Leaves of Quercus ilex as Indicators of Airborne Trace Element Distribution in Lucca (Central Italy) - Francini, A.; Lorenzini, G.; Nali, C.; Loppi, S. (II INTERNATIONAL CONFERENCE ON LANDSCAPE AND URBAN HORTICULTURE, 2010)
Ambient air has always contained particles, ranging from sub-micrometric aerosols to clearly visible dust and sand grains. Plants have evolved to maximise light interception and CO2 assimilation and, as a consequence, they are also highly efficient receptors of airborne pollutants. The use of plant tissues has since long been shown to be an effective indicator of metal air pollution. Leaves of the evergreen species Quercus ilex were used as a passive sampler to describe the distribution of selected elements in the area around the walls of Lucca (Central Italy). Unwashed healthy mature leaves collected in June 2006 from 16 sampling sites were analysed by ICP-MS for Al, Ba, Be, Bi, Br, Ca, Cd, Cl, Co, Cr, Cs, Cu, Fe, K, Li, Mg, Mn, Mo, Na, Ni, Pb, Si, Ti, V and Zn. Values were normalised by subtracting baseline concentrations of biologically essential elements coming from Q. ilex plants collected into Botanical Garden of Lucca. Enrichment factors (EF) were calculated taking Al as crustal reference element. Cd, Cu and Zn exhibited the highest EF, with values ranging between 100 and 1000. Varimax rotated factor analysis allowed identifying three main source groups of elements, namely crustal components, sea-salt spray and anthropogenic sources (vehicular traffic, industrial activities). The factor one (crustal components) explained 48.3% of the total variance. Common high loadings for this factor were Al, Bi, Br, Co, Cu, Fe, Si, V, and Zn, which indicate a predominant soil contribution. Results are discussed with emphasis on the potential role of vegetation for the removal of particulate pollution.
The following values have no corresponding Zotero field: periodical: II INTERNATIONAL CONFERENCE ON LANDSCAPE AND URBAN HORTICULTURE pub-location: 999 RIVERVIEW DR, STE 208, TOTOWA, NJ 07512-1165 USA
Keywords: enrichment factor; factor analysis; ICP-MS; pollution

Assessment of biophysical vegetation properties through spectral decomposition techniques - Hurcom, S J; Harrison, A R; Taberner, Malcolm (Remote sensing of environment, 1996)
This article demonstrates the use of spectral decomposi- tion for analyzing the spectral response of different semi- arid vegetation species found throughout Mediterranean Europe. Using this technique, it is possible to decompose a spectral data set into a smaller number of significant factors that represent the key variables affecting vegeta- tion spectral response. The results presented here show how spectral decomposition can be used to determine the intrinsic number and identity of the significant factors affecting the multispectral response. For the dataset inves- tigated here, which comprises field spectra recorded over 1130 wavelengths, using a GER single field-of-view IRIS (SIRIS) spectroradiometer, it was found that a combina- tion of just four factors was responsible for the majority of spectral variance. Interpretation of these factors was carried out by graphical analysis, stepwise regeneration of the original spectra, and correlation with biophysical data. Considering the identity of these factors, it was found that the second most significant factor (factor 2) was strongly related to the proportion of directly irradi- ated green leaves within the field-of-view of the spectrora- diometer. In addition, it was found that the fourth most significant factor (factor 4) provided a good summary of the spectral response of the different samples in the region of strong chlorophyll absorption. This demonstrates the possibility of using spectral decomposition techniques, particularly in environments dominated by spectrally similar vegetation classes, to model the mixed spectral population as mixtures of fundamental biophysical pa- rameters rather than as mixtures of the classes themselves.
Keywords: factor analysis; leaf reflectance; spectral decomposition; surface leaf area (voyant)