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Jonathan Seaquist

Head of department

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Detecting recent disturbance on montane blanket bogs in the Wicklow Mountains, Ireland, using the MODIS enhanced vegetation index


  • J. Connolly
  • N. Holden
  • Jonathan Seaquist
  • S. Ward

Summary, in English

Irish peat soils are extensive, covering approximately 14-20% of the national land area. They contain between 53% and 62% of the national soil organic carbon stock. Montane blanket bog covers approximately 25% or 242650ha of the total peatland area in Ireland and is the dominant peatland type covering the upland area of Wicklow. Blanket bogs are very sensitive systems and have experienced much disturbance in Ireland due to overgrazing, burning, drainage, forestry and turf cutting. It has been estimated that disturbance of blanket bog, on a national area basis, ranges from 74% to 82% and in Wicklow is 57%. Disturbance can be detrimental to stocks of soil organic carbon in peatlands. Monitoring disturbance in peatlands, which tend to cover large, remote areas, is difficult and expensive using conventional surveying methods. Satellite remote sensing offers a way to gather data for these areas. In this paper a method of determining the probability of disturbance is presented. This method uses the Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) in combination with univariate image differencing along with thresholding and binary logistic regression. A probability map was produced depicting the geospatial patterns and pressures on the peatland soil organic carbon stock in Wicklow. Peat soils in higher and steeper areas were more disturbed and the primary disturbance in between 2000 and 2005 was fire. Lower, flatter areas did not experience as much disturbance probably because they are wetter. The consumer's and producer's accuracy for the map was 76% and 42%, respectively.


  • Dept of Physical Geography and Ecosystem Science
  • BECC: Biodiversity and Ecosystem services in a Changing Climate

Publishing year







International Journal of Remote Sensing





Document type

Journal article


Taylor & Francis


  • Physical Geography




  • ISSN: 1366-5901