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Northern peatland vegetation and the carbon cycle: a remote sensing approach

Northern peatland vegetation and the carbon cycle: a remote sensing approach
Northern peatland vegetation and the carbon cycle: a remote sensing approach
Rates of carbon exchange in northern peatlands are dependent on the composition, structure and spatial arrangement of vegetation. Whilst in situ observations can provide detailed information for a given location, remote sensing is the only viable means of collecting land-surface data in a spatially continuous manner across a range of spatial scales. In this paper we review and evaluate many existing and emerging remote sensing approaches used to retrieve peatland land-surface data of relevance to the carbon cycle. We review studies documented in the scientific literature that use remotely sensed data to (i) generate vegetation maps, which may be used to extrapolate field observations, calibrate and extrapolate carbon models and inform peatland management efforts; and (ii) retrieve vegetation biophysical properties, which can be used to parameterize process-based models (e.g. leaf area index (LAI)). There has been considerable progress in the development and implementation of remote sensing approaches that provide data relating to peatland carbon processes. However, there remain a number of methodological challenges, which limit the effectiveness of remote sensing data in some instances. Consequently, we propose that future research approaches focus on (i) continued development, testing and validation of approaches to overcome difficulties caused by the heterogeneous nature of peatland vegetation surfaces (e.g. mixture modeling); (ii) assessment of spatial errors and uncertainty in image classifications, (iii) synergistic use of multiple datasets, (iii) development of scaling algorithms and (iv) continued development of radiative transfer models that can be applied to heterogeneous peatland plant assemblages.
northern peatlands remote sensing carbon cycle
9780875904498
0065-8448
184
79-98
American Geophysical Union
Harris, A.
13bbc5ce-730a-4918-b751-296ea3d60bb3
Bryant, R.G.
cd620b21-94bb-4347-a6b4-53eb861d8b17
Baird, Andrew J.
Belyea, Lisa R.
Comas, Xavier
Reeve, A.S.
Slater, Lee D.
Harris, A.
13bbc5ce-730a-4918-b751-296ea3d60bb3
Bryant, R.G.
cd620b21-94bb-4347-a6b4-53eb861d8b17
Baird, Andrew J.
Belyea, Lisa R.
Comas, Xavier
Reeve, A.S.
Slater, Lee D.

Harris, A. and Bryant, R.G. (2009) Northern peatland vegetation and the carbon cycle: a remote sensing approach. In, Baird, Andrew J., Belyea, Lisa R., Comas, Xavier, Reeve, A.S. and Slater, Lee D. (eds.) Carbon Cycling in Northern Peatlands. (Geophysical Monograph Series, 184) Washington DC, USA. American Geophysical Union, pp. 79-98.

Record type: Book Section

Abstract

Rates of carbon exchange in northern peatlands are dependent on the composition, structure and spatial arrangement of vegetation. Whilst in situ observations can provide detailed information for a given location, remote sensing is the only viable means of collecting land-surface data in a spatially continuous manner across a range of spatial scales. In this paper we review and evaluate many existing and emerging remote sensing approaches used to retrieve peatland land-surface data of relevance to the carbon cycle. We review studies documented in the scientific literature that use remotely sensed data to (i) generate vegetation maps, which may be used to extrapolate field observations, calibrate and extrapolate carbon models and inform peatland management efforts; and (ii) retrieve vegetation biophysical properties, which can be used to parameterize process-based models (e.g. leaf area index (LAI)). There has been considerable progress in the development and implementation of remote sensing approaches that provide data relating to peatland carbon processes. However, there remain a number of methodological challenges, which limit the effectiveness of remote sensing data in some instances. Consequently, we propose that future research approaches focus on (i) continued development, testing and validation of approaches to overcome difficulties caused by the heterogeneous nature of peatland vegetation surfaces (e.g. mixture modeling); (ii) assessment of spatial errors and uncertainty in image classifications, (iii) synergistic use of multiple datasets, (iii) development of scaling algorithms and (iv) continued development of radiative transfer models that can be applied to heterogeneous peatland plant assemblages.

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More information

Published date: November 2009
Keywords: northern peatlands remote sensing carbon cycle

Identifiers

Local EPrints ID: 69547
URI: https://eprints.soton.ac.uk/id/eprint/69547
ISBN: 9780875904498
ISSN: 0065-8448
PURE UUID: a8966fd0-a726-4006-b7b5-205c7ca19cb6

Catalogue record

Date deposited: 13 Nov 2009
Last modified: 19 Jul 2019 23:47

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