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Analysis of recent spatial–temporal evolution of human driving factors of wildfires in Spain

Author

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  • Marcos Rodrigues

    (University of Zaragoza)

  • Adrián Jiménez

    (University of Zaragoza)

  • Juan de la Riva

    (University of Zaragoza)

Abstract

Fire regimes are strongly dependent on human activities. Understanding the relative influence of human factors on wildfire is an important ongoing task especially in human-dominated landscapes such as the Mediterranean, where anthropogenic ignitions greatly surpass natural ignitions and human activities are modifying historical fire regimes. Most human drivers of wildfires have a temporal dimension, far beyond the appearance of change, and it is for this reason that we require an historical/temporal analytical perspective coupled to the spatial dimension. In this paper, we investigate and analyze spatial–temporal changes in the contribution of major human factors influencing forest fire occurrence, using Spanish historical statistical fire data from 1988 to 2012. We hypothesize that the influence of socioeconomic drivers on wildfires has changed over this period. Our method is based on fitting yearly explanatory regression models—testing several scenarios of wildfire data aggregation—using logit and Poisson generalized linear models to determine the significance thresholds of the covariates. We then conduct a trend analysis using the Mann–Kendall test to calculate and analyze possible trends in the explanatory power of human driving factors of wildfires. Finally, Geographically Weighted Regression Models are explored to examine potential spatial–temporal patterns. Our results suggest that some of the explanatory factors of logistic models do vary over time and that new explanatory factors might be considered (such as arson-related variables or climate factors), since some of the traditional ones seem to be losing significance in the presence–absence models, opposite to fire frequency models. In particular, the wildland–agricultural interface and wildland–urban interface appear to be losing explanatory power regarding ignition probability, and protected areas are becoming less significant in fire frequency models. GWR models revealed that this temporal behavior is not stationary neither over space nor time.

Suggested Citation

  • Marcos Rodrigues & Adrián Jiménez & Juan de la Riva, 2016. "Analysis of recent spatial–temporal evolution of human driving factors of wildfires in Spain," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 84(3), pages 2049-2070, December.
    • Handle: RePEc:spr:nathaz:v:84:y:2016:i:3:d:10.1007_s11069-016-2533-4
    DOI: 10.1007/s11069-016-2533-4
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    References listed on IDEAS

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    Cited by:

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    2. Rasheed Akinleye Hammed & Gbenga Lawrence Alawode & Laura E. Montoya & Andrey Krasovskiy & Florian Kraxner, 2024. "Exploring Drivers of Wildfires in Spain," Land, MDPI, vol. 13(6), pages 1-24, May.
    3. Shu Wu, 2021. "RETRACTED: The Temporal-Spatial Distribution and Information-Diffusion-Based Risk Assessment of Forest Fires in China," Sustainability, MDPI, vol. 13(24), pages 1-18, December.
    4. Alessandra Canepa, 2024. "Socio-economic risk factors and wildfire crime in Italy: a quantile panel approach," Empirical Economics, Springer, vol. 66(1), pages 431-465, January.
    5. Ingrid Vigna & Angelo Besana & Elena Comino & Alessandro Pezzoli, 2021. "Application of the Socio-Ecological System Framework to Forest Fire Risk Management: A Systematic Literature Review," Sustainability, MDPI, vol. 13(4), pages 1-20, February.
    6. Margherita Carlucci & Ilaria Zambon & Andrea Colantoni & Luca Salvati, 2019. "Socioeconomic Development, Demographic Dynamics and Forest Fires in Italy, 1961–2017: A Time-Series Analysis," Sustainability, MDPI, vol. 11(5), pages 1-17, March.
    7. Gervasio López-Rodríguez & Verónica Rodríguez-Vicente & Manuel F. Marey-Pérez, 2021. "Study of Forest Productivity in the Occurrence of Forest Fires in Galicia (Spain)," Sustainability, MDPI, vol. 13(15), pages 1-15, July.
    8. Chao Song & Mei-Po Kwan & Weiguo Song & Jiping Zhu, 2017. "A Comparison between Spatial Econometric Models and Random Forest for Modeling Fire Occurrence," Sustainability, MDPI, vol. 9(5), pages 1-21, May.
    9. Saeedeh Eskandari & Mahdis Amiri & Nitheshnirmal Sãdhasivam & Hamid Reza Pourghasemi, 2020. "Comparison of new individual and hybrid machine learning algorithms for modeling and mapping fire hazard: a supplementary analysis of fire hazard in different counties of Golestan Province in Iran," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 104(1), pages 305-327, October.
    10. Lasanta, Teodoro & Cortijos-López, Melani & Errea, M. Paz & Khorchani, Makki & Nadal-Romero, Estela, 2022. "An environmental management experience to control wildfires in the mid-mountain mediterranean area: Shrub clearing to generate mosaic landscapes," Land Use Policy, Elsevier, vol. 118(C).
    11. Canepa, Alessandra & Drogo, Federico, 2021. "Wildfire crime, apprehension and social vulnerability in Italy," Forest Policy and Economics, Elsevier, vol. 122(C).
    12. Canepa,Alessandra & Drogo,Federico, 2019. "Wildfire Crime and Social Vulnerability in Italy: A Panel Investigation," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202005, University of Turin.

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