Combining satellite data and agricultural statistics to map grassland management intensity in Europe

Stephan Estel*, Sebastian Mader, Christian Levers, Peter H. Verburg, Matthias Baumann, Tobias Kuemmerle

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

The world's grasslands, both natural and managed, provide food and many non-provisioning ecosystem services. Although most grasslands today are used for livestock grazing or fodder production, little is known about the spatial patterns of grassland management intensity, especially at broad geographic scales. Using the European Union as a case study, we mapped mowing frequency as a key indicator of grassland management intensity. We used MODIS NDVI time series from 2000-2012 to map mowing frequency using a spline-fitting algorithm that detects up to five mowing events within a single growing season. We combined mowing frequency maps with existing maps of livestock distribution and grassland management frequency to identify clusters of similar grassland management intensity across Europe. Our results highlight generally high mowing frequency in areas of high grassland productivity, especially in Ireland, Northern and central France, and the Netherlands. Our analyses also show distinct clusters of similar grassland management, representing different grassland-management intensity regimes. High intensity clusters occurred particularly in western and southern Europe, especially in Ireland, in the northern and central parts of France and Spain, and the Netherlands but also in northern and southern Germany and eastern Poland. Low intensity clusters were found mainly in central and eastern Europe and in mountainous regions but also in Extremadura in Spain, Wales and western England (UK). Generally, our analyses emphasize the usefulness of jointly using satellite time series and agricultural statistics to monitor grassland intensity across broad geographic extents. Our maps allow for a new, spatially-detailed view of management intensity in grassland systems and may help to improve regionally targeted land-use and conservation policies.

Original languageEnglish
Article number074020
Pages (from-to)1-11
Number of pages11
JournalEnvironmental Research Letters
Volume13
Issue number7
DOIs
Publication statusPublished - 5 Jul 2018

Keywords

  • Livestock distribution
  • MODIS NDVI time series
  • Mowing frequency
  • Self-organizing maps

Fingerprint

Dive into the research topics of 'Combining satellite data and agricultural statistics to map grassland management intensity in Europe'. Together they form a unique fingerprint.

Cite this