http://www.cnr.it/ontology/cnr/individuo/prodotto/ID43007
The contribution of hyperspectral remote sensing to identify vegetation characteristics necessary to assess the fate of Persistent Organic Pollutants (POPs) in the environment (Articolo in rivista)
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- Label
- The contribution of hyperspectral remote sensing to identify vegetation characteristics necessary to assess the fate of Persistent Organic Pollutants (POPs) in the environment (Articolo in rivista) (literal)
- Anno
- 2006-01-01T00:00:00+01:00 (literal)
- Alternative label
Boschetti M., Brivio P.A., Carnesale D., Di Guardo A. (2006)
The contribution of hyperspectral remote sensing to identify vegetation characteristics necessary to assess the fate of Persistent Organic Pollutants (POPs) in the environment
in Annals of geophysics (Testo stamp.)
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Boschetti M., Brivio P.A., Carnesale D., Di Guardo A. (literal)
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- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
- Rivista
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- ISI Web of Science (WOS) (literal)
- Titolo
- The contribution of hyperspectral remote sensing to identify vegetation characteristics necessary to assess the fate of Persistent Organic Pollutants (POPs) in the environment (literal)
- Abstract
- During recent years hyperspectral remote sensing data were successfully used to characterise the state and properties
of vegetation. The information on vegetation cover and status is useful for a range of environmental modelling
studies. Recent works devoted to the understanding of the fate of Persistent Organic Pollutants (POPs) in
the environment showed that forests and vegetation in general act as a «sponge» for chemicals present in air and
the intensity of this «capture» effect depends on some vegetation parameters such as surface area, leaf composition,
turnover etc. In the framework of the DARFEM experiment conducted in late June 2001, different airborne
hyperspectral images were acquired and analysed to derive some vegetation parameters of relevance for
multimedia models, such as the spatial distribution of plant species and their relative foliage biomass. The study
area, South West of Milan, encompasses a range of land cover types typical of Northern Italy, including intensive
poplar plantations and natural broad-leaf forest. An intensive field campaign was accomplished during the
aerial survey to collect vegetation parameters and radiometric measurements. Results obtained from the analysis
of hyperspectral images, map of vegetation species, Leaf Area Index (LAI) and foliage biomass are presented
and discussed. (literal)
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