Identification of the spectral characteristics of British semi-natural upland vegetation using direct ordination: a case study from Dartmoor, UK

Armitage, RP ORCID:, Kent, M and Weaver, RE 2004, 'Identification of the spectral characteristics of British semi-natural upland vegetation using direct ordination: a case study from Dartmoor, UK' , International Journal of Remote Sensing, 25 (17) , pp. 3369-3388.

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The direct ordination technique Canonical Correspondence Analysis (CCA) is applied to the examination of the relationships between the floristic composition of semi-natural vegetation and its spectral reflectance. Paired measurements of floristic and spectral characteristics, the latter being measured using a portable field spectrometer, were collected at ground level for a range of upland semi-natural vegetation within two study sites on Dartmoor, south-west England. The spectral data were converted to simulate a Compact Airborne Spectrographic Imager (CASI) bandset. Both floristic and spectral data sets were then jointly ordinated using CCA. A sequence of individual species changes along the first ordination axis was identified that showed a strong correspondence with variation in the simulated CASI wavebands covering the 736 nm to 870 nm wavelengths. A significant relationship between first axis CCA scores for quadrats and their estimated total percentage vegetation cover was also identified. Although UK National Vegetation Classification (NVC) categories corresponded to a general sequence of plant community types along the first CCA axis, with the possible exception of the U20 Pteridium aquilinum-dominated community, it proved impossible to demonstrate any close link between any specific plant community type and a distinct set of spectral characteristics because of the continuum nature of the vegetation. The second axis of the CCA showed no interpretable relationship with variation in floristic/spectral data and this was confirmed further by use of Detrended Canonical Correspondence Analysis (DCCA). Possibilities for further research into floristic/spectral data using CCA/DCCA are discussed.

Item Type: Article
Themes: Subjects / Themes > G Geography. Anthropology. Recreation > GA Mathematical geography. Cartography
Subjects / Themes > T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101 Telecommunication (Inc. www, lidar, radio, radar, phone, TV)
Subjects / Themes > G Geography. Anthropology. Recreation > GE Environmental Sciences
Subjects / Themes > Q Science > QH Natural history
Subjects outside of the University Themes
Schools: Schools > School of the Built Environment
Schools > School of Environment and Life Sciences > Ecosystems and Environment Research Centre
Journal or Publication Title: International Journal of Remote Sensing
Publisher: Taylor & Francis
Refereed: Yes
ISSN: 0143-1161
Depositing User: H Kenna
Date Deposited: 08 Oct 2007 14:48
Last Modified: 27 Aug 2021 22:02

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