No abstract

No abstract

No abstract

No abstract

No abstract

Mediterranean vegetation is strongly subjected to the risk of wild res, which can become a major cause of land degradation. The knowledge of the spatial variations of this risk is essential, therefore, for forest resource management. Relying on the fact that diOE erent vegetation types can be associated with diOE erent risk levels, a classi cation approach based on the use of Landsat Thematic Mapper (TM) scenes is currently proposed for the generation of maps related to re risk. Hard and fuzzy classi cations were tested for this purpose on Elba island (central Italy), taking into account the eOE ects of the use of scenes from diOE erent periods (spring and summer) and of ancillary data. The re risk images obtained were evaluated by comparison with the re events that occurred on the island during the last decade. The results show that, while the acquisition period has only minor eOE ects, classi cation accuracy is strongly dependent on the inclusion of ancillary data. Moreover, the fuzzy approach better exploits the information of the integrated datasets, producing maps which are temporally stable and highly indicative of the re risk in the study area.

No abstract

No abstract