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Detection Of Fire-Prone Areas In Attica Region Integrating Urban And Transport Aspect

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In Mediterranean climate areas, wildfires are one of the most critical problems bringing about several negative impacts (loss of human life, infrastructure damages, landscape transformation, natural environment deterioration, etc.). Fires pose great dangers not only for rural areas, but also for suburban or even urban areas. The aim of the research is to detect areas vulnerable to wildfire in Attica Region and then to examine the critical factors affecting the risk degree in macro and microscale. In the first step we examine the wider study area, which is close to vulnerable areas in a zone at least 1km wide. This examination includes the factor of vegetation along with other factors such as road network, aspect, slope etc, aiming to detect the exact area vulnerable to fire. The second step focuses on a vulnerable study area individually, for identifying and measuring the factors that affect the risk degree in microscale. The most notable factors are: a) population density, b) connectivity of the road network, c) geometric features of the streets, c) location of fire stations and police departments, d) existence of open spaces, e) parking conditions and f ) existence of vulnerable facilities. The wider study area (macroscale) is the Regional Unit of Eastern Attica and the main study area (microscale) is the settlement of Saronida. The findings indicate that several rural and peri-urban areas inEastern Atticaare vulnerable to wildfire. Particularly, crucial issues regarding microscale are the low roadway width values and the inadequate connectivity of the network structure.

About the Authors

Efthymia Kourmpa
National Technical University of Athens
Iroon Politechneiou 9, 15780 Zographos

Stefanos Tsigdinos
National Technical University of Athens
Iroon Politechneiou 9, 15780 Zographos


1. Adab H., Kanniah K. and Solaimani K. (2011). GIS-based Probability Assessment of Fire Risk in Grassland and Forested Landscapes of Golestan Province. IPCBEE, 19.

2. Badia A., Serra P. and Modugno S. (2011). Identifying dynamics of fire ignition probabilities in two representative Mediterranean wildland- urban interface areas. Applied Geography, 31(3), 930-940.

3. Brueckner J. (2000). Urban Sprawl: Diagnosis and Remedies. International Regional Science Review, 23(2), 160-171.

4. Caceres C.F. (2011). Using GIS in Hotspots Analysis and for Forest Fire Fisk Zones Mapping in the Yeguare Region, Southeastern Honduras, Papers in Resource Analysis. Saint Mary’s University of Minnesota University Central Services Press. Winona, MN, 13, 14.

5. Carroll M., Blatner K., Cohn P. and Morgan T. (2007). Managing fire danger in the forests of the US inland northwest: a classic «wicked problem» in Public Land Policy. Journal of Forestry, 105, 239-244.

6. Crippen R.E. (1990). Calculating the vegetation index faster. Remote sensing of Environment, 34(1), 71-73.

7. Darques R. (2015). Mediterranean cities under fire. A critical approach to the wildland-urban interface. Applied Geography, 59, 20-21.

8. Diakakis M., Xanthopoulos G. and Gregos L. (2016). Analysis of forest fire fatalities in Greece: 1977–2013. International Journal of Wildland Fire, 25, 797-809.

9. Dong X., Li Y., Pan Y., Huang Y. and Cheng X. (2018). Study on Urban Fire Station Planning based on Fire Risk Assessment and GIS Technology, 8th International Conference on Fire Science and Fire Protection Engineering (on the Development of Performance-based Fire Code), 211, 124-130.

10. Fried J.S., Winter G.J. and Gilless J.K. (1999). Assessing the benefits of reducing fire risk in the wildland-urban interface: A contingent valuation approach. International Journal of Wildland Fire, 9, 9-20.

11. Gerdzheva A. (2014). A comparative analysis of different wildfire risk assessment models (A case study for Smolyan district, Bulgaria). European Journal of Geography, 5(3), 22-36.

12. Hernandez-Leal P.A., Arbelo M. and Gonzalez-Calvo A. (2006). Fire Risk assessment using satellite data, Advances in Space research, 37(4), 741-746.

