Remotely sensed trends in the phenology of northern high latitude terrestrial vegetation, controlling for land cover change and vegetation type

- Terrestrial vegetation phenology above 45°N was analysed using remote sensing data.
- Trends in vegetation phenology were analysed, controlling for land cover changes.
- Latitudes 55°N to 65°N experienced the greatest changes in vegetation phenology.
- Needle leaf deciduous vegetation had the maximum decrease in SOS (− 1.07 days yr− 1).
- Broad leaf deciduous vegetation had the maximum delay in EOS (+ 1.06 days yr− 1).

Trends in the start or end of growing season (SOS, EOS) of terrestrial vegetation reported previously as latitudinal averages limit the ability to investigate the effects of land cover change and species-wise conditioning on the presented vegetation phenology information. The current research provided more reliable estimates of the trends in the annual growth pattern of terrestrial vegetation occurring at latitudes greater than 45°N. 25 years of satellite-derived Normalised Difference Vegetation Index (GIMMS NDVI) was used and reliable vegetated pixels were analysed to derive the SOS and EOS. The rate of change in SOS and EOS over 25 years was estimated, aggregated and scrutinised at different measurement levels: a) vegetation type, b) percentage vegetative cover, c) core area, d) percentage forest cover loss, and e) latitude zones. The research presents renewed and detailed estimates of the trends in these phenology parameters in these strata. In the > 45°N zone, when only reliable pixels were considered, there was an advancement of − 0.58 days yr− 1 in SOS and a delay of + 0.64 days yr− 1 in EOS. For homogeneous vegetated areas (91-100% cover at 8 km spatial resolution) the 55-65°N zone showed the maximum change with − 1.07 days yr− 1 advancement in SOS for needle leaved deciduous vegetation, and − 1.06 days yr− 1 delay in EOS for broad leaved deciduous vegetation. Overall, the increasing trend in EOS during senescence (September to November) was greater in magnitude than the decreasing trend in SOS during spring (March to May) and the change in EOS was more consistent and greater than that in SOS.