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| Titel |
Estimation of vegetation cover resilience from satellite time series |
| VerfasserIn |
T. Simoniello, M. Lanfredi, M. Liberti, R. Coppola, M. Macchiato |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 12, no. 4 ; Nr. 12, no. 4 (2008-07-30), S.1053-1064 |
| Datensatznummer |
250010757
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| Publikation (Nr.) |
 copernicus.org/hess-12-1053-2008.pdf |
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| Zusammenfassung |
Resilience is a fundamental concept for understanding vegetation as a
dynamic component of the climate system. It expresses the ability of
ecosystems to tolerate disturbances and to recover their initial state.
Recovery times are basic parameters of the vegetation's response to forcing
and, therefore, are essential for describing realistic vegetation within
dynamical models. Healthy vegetation tends to rapidly recover from shock and
to persist in growth and expansion. On the contrary, climatic and anthropic
stress can reduce resilience thus favouring persistent decrease in
vegetation activity.
In order to characterize resilience, we analyzed the time series 1982–2003
of 8 km GIMMS AVHRR-NDVI maps of the Italian territory. Persistence
probability of negative and positive trends was estimated according to the
vegetation cover class, altitude, and climate. Generally, mean recovery
times from negative trends were shorter than those estimated for positive
trends, as expected for vegetation of healthy status. Some signatures of
inefficient resilience were found in high-level mountainous areas and in the
Mediterranean sub-tropical ones. This analysis was refined by aggregating
pixels according to phenology. This multitemporal clustering synthesized
information on vegetation cover, climate, and orography rather well. The
consequent persistence estimations confirmed and detailed hints obtained
from the previous analyses. Under the same climatic regime, different
vegetation resilience levels were found. In particular, within the
Mediterranean sub-tropical climate, clustering was able to identify features
with different persistence levels in areas that are liable to different
levels of anthropic pressure. Moreover, it was capable of enhancing reduced
vegetation resilience also in the southern areas under Warm Temperate
sub-continental climate. The general consistency of the obtained results
showed that, with the help of suited analysis methodologies, 8 km AVHRR-NDVI
data could be useful for capturing details on vegetation cover activity at
local scale even in complex territories such as that of the Italian
peninsula. |
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