FOREST FIRE RISK ZONE MAPPING FROM SATELLITE IMAGERY AND GIS A CASE STUDY

Forest fires are one of the major natural risk in the Mediterranean countries. In such areas, fires occur frequently and there is a need for supranational approaches that analyse wide scenarios of factors involved and global fire effects. It is impossible to control nature, but is possible to map forest fire risk zone and thereby minimise the frequency of fire. Fire risk must involve both ignition and spreading risk. It is necessary to be able to estimate the spread of fire starting in any stand of a forest, giving the burning conditions. Spreading of forest fire can impose a threat to the natural coverage of land and safety of population. Early detection of forest fires is essential in reduction of fire damage. Satellite data plays a vital role in identifying and mapping forest fire and in recording the frequency at which different vegetation types/zones are effected. A geographic information system (GIS) can be used effectively to combine different forest-fire causing factors for demanding the forest fire risk zone map. A risk model for fire spreading is set up for Gallipoli Peninsula as a pilot zone, because it continually faces a forest fire problem. It is based upon a combination of remote sensing and GIS data. In this study, the LANDSAT satellite images were used. In order to search the effects of the fire occurred in the region on the 25 July 1994, the satellite images both before the fire and after the fire were used. Parameters that effect the fire such as topography and vegetation with the other land use information including population, settlements, forest fire towers, fire stations, intervention places, the characteristics of the staff that will intervene and transportation were integrated within GIS. The shortest way of intervention during the disaster and the areas to be emptied were questioned. For these analyses ARCGIS software was used. Land use information were obtained from the satellite images in this study. In this phase the distinction of spices in the forest was determined using supervised classification. The lands that have priorities in case of fire were decided by combining the moisture of the land and slope classes that were determined by conventional approaches with the satellite images. The results of the analysis were shown by reports and graphics. The test region results should be applied all over Turkey.