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

Autor: Armitage, R. P., Kent, M., Weaver, R. E.
Předmět:
Zdroj: International Journal of Remote Sensing; 9/10/2004, Vol. 25 Issue 17, p3369-3388, 20p
Abstrakt: 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. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index