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Modeling fire ignition patterns in Mediterranean urban interfaces

  • M. Elia
  • V. Giannico
  • R. Lafortezza
  • G. Sanesi
Original Paper

Abstract

The rapid growth of built-up areas and infrastructure in the Mediterranean environment has resulted in the expansion of urban interfaces where fire can ignite and spread. Within this context, there is a need to understand spatial patterns of ignition distribution and the relative importance of influencing drivers. In response to this need we developed an analysis of fire ignition patterns using human and biophysical explanatory variables by firstly developing two different linear models to assess patterns of fire ignition points in terms of occurrence (presence/absence) and frequency (number of ignition points per area and secondly applying statistical tests to both models to evaluate the most important human and/or biophysical drivers influencing these patterns. The probability of ignition point occurrence and frequency were mapped using the predicted values of the two models in the Apulia region (southern Italy). Our findings revealed that dependent variables (fire ignition occurrence points and frequency) are negatively correlated with population density, but positively correlated for presence of urban areas with a significantly higher likelihood of ignition in cultivated (crop)land, forest, shrubland, grassland, and other natural spaces. The probability of ignition increased with elevation and slope. The maps show that the probability of ignition occurrence is relevant along the coast in the northern and southern parts of the region, especially in urban interfaces with a strong presence of shrubland and Mediterranean maquis. Ignition point frequency was predicted along the coast, particularly in the south and in some densely urbanized inland areas. By adopting the models, forest managers and decision makers may avail of the knowledge gained to design and promote sustainable fire management strategies in the Apulia region.

Keywords

Fire Ignition points Logistic regression Poisson regression Urban interface 

Notes

Acknowledgements

This research was developed in the context of the project concerning the update of the forecasting, monitoring and suppression forest fire risk plan (AIB plan) in the Apulia Region, funded by Civil Protection Department.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Agricultural and Environmental SciencesUniversity of Bari “A. Moro”BariItaly

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