Patrono, Andrea
ecological processes that can take decades depending on the intensity of the fire and the % damage. Additionally the long
term forecast is not entirely acceptable and applicable since unpredictable natural or anthropogenic occurrences may eas-
ily modify the extrapolated trends.
Despite the fact that all sites are characterised by typical Mediterranean features, the methods applied have, in some
localised cases, minor discrepancies and effectiveness due to locally varying environmental and climatic conditions; an
addition of collateral data - for example land cover, terrain, climatic, etc. - would have helped in solving doubtful situa-
tions.
From a practical viewpoint, the developed methodology strives to lead the information output to a stage that can be of
best use for decision makers involved in post-fire management. For example when replanting occurs within the imagery
time frame (as in one of the studied cases) the efficiency of the methodology can be analysed in terms of deviation from
the expected trend or, vice versa, the analytical process may be used to highlight areas characterized by lower recovery
ratios (e.g. extremely damaged areas) where mitigation measurements should be enforced to avoid further deterioration.
As a general conclusion, it is possible to state that in most of the areas, affected by anthropic pressure and not in extreme
environmental situations such as very steep slopes, the NDVI values reach the pre-fire levels in an average range of three/
four years, confirming that the pioneer stages of vegetation recovery have an immediate post-fire reaction.
REFERENCES
De Bano L.F,, Neary D.G., Folliott P.F,, 1998. Fire’s Effects on Ecosystems. John Wiley & Sons, New York. 331 pp.
Fiorella M., Ripple W.J., 1993. Determining successional stage of temperate coniferous forests with Landsat satellite
data. Photogrammetric Engineering & Remote Sensing, 59(2): 239-246.
Lillesand M., Kiefer R.W., 1987. Remote Sensing and Image Interpretation. John Wiley & Sons, New York. 721 pp.
Maselli F., Rodolfi L., Conese C., 1996. Evaluation of forest fire risk by the analysis of environmental data and TM
images. Int. J. Remote Sensing, 17(7):1417-1423.
Odum E.P., 1993. Ecology and Our Endangered Life-Support Systems. Sinauer Associates Inc. Publ., Massachusetts,
301 pp.
Sabins EF. jr., 1987. Remote Sensing Principles and Interpretations. Freeman & Co., New York. 494 pp.
Whelan R.J., 1995. The Ecology of Fires. Cambridge University Press. 346 pp.
1136 International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B7. Amsterdam 2000.
F3 a3 C) C em ew gm nN}
evt
Uu r^ ej en n) u— mmo mb