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| Titel |
Analysis of satellite VEGETATION NDVI time series for estimating Post Fire vegetation recovery |
| VerfasserIn |
Rosa Coluzzi, Tiziana Montesano, Antonio Lanorte, Fortunato De Santis |
| 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 |
250040876
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| Zusammenfassung |
| In this paper we compared Hurst exponent as results from aggregate variance and Detrended
fluctuation analysis to evaluate the estimation of the self similarity coefficients in satellite
time series to assess post fire recovery.
The Hurst exponent for a data set provides a measure of whether, the data
is a pure random walk or has underlying trends. The Hurst exponent was
computed using the aggregate variance which is a time domain method useful
for non-stationary time series. It obtains the multi-scale analysis with the
aggregation of adjacent points and measures the similarity in terms of variance.
If H=0.5, the signal is uncorrelated; if H>0.5 the correlations of the signal are
persistent, where persistence means that a large (small) value (compared to the
average) is more likely to be followed by a large (small) value; if H0.5 the correlations of the
signal are persistent, if α |
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