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Hyperspectral and multispectral remote sensing for mapping grassland vegetation

Möckel, Thomas LU (2015)
Abstract (Swedish)
Popular Abstract in English

European dry extensive grasslands are biodiversity hotspots which are severely

threatened by land use intensification and abandonment. In order to plan efficient

conservation actions it is necessary to collect information on the current status of

grasslands, their species diversity and prevailing environmental conditions. Remote

sensing technology in combination with ground surveys provides an effective tool to

monitor ecosystem properties continuously across the landscape with high spatial

precision in a repeatable way. In this thesis, the potential of hyper-and multispectral

remote sensing imagery to predict grassland ecological... (More)
Popular Abstract in English

European dry extensive grasslands are biodiversity hotspots which are severely

threatened by land use intensification and abandonment. In order to plan efficient

conservation actions it is necessary to collect information on the current status of

grasslands, their species diversity and prevailing environmental conditions. Remote

sensing technology in combination with ground surveys provides an effective tool to

monitor ecosystem properties continuously across the landscape with high spatial

precision in a repeatable way. In this thesis, the potential of hyper-and multispectral

remote sensing imagery to predict grassland ecological parameters, such as grazing

continuity, plant species diversity and habitat environmental conditions was evaluated

studying grassland sites on the Baltic island of Öland, Sweden. Different methods

were compared on the basis of their prediction quality and practical feasibility. The

findings of this thesis provide a useful guidance for the selection of prediction

methods of ecological grassland parameter in future studies. Combined with ground

surveys, remote sensing can serve as time-efficient decision support tool for

prioritising areas of high conservation value for management actions. (Less)
Abstract
As a consequence of agricultural intensification, large areas of species-rich grasslands

have been lost and farmland biodiversity has declined. Previous studies have shown

that the continuity of grazing management can have a significant influence on the

environmental conditions and the levels of plant species diversity in grassland

habitats. The preservation of species-rich grasslands has become a high conservation

priority within the European Union and the mapping of grazed grassland vegetation

across wide areas has been identified as a central task for biodiversity conservation in

agricultural landscapes. The fact that detailed field inventories of plant communities

... (More)
As a consequence of agricultural intensification, large areas of species-rich grasslands

have been lost and farmland biodiversity has declined. Previous studies have shown

that the continuity of grazing management can have a significant influence on the

environmental conditions and the levels of plant species diversity in grassland

habitats. The preservation of species-rich grasslands has become a high conservation

priority within the European Union and the mapping of grazed grassland vegetation

across wide areas has been identified as a central task for biodiversity conservation in

agricultural landscapes. The fact that detailed field inventories of plant communities

are time-consuming may limit the spatial extent of grassland habitat surveys. If

remote sensing data are able to identify grassland sites characterised by different

environmental conditions and plant species diversity, then field sampling efforts could

be directed towards sites that are of potential conservation interest.

In the thesis, I have examined the potential of hyperspectral and multispectral remote

sensing imagery to map grassland vegetation at detailed scales in dry grazed grassland

habitats. Fieldwork included the recording of vascular plant species and

environmental variables in grasslands plots representing three age-classes within an

arable-to-grassland succession in an agricultural landscape on the Baltic island of

Öland (Sweden). Remotely sensed data were acquired with the help of two airborne

HySpex hyperspectral spectrometers (415–2501 nm) and by the multispectral

WorldView-2 satellite.

The results of the thesis show that the soil nutrient and moisture status within

grassland plots influenced the hyperspectral reflectance. Hyperspectral data had the

ability to classify grassland plots into different age-classes. Hyperspectral reflectance

measurements could be used to predict plant indicator values for nutrient and soil

moisture in grassland plots. Prediction models developed from hyperspectral data

were successfully used to assess levels of plant species diversity (species richness and

Simpsons’s diversity). In addition, between-plot dissimilarities in the satellite spectral

reflectance were shown to be related to between-plot dissimilarities in the species

composition in old grassland sites.

