The Contribution of Roads to Forest Fire Protection in Tamza Municipality, Northeast Algeria

By Vladimir CvetkovicNews

Authors

  • Faicel ToutTerritory Planning Research Center, Zouaghi Slimane Campus, Ain el Bey Road, 25000 Constantine, Algeria
  • Nouh RebouhTerritory Planning Research Center, Zouaghi Slimane Campus, Ain el Bey Road, 25000 Constantine, Algeria
  • Haythem DinarTerritory Planning Research Center, Zouaghi Slimane Campus, Ain el Bey Road, 25000 Constantine, Algeria
  • Yacine BenzidTerritory Planning Research Center, Zouaghi Slimane Campus, Ain el Bey Road, 25000 Constantine, Algeria
  • Zakaria ZouakTerritory Planning Research Center, Zouaghi Slimane Campus, Ain el Bey Road, 25000 Constantine, Algeria

DOI: 

https://doi.org/10.18485/ijdrm.2024.6.2.3

Keywords: 

disasters, forest fires, roads, protection, Tamza, Algeria

Abstract

With rising forest fire frequency due to climate change, countries are advancing measures for prevention and faster emergency response. In Algeria, efforts centre on improving access to at-risk forests by expanding forest roads and paths. This study focuses on Ain Mimoun, Tamza in Khenchela Province, examining the role of these routes in forest protection. Using Geographic Information Systems (Google Earth Engine and ArcGIS) alongside field surveys, it identifies areas impacted by the 2021 fires through the difference normalised burn ratio (dNBR) and assesses road proximity to affected zones. Using a cartographic approach, this study highlights road density in fire-hit areas, revealing several constraints limiting the roads’ effectiveness as fire barriers. Factors such as tree types and terrain influence fire spread, while fires near forest entrances impede firefighting vehicles due to risks from visibility and respiratory hazards. Maintenance issues further limit the utility of forest paths, and outdated forest road maps complicate firefighting efforts. Proposed solutions include upgrading the firefighting fleet with advanced tools like aircraft for isolated areas, intensifying forest road maintenance, and increasing forest monitors. Additionally, the study suggests exploring fire-resistant plant species, adopting strategic afforestation, and using Geographic Information Systems alongside advanced technologies like drones. These drones, which can provide real-time monitoring of fire and road conditions, support timely decision-making for rescue, evacuation and emergency response.

References

Akay, A. E., Podolskaia, E. S., & Uçar, Z. (2021). Effects of Improving Forest Road Standards on Shortening the Arrival Time of Ground-based Firefighting Teams Accessing to the Forest Fires. European Journal of Forest Engineering, 7(1), 32–38. https://doi.org/10.33904/ejfe.952174

Cvetković, V. (2019). Risk Perception of Building Fires in Belgrade. International Journal of Disaster Risk Management, 1(1), 81-91.

Guo, L., Wu, Z., Li, S., & Xie, G. (2024). The relative impacts of vegetation, topography and weather on landscape patterns of burn severity in subtropical forests of southern China. Journal of Environmental Management, 351(November 2023), 119733. https://doi.org/10.1016/j.jenvman.2023.119733

Guo, R., Yan, J., Zheng, H., & Wu, B. (2024). Assessment of the Analytic Burned Area Index for Forest Fire Severity Detection Using Sentinel and Landsat Data. Fire, 7(1). https://doi.org/10.3390/fire7010019

Gupta, P., Shukla, A. K., & Shukla, D. P. (2024). Sentinel 2 based burn severity mapping and assessing post-fire impacts on forests and buildings in the Mizoram, a north-eastern Himalayan region. Remote Sensing Applications: Society and Environment, 36(June), 101279. https://doi.org/10.1016/j.rsase.2024.101279

He, K., Shen, X., & Anagnostou, E. N. (2024). A global forest burn severity dataset from Landsat imagery (2003-2016). Earth System Science Data, 16(6), 3061–3081. https://doi.org/10.5194/essd-16-3061-2024

