7th Workshop on Forest Fire Management - EARSeL, European ...
7th Workshop on Forest Fire Management - EARSeL, European ...
7th Workshop on Forest Fire Management - EARSeL, European ...
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42<br />
I - PRE-FIRE PLANNING AND MANAGEMENT<br />
The distance bands so found were introduced in Getis and Ord’s G, in order<br />
to find where clusters were localized. Getis and Ord’s index value was classified<br />
according to date of occurrence of the event as reported in figure 1<br />
and in table 2, which shows the example of the 2000 year.<br />
Figure 1 shows fire locati<strong>on</strong> and “seas<strong>on</strong>al” occurrence for the years 1999,<br />
2002, 2003, 2005 which exhibited the higher time and spatial clusterizati<strong>on</strong>.<br />
The spatial distributi<strong>on</strong> of fires depends <strong>on</strong> different types of land use<br />
and also <strong>on</strong> different interannual climate variability, which lead to different<br />
fire susceptibility. It is quite interesting the fact that: (i) for the 1999<br />
year fires mainly occurred in the summer, as usual for the Mediterranean<br />
ecosystems (ii) for 2002 fire occurred, as usual, in summer but also during<br />
winter, and finally (iii) for both 2003 and 2005 years fires happened during<br />
the spring, summer and winter seas<strong>on</strong>. This behavior shows a significant<br />
variability in the fire “seas<strong>on</strong>ality” for the Basilicata Regi<strong>on</strong>.<br />
Seas<strong>on</strong> Day of the year when the event occurred Getis and Ord’s G<br />
winter 1 79 -4,02502 -2,01534<br />
356 365 1,89023 2,83819<br />
springer 80 171 -2,01534 -0,00567<br />
summer 172 294 -0,00567 0,94228<br />
autumn 295 355 0,94228 1,89023<br />
Table 2 - Classificati<strong>on</strong> of Getis and Ord’s G for dataset of 2000 year.<br />
4 - Final remarks<br />
The aim of this study was to characterize the interannual fire activity in the<br />
Basilicata Regi<strong>on</strong>. Areas of homogeneous fire dynamics were identified with<br />
cluster analysis. The cluster obtained are physically meaningful and this<br />
allows us to better characterize and understand fire activity variability. This<br />
provides useful informati<strong>on</strong> to investigate the relative importance of different<br />
factors influencing short-term variability in fire occurrence at different<br />
scales and to better understand the c<strong>on</strong>tributi<strong>on</strong> of human activities<br />
and climate variability to the fire incidence. Our results show that rainfall<br />
variability significantly influences the fire occurrence and areas with different<br />
types of land use react in a different way to interannual climate variability,<br />
leading to different fire susceptibility depending <strong>on</strong> the land use<br />
type.