The findings of the thesis demonstrate that remote sensing data are capable of

capturing detailed-scale information that discriminates between grassland plant

communities representing different environmental conditions and levels of plant

species diversity. The results suggest that remote sensing data may have the ability for

use as a decision-support tool to help conservation planners identify grassland habitats

in agricultural landscapes that are of high conservation interest. (Less)
Please use this url to cite or link to this publication:
author
supervisor
opponent
  • Dr. Rocchini, Duccio, Fondazione Edmund Mach, Italy
organization
publishing date
type
Thesis
publication status
published
subject
keywords
Plant diversity Partial least squares Ellenberg indicators Vegetation index Heterogeneity
pages
169 pages
publisher
Department of Physical Geography and Ecosystem Science, Lund University
defense location
Pangea
defense date
2015-05-19 10:00
ISBN
978-91-85793-46-4
language
English
LU publication?
yes
id
3942a88a-f50e-4be8-98cc-b503eac866bb (old id 5277106)
date added to LUP
2015-05-05 11:37:45
date last changed
2016-09-19 08:45:10
@phdthesis{3942a88a-f50e-4be8-98cc-b503eac866bb,
  abstract     = {As a consequence of agricultural intensification, large areas of species-rich grasslands<br/><br>
have been lost and farmland biodiversity has declined. Previous studies have shown<br/><br>
that the continuity of grazing management can have a significant influence on the<br/><br>
environmental conditions and the levels of plant species diversity in grassland<br/><br>
habitats. The preservation of species-rich grasslands has become a high conservation<br/><br>
priority within the European Union and the mapping of grazed grassland vegetation<br/><br>
across wide areas has been identified as a central task for biodiversity conservation in<br/><br>
agricultural landscapes. The fact that detailed field inventories of plant communities<br/><br>
are time-consuming may limit the spatial extent of grassland habitat surveys. If<br/><br>
remote sensing data are able to identify grassland sites characterised by different<br/><br>
environmental conditions and plant species diversity, then field sampling efforts could<br/><br>
be directed towards sites that are of potential conservation interest.<br/><br>
In the thesis, I have examined the potential of hyperspectral and multispectral remote<br/><br>
sensing imagery to map grassland vegetation at detailed scales in dry grazed grassland<br/><br>
habitats. Fieldwork included the recording of vascular plant species and<br/><br>
environmental variables in grasslands plots representing three age-classes within an<br/><br>
arable-to-grassland succession in an agricultural landscape on the Baltic island of<br/><br>
Öland (Sweden). Remotely sensed data were acquired with the help of two airborne<br/><br>
HySpex hyperspectral spectrometers (415–2501 nm) and by the multispectral<br/><br>
WorldView-2 satellite.<br/><br>
The results of the thesis show that the soil nutrient and moisture status within<br/><br>
grassland plots influenced the hyperspectral reflectance. Hyperspectral data had the<br/><br>
ability to classify grassland plots into different age-classes. Hyperspectral reflectance<br/><br>
measurements could be used to predict plant indicator values for nutrient and soil<br/><br>
moisture in grassland plots. Prediction models developed from hyperspectral data<br/><br>
were successfully used to assess levels of plant species diversity (species richness and<br/><br>
Simpsons’s diversity). In addition, between-plot dissimilarities in the satellite spectral<br/><br>
reflectance were shown to be related to between-plot dissimilarities in the species<br/><br>
composition in old grassland sites.<br/><br>
The findings of the thesis demonstrate that remote sensing data are capable of<br/><br>
capturing detailed-scale information that discriminates between grassland plant<br/><br>
communities representing different environmental conditions and levels of plant<br/><br>
species diversity. The results suggest that remote sensing data may have the ability for<br/><br>
use as a decision-support tool to help conservation planners identify grassland habitats<br/><br>
in agricultural landscapes that are of high conservation interest.},
  author       = {Möckel, Thomas},
  isbn         = {978-91-85793-46-4},
  keyword      = {Plant diversity Partial least squares Ellenberg indicators Vegetation index Heterogeneity},
  language     = {eng},
  pages        = {169},
  publisher    = {Department of Physical Geography and Ecosystem Science, Lund University},
  school       = {Lund University},
  title        = {Hyperspectral and multispectral remote sensing for mapping grassland vegetation},
  year         = {2015},
}