The potential for modelling peatland habitat condition in Scotland using long-term MODIS data

Rebekka Artz (Corresponding Author), Sally Johnson, Patricia Bruneau, Andrea J. Britton, Ruth J Mitchell, Louise Ross, Gillian Donaldson-Selby, David Donnelly, Matt J. Aitkenhead, Alessandro Gimona, Laura Poggio

Research output: Contribution to journalArticle

Abstract

Globally, peatlands provide an important sink of carbon in their near natural state but potentially act as a source of gaseous and dissolved carbon emission if not in good condition. There is a pressing need to remotely identify peatland sites requiring improvement and to monitor progress following restoration. A medium resolution model was developed based on a training dataset of peatland habitat condition and environmental covariates, such as morphological features, against information derived from the Moderate Resolution Imaging Spectroradiometer (MODIS), covering Scotland (UK). The initial, unrestricted, model provided the probability of a site being in favourable condition. Receiver operator characteristics (ROC) curves for restricted training data, limited to those located on a peat soil map, resulted in an accuracy of 0.915. The kappa statistic was 0.8151, suggesting good model fit. The derived map of predicted peatland condition at the suggested 0.56 threshold was corroborated by data from other sources, including known restoration sites, areas under known non-peatland land cover and previous vegetation survey data mapped onto inferred condition categories. The resulting locations of the areas of peatland modelled to be in favourable ecological condition were largely confined to the North and West of the country, which not only coincides with prior land use intensity but with published predictions of future retraction of the bioclimatic space for peatlands. The model is limited by a lack of spatially appropriate ground observations, and a lack of verification of peat depth at training site locations, hence future efforts to remotely assess peatland condition will require more appropriate ground-based monitoring. If appropriate ground-based observations could be collected, using remote sensing could be considered a cost-efficient means to provide data on changes in peatland habitat condition.
Original languageEnglish
Pages (from-to)429-442
Number of pages14
JournalScience of the Total Environment
Volume660
Early online date22 Dec 2018
DOIs
Publication statusPublished - 10 Apr 2019

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peatland
MODIS
Imaging techniques
Peat
habitat
Restoration
modeling
Carbon
Land use
Remote sensing
Statistics
Soils
peat soil
Monitoring
carbon emission
Costs
peat
land cover
remote sensing
land use

Keywords

  • peatland
  • habitat condition
  • remote sensing
  • MODIS
  • modelling
  • mapping
  • REMOTE-SENSING APPROACH
  • PATTERNS
  • Mapping
  • Habitat condition
  • Remote sensing
  • CARBON STOCKS
  • HOMOGENIZATION
  • MOISTURE
  • Modelling
  • EXAMPLE
  • UPLAND VEGETATION
  • INDEX
  • Peatland
  • WATER

Cite this

The potential for modelling peatland habitat condition in Scotland using long-term MODIS data. / Artz, Rebekka (Corresponding Author); Johnson, Sally; Bruneau, Patricia; Britton, Andrea J.; Mitchell, Ruth J; Ross, Louise; Donaldson-Selby, Gillian; Donnelly, David; Aitkenhead, Matt J.; Gimona, Alessandro; Poggio, Laura.

In: Science of the Total Environment, Vol. 660, 10.04.2019, p. 429-442.

Research output: Contribution to journalArticle

Artz, R, Johnson, S, Bruneau, P, Britton, AJ, Mitchell, RJ, Ross, L, Donaldson-Selby, G, Donnelly, D, Aitkenhead, MJ, Gimona, A & Poggio, L 2019, 'The potential for modelling peatland habitat condition in Scotland using long-term MODIS data', Science of the Total Environment, vol. 660, pp. 429-442. https://doi.org/10.1016/j.scitotenv.2018.12.327
Artz, Rebekka ; Johnson, Sally ; Bruneau, Patricia ; Britton, Andrea J. ; Mitchell, Ruth J ; Ross, Louise ; Donaldson-Selby, Gillian ; Donnelly, David ; Aitkenhead, Matt J. ; Gimona, Alessandro ; Poggio, Laura. / The potential for modelling peatland habitat condition in Scotland using long-term MODIS data. In: Science of the Total Environment. 2019 ; Vol. 660. pp. 429-442.
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N1 - Funding: All James Hutton Institute authors are supported by the Scottish Government’s Rural and Environment Research and Analysis Directorate under the current Strategic Research Programme (2016-2021). Sally Johnson, Patricia Bruneau and Louise Ross did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors for this project. The peat spatial extent model was created in part within a UK Government – Department for Business, Energy and Industrial Strategy-funded project (TRN860/07/2014, Scoping the use of the methodology set out in Chapters 2 and 3 of the ‘2013 Supplement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories: Wetlands in the UK GHG Inventory: Land Use, Land Use Change and Forestry (LULUCF)), with further updates created within the Strategic Research Programme (2016-2021) funding.

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KW - mapping

KW - REMOTE-SENSING APPROACH

KW - PATTERNS

KW - Mapping

KW - Habitat condition

KW - Remote sensing

KW - CARBON STOCKS

KW - HOMOGENIZATION

KW - MOISTURE

KW - Modelling

KW - EXAMPLE

KW - UPLAND VEGETATION

KW - INDEX

KW - Peatland

KW - WATER

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