Forest fires are one of the major environmental issues in large areas of Southern Italy, and more generally in Mediterranean Europe. Biomass burning reduces carbon fixation in terrestrial vegetation, while risk of soil erosion increases in burned areas. The premier action against fires is prevention, and in this context fire risk mapping is an invaluable tool.
Various factors, either static or dynamic, contribute to the definition of fire risk. Among them, vegetation moisture plays a key role, since forests susceptibility to fire increases with increasing plant water stress and biomass dryness. A tool is needed to allow a timely detection of such forest conditions, and space-borne and airborne remote sensing can be very effective to this end.
Many authors have demonstrated the role of remote sensing in the assessment of vegetation moisture. Various multi-spectral systems have been reported to be useful, such as Landsat TM, SPOT or NOAA AVHRR. We have recently started a research to evaluate fire risk in the rural environment of Southern Italy using the Moderate Resolution Imaging Spectrometer (MODIS), carried on board of EOS Terra and Aqua satellites. The MODIS systems have 20 spectral wavebands covering the visible, the near infrared and the shortwave infrared with a spectral resolution of 10-50 nm.
This paper describes the results of a preliminary experiment to identify the most useful bands or band combinations (spectral indexes) for the detection of biological indicators of plant water stress. PROSPECT radiative transfer code has been adopted to simulate leaf reflectance as a function of leaf properties. Results highlighted the potential of single and combined simulated MODIS bands in the retrieval of vegetation moisture indicators related to fire risk.