Author(s)

L. Pirone, F. Intini & V. D’Agostino

Abstract

In this paper we present a new approach for evaluating forest fire static risk. This new methodology, based on cartographic data integration, has been applied to Alta Murgia National Park, located in the South East of Italy, to identify fire more vulnerable areas. The static risk resulted strongly dependent on factors which are constant or which are varying very slowly with time, such as morphological factors (exposition, inclination), environmental static factors (soil use and vegetation coverage) and human factors (urban areas extension, road network, restoring activity centres, fire recurrence during the past five years at least). Moreover, on the short time, fire risk (particularly fire start and development) results strictly related to different factors such as vegetation factors (types and density, maintenance management rules), orographic factors (altitude, sides exposition and inclination, insulation), meteorological factors (air temperature, air humidity, wind velocity and direction, last ten days cumulated rain). The methodology we used is based on a step by step procedure for the calculation of any of the factors mentioned above. Data processing has been realized in a GIS (Arcview 3.2) environment using overlay procedures. The result is a chart representing five levels of fire risk (static) with a resolution of 30 m. Significantly helpful resulted fuzzy logic applications for previous indicators integration. This kind of procedure, which allows remote sensing data as well as local measured data assimilation, gives to local authorities a highly versatile tool for fire risk localisation and for Alta Murgia Park resources optimal planning and management. Keywords: fire risk, fuzzy logic, AHP, WLC, Alta Murgia Park.

Keywords

fire risk, fuzzy logic, AHP, WLC, Alta Murgia Park.