Detection of Forest Fire Risk Areas of Zonguldak and Eregli Regional Forest Directorate

Abstract

Nowadays, detecting the recent increase in naturally caused or human induced forest fires by using the techniques of Remote Sensing and Geographic Information Systems has become quite crucial for fire management and planning. Mapping the risk areas of forest fires for fighting will be very beneficial in terms of labour, time and cost. In relation with the fighting forest fire, the forest fire risk maps partially reveal the factors that affect the fire outbreak and its course. Under the conditions of our country, the crucial use and help of these maps, particularly the ones related with the human factors in the land categories for evaluating the forest fire risk, have been clearly comprehended. In this study, a total of 126 forest fires that occur within the Zonguldak and Eregli regional forest directorate between 2008 to 2019 were investigated using forest fire information form. Human factors, topographic factors and land use categories that caused fire in outbreak area were identified. The vector illustrations related to the settlements and road networks were made on Google Earth. For the topographic data, Digital Elevation Model input was used. The classification processes were carried out through Landsat 8 satellite data for the land usage data and the classes that had been subjected to the fires were identified, respectively. The congruity scores evaluated for corresponding factors were determined by Analytical Hierarchy Process method. The forest fire risk map was produced in Geographic Information Systems according to these results. Additionally, the low, medium and high risk groups were classified on it. It has been seen that 18% of the area was in low, 43% was in medium and %39 of it was in high forest fire risk group. For the accuracy validation of classified map, the discriminant analysis was performed. It has been observed that the importance of classifying fire risk groups of study area was 86% in relation with the assessment of fire risk index values obtained by the analysis that was conducted in this study. Being a significant base for interception of forest fires and fire management, this research might also be improved for other fire sensitive regions.