Articles | Volume 18, issue 6
https://doi.org/10.5194/bg-18-1971-2021
https://doi.org/10.5194/bg-18-1971-2021
Research article
 | 
19 Mar 2021
Research article |  | 19 Mar 2021

Improving the monitoring of deciduous broadleaf phenology using the Geostationary Operational Environmental Satellite (GOES) 16 and 17

Kathryn I. Wheeler and Michael C. Dietze

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Cited articles

Ahl, D. E., Gower, S. T., Burrows, S. N., Shabanov, N. V., Myneni, R. B., and Knyazikhin, Y.: Monitoring spring canopy phenology of a deciduous broadleaf forest using MODIS, Remote Sens. Environ., 104, 88–95, https://doi.org/10.1016/j.rse.2006.05.003, 2006. 
Alekseychik, P. K., Korrensalo, A., Mammarella, I., Vesala, T., and Tuittila, E.-S.: Relationship between aerodynamic roughness length and bulk sedge leaf area index in a mixed-species boreal mire complex, Geophys. Res. Lett., 44, 5836–5843, https://doi.org/10.1002/2017GL073884, 2017. 
Cleland, E., Chuine, I., Menzel, A., Mooney, H., and Schwartz, M.: Shifting plant phenology in response to global change, Trends Ecol. Evol., 22, 357–365, https://doi.org/10.1016/j.tree.2007.04.003, 2007. 
Delbart, N., Le Toan, T., Kergoat, L., and Fedotova, V.: Remote sensing of spring phenology in boreal regions: A free of snow-effect method using NOAA-AVHRR and SPOT-VGT data (1982–2004), Remote Sens. Environ., 101, 52–62, https://doi.org/10.1016/j.rse.2005.11.012, 2006. 
Denwood, M. J.: runjags: An R Package Providing Interface Utilities, Model Templates, Parallel Computing Methods and Additional Distributions for MCMC Models in JAGS, J. Stat. Softw., 71, 1–25, https://doi.org/10.18637/jss.v071.i09, 2016. 
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Short summary
Monitoring leaf phenology (i.e., seasonality) allows for tracking the progression of climate change and seasonal variations in a variety of organismal and ecosystem processes. Recent versions of the Geostationary Operational Environmental Satellites allow for the monitoring of a phenological-sensitive index at a high temporal frequency (5–10 min) throughout most of the western hemisphere. Here we show the high potential of these new data to measure the phenology of deciduous forests.
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