A.K., Fisher, J.I., Graham, E.A., Abatzoglou, J., Wilson, B.E., Breshears, D.D., Henebry, G.M., & Hanes, J.M. (2008). Tracking the rhythm of the seasons in the face of global change: phenological research in the 21st century. Frontiers in Ecology and the Environment, 7, 253-260
Studer, S., Stöckli, R., Appenzeller, C., & Vidale, P. (2007). A comparative study of satellite and ground-based phenology. International Journal of Biometeorology, 51, 405-414