Ibrahim, S., Kose, M., Adamu, B., & Jega, I. M. (2024). Remote sensing for assessing the impact of forest fire severity on ecological and socio-economic activities in Kozan District, Turkey. Journal of Environmental Studies and Sciences. https://doi.org/10.1007/s13412-024-00951-z

Li, X., Zhang, G., Tan, S., Yang, Z., & Wu, X. (2023). Forest Fire Smoke Detection Research Based on the Random Forest Algorithm and Sub-Pixel Mapping Method. Forests, 14(3). https://doi.org/10.3390/f14030485

Llorens, R., Sobrino, J. A., Fernández, C., Fernández-Alonso, J. M., & Vega, J. A. (2021). A methodology to estimate forest fires burned areas and burn severity degrees using Sentinel-2 data. Application to the October 2017 fires in the Iberian Peninsula. International Journal of Applied Earth Observation and Geoinformation, 95 (January 2020). https://doi.org/10.1016/j.jag.2020.102243

Lourenço, M., Estima, D., Oliveira, H., Oliveira, L., & Mora, A. (2023). Automatic Rural Road Centerline Detection and Extraction from Aerial Images for a Forest Fire Decision Support System. Remote Sensing, 15(1). https://doi.org/10.3390/rs15010271

Lu, Z., Sun, S., Yuan, M., Yang, F., & Yin, H. (2022). Fire Path Fighting in Forest Off-Road Using Improved ACA—An Example of The Northern Primitive Forest Region of The Great Xing’an Range in Inner Mongolia, China. Forests, 13(10). https://doi.org/10.3390/f13101717

Belgherbi, B., Benabdeli, K., & Mostefai, K. (2018). Mapping the Risk of Forest Fires in Algeria : Application of the Forest of Guetarnia in Western Algeria. Sciendo, 37(3), 289–300. https://doi.org/10.2478/eko-2018-0022

Marra, A. B., Galo, M. de L. B. T., & Sano, E. E. (2024). Contribution of SAR/Sentinel-1 images in the detection of burnt areas in the natural vegetation of the Brazilian Pantanal biome. Boletim de Ciencias Geodesicas, 30, 0–1. https://doi.org/10.1590/s1982-21702024000100005

Meddour-Sahar, O., González-Cabán, A., Meddour, R., & Derridj, A. (2013). Wildfire management policies in Algeria: present and future needs. International Symposium on Fire Economics, Planning, and Policy: Climate Change and Wildfires, 92507, 382.

Mitsopoulos, I., Chrysafi, I., Bountis, D., & Mallinis, G. (2019). Assessment of factors driving high fire severity potential and classification in a Mediterranean pine ecosystem. Journal of Environmental Management, 235(May 2018), 266–275. https://doi.org/10.1016/j.jenvman.2019.01.056

Mohammad, L., Bandyopadhyay, J., Sk, R., Mondal, I., Nguyen, T. T., Lama, G. F. C., & Anh, D. T. (2023). Estimation of agricultural burned affected area using NDVI and dNBR satellite-based empirical models. Journal of Environmental Management, 343(April), 118226. https://doi.org/10.1016/j.jenvman.2023.118226.

Molnár, A. (2024). A Systematic Collaboration of Volunteer and Professional Fire Units in Hungary. International Journal of Disaster Risk Management, 6(1), 1–13.

