Vegetation growing season dynamics across land cover classes in central Europe

Abstract Phenological shifts represent one of the most evident biological responses to climate change. This study used the two-band Enhanced Vegetation Index derived from Moderate Resolution Imaging Spectroradiometer satellite data to analyze changes in the growing seasons of arable land, broad-leaved forest, coniferous forest, and grassland across the central European region from 2000 to 2022. Phenological metrics included the start, end, and length of the growing season. Nonparametric Theil–Sen regression indicated an earlier start of the season (median of trends for all land cover classes ranging from -9.3 to -17.5 days per decade), a later end of the season (ranging from +8.1 to +11.4 days per decade), and consequently longer length of the season (ranging from +13.3 to +25.0 days per decade), with advancing start of the season identified as the primary driver of length of the season prolongation. The most pronounced changes across all phenological metrics were associated with arable land. Elevation zone-based analysis showed that the highest median of trends of start and length of the season was found for arable land and coniferous forest in elevations below 600 m a.s.l., with values decreasing progressively with increasing elevation. The analysis of environmental zones revealed a higher median of trends of the start and length of the season in cool-moist and warm-mesic zones, while end-of-season-related changes were more pronounced in cold-wet zones. This study demonstrates coherent long-term trends in vegetation phenology across different land cover classes, with stronger acceleration over arable land, highlighting potential implications for agricultural systems.

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Publication Details

Journal
Regional Environmental Change
Published
2026-10-03
DOI
https://doi.org/10.1007/s10113-026-02697-6
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
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article

Vegetation growing season dynamics across land cover classes in central Europe

Lenka Bartošová, Petra Dížková, Zdeňěk Žalud, Milan Fischer et al.
Regional Environmental Change
Remote Sensing in Agriculture
article

Vegetation growing season dynamics across land cover classes in central Europe

Lenka Bartošová, Petra Dížková, Zdeňěk Žalud, Milan Fischer, Brian D. Wardlow, Michael J. Hayes, Daniela Semerádová, Markéta Poděbradská, Miroslav Trnka, Jan Balek, Lenka Hájková, Monika Hlavsová, Megan Baldissara
article en

Abstract

Abstract Phenological shifts represent one of the most evident biological responses to climate change. This study used the two-band Enhanced Vegetation Index derived from Moderate Resolution Imaging Spectroradiometer satellite data to analyze changes in the growing seasons of arable land, broad-leaved forest, coniferous forest, and grassland across the central European region from 2000 to 2022. Phenological metrics included the start, end, and length of the growing season. Nonparametric Theil–Sen regression indicated an earlier start of the season (median of trends for all land cover classes ranging from -9.3 to -17.5 days per decade), a later end of the season (ranging from +8.1 to +11.4 days per decade), and consequently longer length of the season (ranging from +13.3 to +25.0 days per decade), with advancing start of the season identified as the primary driver of length of the season prolongation. The most pronounced changes across all phenological metrics were associated with arable land. Elevation zone-based analysis showed that the highest median of trends of start and length of the season was found for arable land and coniferous forest in elevations below 600 m a.s.l., with values decreasing progressively with increasing elevation. The analysis of environmental zones revealed a higher median of trends of the start and length of the season in cool-moist and warm-mesic zones, while end-of-season-related changes were more pronounced in cold-wet zones. This study demonstrates coherent long-term trends in vegetation phenology across different land cover classes, with stronger acceleration over arable land, highlighting potential implications for agricultural systems.

Regional Environmental ChangeVol. 26(4)
University of Nebraska–Lincoln (US), Czech Hydrometeorological Institute (CZ), Czech Academy of Sciences, Global Change Research Institute (CZ), Mendel University in Brno (CZ)
Openalex Percentile: Top 11%
Remote Sensing in Agriculture
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