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

Daily monitoring of pre-fire vegetation conditions using satellite MODIS data: the experience of FIRE-SAT in the Basilicata Region 153
MODIS data have been used to obtain both (i) Greenness and (ii) moisture
index.
(i) Greenness is a quite popular fire danger index, developed by Burgan, et
al. (1998). The basis for calculating RG is historical NDVI data that defines
the maximum and minimum NDVI values observed for each pixel. Thus RG
indicates how green each pixel currently is in relation to the range of historical
NDVI observations for it. RG values are scaled from 0 to 100, with
low values indicating the vegetation is at or near its minimum greenness.
Specifically the algorithm is:
RG = (ND0 - NDmn)/(NDmx - Ndmn) * 100
where
ND0 = highest observed NDVI value for the considered
composite period which 8 days
NDmn = historical minimum NDVI value for a given pixel
NDmx = historical maximum NDVI value for a given pixel
The purpose of using relative greenness in the fire danger estimation is to partition
the live fuel load between the live and dead vegetation fuel classes.
(ii) Among the wide range of vegetation indices, specifically devised to
estimate vegetation water content, we adopted the MSI. This choice was
driven by the results from statistical analyses that we performed on a significant
time series. Such results pointed out the all the available satellitebased
moisture index exhibited high correlation values.
MSI = R 1600/ R 820
Where R 1600 and R 820 denote the MODIS Reflectance as acquired in the
spectral bands 1600nm and 820 nm.
The danger classification on live fuel can be estimated by dividing the
range of the MSI maps into different classes. Finally, The fire danger index
(FDI), related to vegetation state, was obtained by combining the danger
classes obtained from RG and those from MSI following an approach similar
to that adopted in Lasaponara (2005) for combining NDVI and
Temperature. High fire danger, as classified by FDI, was deduced by a combination
of high dryness and low RG values, and low fire danger was
deduced by a combination of low dryness and high RG values.
3 - Results and discussion
The analysis was performed in the Basilicata (9,992 km 2 ) Region for the
2008 year. Figures 2 show some fire danger maps obtained for the summer
season. Currently, the fire susceptibility maps are provided daily during the
fire season (summer season) and weekly for the rest of the year.
Results obtained during the first year of the project (2008) shows that more
tha 85% of fires occurred in the areas classified as high and very high dan-