Mapping and classification of Peatland on the Isle of Lewis using Landsat ETM+.
Britain contains some of the largest areas of blanket peatland in the world and the monitoring of this resource is vital. This study has investigated whether Landsat ETM+ can be used to identify types of blanket peatland on Lewis. This was done using Principal Component Analysis (PCA) on composites...
| Publicado en: | Scottish Geographical Journal Vol. 123; no. 3; pp. 173 - 193 |
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| Autores principales: | , , , |
| Formato: | Artículo |
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Taylor & Francis Ltd
Sep2007
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=31183745&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 31183745 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 14702541 8NB jtl: Scottish Geographical Journal issn: 14702541 maglogo: N pubinfo: dt: Sep2007 vid: 123 iid: 3 pid: 377 pub: Taylor & Francis Ltd artinfo: ui: 31183745 10.1080/14702540701786912 ppf: 173 ppct: 20 formats: fmt: – @attributes: type: T – @attributes: type: P size: 1.5MB tig: atl: Mapping and classification of Peatland on the Isle of Lewis using Landsat ETM+. aug: au: Brown, E. Aitkenhead, M. Wright, R. Aalders, I.H. affil: Environment Section, Planning & Development Service, The Highland Council, Inverness, UK University of Aberdeen, Department of Plant & Soil Science, Aberdeen, UK Department of Geography & Environment, University of Aberdeen, Aberdeen, UK The Macaulay Institute, Craigiebuckler, Aberdeen, UK su: Peatlands Artificial neural networks Cartography Remote sensing Geography United Kingdom sug: subj: United Kingdom Peatlands Artificial neural networks Cartography Remote sensing Geography keyword: GIS/cartography land cover peat remote sensing ab: Britain contains some of the largest areas of blanket peatland in the world and the monitoring of this resource is vital. This study has investigated whether Landsat ETM+ can be used to identify types of blanket peatland on Lewis. This was done using Principal Component Analysis (PCA) on composites of band ratios and single band variables, and using neural network classification. The distinction between peatland and non-peatland was easily accomplished, but the identification of different peatland types was more difficult. PCA on a composite of spectral bands 1 to 9 was the most useful composite, but did not improve over the use of NDVI-related band ratios. An overlap was found between peatland classes caused by similar spectral signatures of peat banks and eroded peatland. This was confirmed by a separate study examining the variation between different blanket bog classes in the Land Cover of Scotland 1988 dataset. It is suspected that this problem will remain with Landsat ETM+ -based classification of peatland because the spatial resolution is insufficient to capture the heterogeneous nature of the terrain and vegetation types. The paper discusses further methodologies and information sources which, in combination with Landsat ETM+ data, could improve the ability to classify peatland. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Copyright of Scottish Geographical Journal is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. item: Scottish Geographical Journal holder: Taylor & Francis Ltd dt: @attributes: year: 2007 holdings: @attributes: islocal: N |
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