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Open AccessArticle

An Empirical Assessment of the MODIS Land Cover Dynamics and TIMESAT Land Surface Phenology Algorithms

1
Department of Earth and Environment, Boston University, 675 Commonwealth Avenue, Boston, MA 02215, USA
2
Department of Physical Geography and Ecosystems Analysis, Lund University, 221 00 Lund, Sweden
3
Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC 27695, USA
4
Center for Geospatial Analytics, North Carolina State University, Raleigh, NC 27695, USA
5
Department of Materials Science and Applied Mathematics, Malmö University, 205 06 Malmö, Sweden
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(19), 2201; https://doi.org/10.3390/rs11192201
Received: 11 July 2019 / Revised: 14 September 2019 / Accepted: 18 September 2019 / Published: 20 September 2019
(This article belongs to the Special Issue Land Surface Phenology )
Observations of vegetation phenology at regional-to-global scales provide important information regarding seasonal variation in the fluxes of energy, carbon, and water between the biosphere and the atmosphere. Numerous algorithms have been developed to estimate phenological transition dates using time series of remotely sensed spectral vegetation indices. A key challenge, however, is that different algorithms provide inconsistent results. This study provides a comprehensive comparison of start of season (SOS) and end of season (EOS) phenological transition dates estimated from 500 m MODIS data based on two widely used sources of such data: the TIMESAT program and the MODIS Global Land Cover Dynamics (MLCD) product. Specifically, we evaluate the impact of land cover class, criteria used to identify SOS and EOS, and fitting algorithm (local versus global) on the transition dates estimated from time series of MODIS enhanced vegetation index (EVI). Satellite-derived transition dates from each source are compared against each other and against SOS and EOS dates estimated from PhenoCams distributed across the Northeastern United States and Canada. Our results show that TIMESAT and MLCD SOS transition dates are generally highly correlated (r = 0.51-0.97), except in Central Canada where correlation coefficients are as low as 0.25. Relative to SOS, EOS comparison shows lower agreement and higher magnitude of deviations. SOS and EOS dates are impacted by noise arising from snow and cloud contamination, and there is low agreement among results from TIMESAT, the MLCD product, and PhenoCams in vegetation types with low seasonal EVI amplitude or with irregular EVI time series. In deciduous forests, SOS dates from the MLCD product and TIMESAT agree closely with SOS dates from PhenoCams, with correlations as high as 0.76. Overall, our results suggest that TIMESAT is well-suited for local-to-regional scale studies because of its ability to tune algorithm parameters, which makes it more flexible than the MLCD product. At large spatial scales, where local tuning is not feasible, the MLCD product provides a readily available data set based on a globally consistent approach that provides SOS and EOS dates that are comparable to results from TIMESAT. View Full-Text
Keywords: Enhanced vegetation index (EVI); land surface phenology; MODIS; phenology product; smoothing methods; TIMESAT Enhanced vegetation index (EVI); land surface phenology; MODIS; phenology product; smoothing methods; TIMESAT
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MDPI and ACS Style

Stanimirova, R.; Cai, Z.; Melaas, E.K.; Gray, J.M.; Eklundh, L.; Jönsson, P.; Friedl, M.A. An Empirical Assessment of the MODIS Land Cover Dynamics and TIMESAT Land Surface Phenology Algorithms. Remote Sens. 2019, 11, 2201. https://doi.org/10.3390/rs11192201

AMA Style

Stanimirova R, Cai Z, Melaas EK, Gray JM, Eklundh L, Jönsson P, Friedl MA. An Empirical Assessment of the MODIS Land Cover Dynamics and TIMESAT Land Surface Phenology Algorithms. Remote Sensing. 2019; 11(19):2201. https://doi.org/10.3390/rs11192201

Chicago/Turabian Style

Stanimirova, Radost; Cai, Zhanzhang; Melaas, Eli K.; Gray, Josh M.; Eklundh, Lars; Jönsson, Per; Friedl, Mark A. 2019. "An Empirical Assessment of the MODIS Land Cover Dynamics and TIMESAT Land Surface Phenology Algorithms" Remote Sens. 11, no. 19: 2201. https://doi.org/10.3390/rs11192201

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