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| Titel |
NDVI as a tool for measuring impact of climate variability upon vegetation |
| VerfasserIn |
Alessandro M. S. Delitala, Marco Vizzari, Paolo Capece, Michele Fiori, Giovanna Maria Mannu, Ciro Luca Pacicco, Roberto Pinna Nossai |
| Konferenz |
EGU General Assembly 2010
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 12 (2010) |
| Datensatznummer |
250040156
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| Zusammenfassung |
| Land-atmosphere interactive processes are useful to understand impacts of year by year
climate variability and to highlight possible trends, since the status of the natural vegetation
cover is strongly controlled by climate factors.
The so-called NDVI (Normalized Difference Vegetation Index), derived from the red and the
near infrared channels of NOAA satellite, is a reliable indicator applicable to the analysis of
photosynthetic biomass variations in vegetated areas.
NDVI images, derived on a monthly basis by maximum composite value technique, can
become a useful tool to monitor the dynamics of vegetation and to determine the maximum
level of vegetation greenness observed over every year.
Interannual variability of precipitation is likely to have a significant impact on the greenness
of vegetation cover, since rainy seasons are expected to stimulate a much richer plants
development than drier ones.
The present poster intends to outline a research, jointly carried by ARPAS (the Regional
Environmental Protection Agency of Sardinia) and the “Department of Man and Territory” of
the University of Perugia, that aimed to correlate the year by year variability of hydrological
variables (precipitation and soil water content) and the maximum annual NDVI over the
island of Sardinia.
In order to do that, the authors defined four test areas, extending from 235 km2 to 1015 km2.
Test areas were chosen in order to be mostly covered by natural vegetations, according to
CORINE land-cover.
Over such areas surface measures by ARPAS stations were compared against annual
maximum NDVI index from 1998 to 2008, focusing on the so-called “rainy season” that in
Sardinia ranges from October to April.
Precipitation for the selected areas was measured with the network of ground stations of
ARPAS. Evapotranspiration was estimated by means of Hargreaves-Samani method
applied to data from the above stations. Finally, estimation of the soil moisture
content was carried out by means of a daily time step simplified water balance
model.
Despite the low resolution of NDVI images, the maximum value of each year responded quite
well to interannual variability of precipitation and soil water content.
Different NDVI responses was observed in relation to the various land cover classes of
CORINE data. Because of the low image resolution and of the complex spatial patterns of
vegetated area under investigation, this analysis was performed using the second level of the
CORINE hierarchical classification.
In the last phase of the study, the authors defined a few small test area completely
homogeneous as far as the type of land cover. This further analysis aimed to highlight
different responses by the different type of vegetations: deciduous woods, evergreen, prairies
and others. |
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