Upland vegetation mapping using Random Forests with optical and radar satellite data

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dc.contributor.authorBarrett, Brian
dc.contributor.authorRaab, Christoph
dc.contributor.authorCawkwell, Fiona
dc.contributor.authorGreen, Stuart
dc.contributor.funderEnvironmental Protection Agency
dc.date.accessioned2017-12-08T13:33:40Z
dc.date.available2017-12-08T13:33:40Z
dc.date.issued2016-11-28
dc.description.abstractUplands represent unique landscapes that provide a range of vital benefits to society, but are under increasing pressure from the management needs of a diverse number of stakeholders (e.g. farmers, conservationists, foresters, government agencies and recreational users). Mapping the spatial distribution of upland vegetation could benefit management and conservation programmes and allow for the impacts of environmental change (natural and anthropogenic) in these areas to be reliably estimated. The aim of this study was to evaluate the use of medium spatial resolution optical and radar satellite data, together with ancillary soil and topographic data, for identifying and mapping upland vegetation using the Random Forests (RF) algorithm. Intensive field survey data collected at three study sites in Ireland as part of the National Parks and Wildlife Service (NPWS) funded survey of upland habitats was used in the calibration and validation of different RF models. Eight different datasets were analysed for each site to compare the change in classification accuracy depending on the input variables. The overall accuracy values varied from 59.8% to 94.3% across the three study locations and the inclusion of ancillary datasets containing information on the soil and elevation further improved the classification accuracies (between 5 and 27%, depending on the input classification dataset). The classification results were consistent across the three different study areas, confirming the applicability of the approach under different environmental contexts.en
dc.description.sponsorshipEnvironmental Protection Agency (Science, Technology, Research and Innovation for the Environment (STRIVE)en
dc.description.statusPeer revieweden
dc.description.versionPublished Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationBarrett, B., Raab, C., Cawkwell, F. and Green, S. (2016) 'Upland vegetation mapping using Random Forests with optical and radar satellite data', Remote Sensing in Ecology and Conservation, 2(4), pp. 212-231. doi: 10.1002/rse2.32en
dc.identifier.doi10.1002/rse2.32
dc.identifier.endpage231
dc.identifier.issn2056-3485
dc.identifier.issued4
dc.identifier.journaltitleRemote Sensing in Ecology and Conservationen
dc.identifier.startpage212
dc.identifier.urihttps://hdl.handle.net/10468/5132
dc.identifier.volume2
dc.language.isoenen
dc.publisherJohn Wiley & Sons Ltd.en
dc.relation.urihttp://onlinelibrary.wiley.com/doi/10.1002/rse2.32/abstract
dc.rights© 2016, the Authors. Remote Sensing in Ecology and Conservation published by John Wiley & Sons Ltd on behalf of Zoological Society of London. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.en
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/
dc.subjectRadaren
dc.subjectRandom forestsen
dc.subjectRemote sensingen
dc.subjectSatellite dataen
dc.subjectUplandsen
dc.subjectVegetation mappingen
dc.titleUpland vegetation mapping using Random Forests with optical and radar satellite dataen
dc.typeArticle (peer-reviewed)en
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