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Classification of grassland successional stages using airborne hyperspectral imagery

  • Thomas Möckel
  • Jonas Dalmayne
  • Honor C Prentice
  • Lars Eklundh
  • Oliver Purschke
  • Sebastian Schmidtlein
  • Karin Hall
Publishing year: 2014
Language: English
Pages: 7732-7761
Publication/Series: Remote Sensing
Volume: 6
Issue: 8
Document type: Journal article
Publisher: MDPI AG

Abstract english

Plant communities differ in their species composition, and, thus, also in their functional trait composition, at different stages in the succession from arable fields to grazed grassland. We examine whether aerial hyperspectral (414–2501 nm) remote sensing can be used to discriminate between grazed vegetation belonging to different grassland successional stages. Vascular plant species were recorded in 104.1 m2 plots on the island of Öland (Sweden) and the functional properties of the plant species recorded in the plots were characterized in terms of the ground-cover of grasses, specific leaf area and Ellenberg indicator values. Plots were assigned to three different grassland age-classes, representing 5–15, 16–50 and >50 years of grazing management. Partial least squares discriminant analysis models were used to compare classifications based on aerial hyperspectral data with the age-class classification. The remote sensing data successfully classified the plots into age-classes: the overall classification accuracy was higher for a model based on a pre-selected set of wavebands (85%, Kappa statistic value = 0.77) than one using the full set of wavebands (77%, Kappa statistic value = 0.65). Our results show that nutrient availability and grass cover differences between grassland age-classes are detectable by spectral imaging. These techniques may potentially be used for mapping the spatial distribution of grassland habitats at different successional stages.


  • Biological Sciences
  • Physical Geography
  • arable-to-grassland succession
  • Ellenberg indicator values
  • HySpex spectrometer
  • imaging spectroscopy
  • partial least square discriminant analysis


  • ISSN: 2072-4292
E-mail: lars [dot] eklundh [at] nateko [dot] lu [dot] se


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Dept of Physical Geography and Ecosystem Science


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