13. Jaiswal R.K, Mukherjee S., Raju K.D, Saxena R. (2002). Forest Fire Risk Zone Mapping through Satellite Imagery & Geographical Information System. International Journal of Applied Earth Observation and Geoinformation, Elsevier Publications, 4(1), 10.

14. Karmas A., Karantzalos K. and Athanasiou S. (2014). Online analysis of remote sensing data for agricultural applications. Proceedings of OSGeo’s European Conference on Free and Open Source Software for Geospatial, Bermen, Germany.

15. Kourmpa E., Markou I., Mouratidou E., Tsafourou N. and Filippa E. (2019). Vulnerable settlements to fire: Forecasting and Protection, Interdisciplinary Program of Postgraduate Studies «Environment and Development», National Technical University of Athens (In Greek).

16. Lampin-Maillet C., Jappiot M., Long, M., Morge D. and Ferrier J.P. (2009). Characterization and Mapping of Dwelling Types for Forest Fire Prevention. Computers, Environment and Urban Systems, 33, 224-232.

17. Martinez J., Vega-García C. and Chuvieco E. (2009). Human-caused wildfire risk rating for prevention planning in Spain. Journal of Environmental Management, 90, 1241-1252.

18. McDonald T., Walker B. (2007). Resilience Thinking: Interview with Brian Walker. Ecological Management and Restoration, 8 (2), 85–91.

19. Montz B., Tobin G. and Hagelman R. (2017). Natural Hazards. Explanation and Integration. 2nd ed. The Guilford Press, New York.

20. Neil Adger W. (2006). Vulnerability. Global Environmental Change, 16 (3), 268-281.

21. Newman P., Beatley T. and Boyer H. (2017). Resilient Cities. Island Press, Washington.

22. Noon, E.K. (2003). A Coupled Model Approach for Assessing Fire Hazard at Point Reyes National Seashore: Flam Map and GIS, Proceedings of the 2nd International Wildland Fire Ecology and Fire Management Congress, Springs Resort.

23. Radeloff V.C., Hammer R., Stewart S.I., Fried J.S., Holcomb S.S. and Mckeefry J.F. (2005). The wildland urban interface in the United States. Ecological Applications, 15(3), 799-805.

24. Radke J. (1995). Modeling urban/wildland interface fire hazards within a geographic information system, Geographic Information Sciences, 1(1), 9-21.

25. Ramirez J., Monedero S. and Buckley D. (2011). New approaches in fire simulations analysis with Wildfire Analyst. The 5th International Wildland Fire Conference. Sun City, South Africa.

26. Reggiani A., Nijkamp P. and Lanzi D. (2015). Transport resilience and vulnerability: The role of connectivity. Transportation Research Part A: Policy and Practice, 81, 4-15.

27. Rothermel R.C. (1983). How to predict the spread and intensity of forest and range fires. Gen. Tech. Rep. INT-143. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station, 161

28. Siachalou S., Doxani, G. and Tsakiri-Strati M. (2009). Integrating Remote Sensing Processing and GIS to Fire Risk Zone Mapping: A case study for the Seih-Sou Forest of Thessaloniki. Proceedings of the 24th International Cartographic Conference (ICC)

29. Stefanovic B., Stojnic D. and Danilovic M. (2015). Multi-criteria forest road network planning in fire-prone environment: a case study in Serbia. Journal of Environmental Planning and Management, 59(5), 911-926.

30. Viegas D.X., Ribeiro L.M., Viegas M.T., Pita P. and Rossa C. (2009). Impacts of fire on society: extreme fire propagation issues. In E. Chuvieco (Ed.), Earth observation of wildland fires in Mediterranean ecosystems, 97-109.

31. Williams C., Hanan N., Neff J., Scholes R., Berry J., Denning A. and Baker D. (2007). Africa and the global carbon cycle. Carbon Balance and Management BioMed Central, 2, 1-13.

For citation:

Kourmpa E., Tsigdinos S. Detection Of Fire-Prone Areas In Attica Region Integrating Urban And Transport Aspect. GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY. 2020;13(3):84-89.

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ISSN 2071-9388 (Print)
ISSN 2542-1565 (Online)