7th Workshop on Forest Fire Management - EARSeL, European ...

Abstract: In this paper NDVI VEGETATION time series were analysed using
the Detrended Fluctuation Analysis (DFA) to estimate post fire vegetation
recovery.The DFA is a well-known methodology, which allows the detectin
of long-range power-law correlations in signals possibly characterized by
nonstationarity, which features most of the observational and experimental
signals. Results from our analysis point out that the persistence of vegetation
dynamics is significantly increased by the occurrence of fires. In particular,
a scaling behavior of two classes of vegetation (burned and
unburned) has been revealed. The estimated scaling exponents of both
classes suggest a persistent character of the vegetation dynamics. But, the
burned sites show much larger exponents than those calculated for the
unburned sites.
1 - Introduction
POST FIRE VEGETATION RECOVERY ESTIMATION USING
SATELLITE VEGETATION TIME SERIES
R. Lasaponara , R. Coluzzi , F. Desantis,
A. Lanorte, L. Telesca
CNR-IMAA, Tito Scalo (PZ) Italy
a.lanorte@imaa.cnr.it
The dynamics of vegetation covers in burned and unburned areas can be
monitored by using satellite data, which provide a wide spatial coverage
and internal consistency of data sets. Several indices can be used to perform
such kind of remote sensing monitoring. In particular, NDVI
(Normalized Difference Vegetation Index) obtained from the visible (Red)
and near infrared (NIR) by using the following formula NDVI= (NIR-
Red)/(NIR+ Red), is the most widely used index to follow the process of
recovery after fire.
This investigation aims to perform a dynamical characterization of burned
and unburned vegetation covers, using time series of remotely sensed data
of two fire-affected and two fire-unaffected sites. For this purpose, we used
the Detrended Fluctuation Analysis (DFA), which permits the detection of
persistent properties in nonstationary signals.
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