Advanced

Classification of grassland successional stages using airborne hyperspectral imagery

Möckel, Thomas LU ; Dalmayne, Jonas LU ; Prentice, Honor C LU ; Eklundh, Lars LU ; Purschke, Oliver; Schmidtlein, Sebastian and Hall, Karin LU (2014) In Remote Sensing 6(8). p.7732-7761
Abstract
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... (More)
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. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
arable-to-grassland succession, Ellenberg indicator values, HySpex spectrometer, imaging spectroscopy, partial least square discriminant analysis
in
Remote Sensing
volume
6
issue
8
pages
7732 - 7761
publisher
MDPI AG
external identifiers
  • wos:000341518700044
  • scopus:84997553768
ISSN
2072-4292
DOI
10.3390/rs6087732
project
BECC
language
English
LU publication?
yes
id
4a3a55ef-f293-4d43-a29d-ddf243c11e9e (old id 4589585)
alternative location
http://www.mdpi.com/2072-4292/6/8/7732
date added to LUP
2014-09-25 11:51:39
date last changed
2017-11-05 04:03:57
@article{4a3a55ef-f293-4d43-a29d-ddf243c11e9e,
  abstract     = {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.},
  author       = {Möckel, Thomas and Dalmayne, Jonas and Prentice, Honor C and Eklundh, Lars and Purschke, Oliver and Schmidtlein, Sebastian and Hall, Karin},
  issn         = {2072-4292},
  keyword      = {arable-to-grassland succession,Ellenberg indicator values,HySpex spectrometer,imaging spectroscopy,partial least square discriminant analysis},
  language     = {eng},
  number       = {8},
  pages        = {7732--7761},
  publisher    = {MDPI AG},
  series       = {Remote Sensing},
  title        = {Classification of grassland successional stages using airborne hyperspectral imagery},
  url          = {http://dx.doi.org/10.3390/rs6087732},
  volume       = {6},
  year         = {2014},
}