Peña-Molina, E., Moya, D., Marino, E., Tomé, J. L., Fajardo-Cantos, Á., González-Romero, J., Lucas-Borja, M. E., & de las Heras, J. (2024). Fire Vulnerability, Resilience, and Recovery Rates of Mediterranean Pine Forests Using a 33-Year Time Series of Satellite Imagery. Remote Sensing, 16(10), 1–21. https://doi.org/10.3390/rs16101718

Singha, C., Swain, K. C., Moghimi, A., Foroughnia, F., & Swain, S. K. (2024). Integrating geospatial, remote sensing, and machine learning for climate-induced forest fire susceptibility mapping in Similipal Tiger Reserve, India. Forest Ecology and Management, 555(January), 121729. https://doi.org/10.1016/j.foreco.2024.121729

Sobrino, J. A., Llorens, R., Fernández, C., Fernández-Alonso, J. M., & Vega, J. A. (2019). Relationship between forest fire severity measured in situ and through remotely sensed spectral indices. Forests, 10(5), 1–13. https://doi.org/10.3390/f10050457

Suárez-Fernández, G. E., Martínez-Sánchez, J., Arias, P., & Lorenzo, H. (2024). Characterizing Forest Fires Risks Using Free Multi-Source Data: Identifying High-Risk Road Sections. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences – ISPRS Archives, 48(4/W11-2024), 121–128. https://doi.org/10.5194/isprs-archives-XLVIII-4-W11-2024-121-2024

Tout, F. (2023). MODEL NA PREDPOVEDAN IE OBLASTÍ VÝSKYTU A MODEL TO PREDICT THE OUTBREAK. Geografická Revue, 19(1). https://doi.org/10.24040/GR.2023.19.1.62-75

Wu, Y., Lin, K., Li, W. H., Xiang, T., Zhang, Y., Yang, Y., Chen, Y., & Zhou, R. (2023). Forest fire emergency rescue and evacuation path planning based on improved APF. EM-GIS 2023 – Proceedings of the 8th ACM SIGSPATIAL International Workshop on Security Response Using GIS 2023, 1–6. https://doi.org/10.1145/3615884.3629421

Delcourt, C. J. F., Combee, A., Izbicki, B., Mack, M. C., Maximov, T., Petrov, R., Rogers, B. M., Scholten, R. C., Shestakova, T. A., van Wees, D., & Veraverbeke, S. (2021). Evaluating the differenced normalized burn ratio for assessing fire severity using sentinel-2 imagery in northeast siberian larch forests. Remote Sensing, 13(12), 1–20. https://doi.org/10.3390/rs13122311

30. Zahira, S., & Hadj, B. (2017). L’algerie: Une Region Mediterraneene Tres Sensible Aux Incendies De Foret. Territorium, 24(I), 177–186.

Zhu, Y., Zhang, G., Chu, R., Xiao, H., Yang, Y., & Wu, X. (2024). Research on escape route planning analysis in forest fire scenes based on the improved A* algorithm. Ecological Indicators, 166(July), 112355. https://doi.org/10.1016/j.ecolind.2024.112355.

Eker, R., Çınar, T., Baysal, İ., & Aydın, A. (2024). Remote sensing and GIS-based inventory and analysis of the unprecedented 2021 forest fires in Türkiye’s history. Natural Hazards, 0123456789. https://doi.org/10.1007/s11069-024-06622-0

Erzurumlu, G. S., & Yıldız, N. E. (2024). Determination of fire intensity after forest fire by remote sensing: marmaris case study. BIO Web of Conferences, 85, 0–5. https://doi.org/10.1051/bioconf/20248501041

Fernández-García, V., Fulé, P. Z., Marcos, E., & Calvo, L. (2019). The role of fire frequency and severity on the regeneration of Mediterranean serotinous pines under different environmental conditions. Forest Ecology and Management, 444(March), 59–68. https://doi.org/10.1016/j.foreco.2019.04.040

Ganteaume, A., & Jappiot, M. (2013). What Causes Large Fires in Southern France. Forest Ecology and Management, 294, 76–85. https://doi.org/10.1016/j.foreco.2012.06.055

Guehaz, R., & Sivakumar, V. (2023). A case study about the forest fire occurred on 05 July 2021 over Khenchela province, Algeria, using space-borne remote sensing. December, 1–14. https://doi.org/10.3389/frsen.2023.1289963

Guo, L., Li, S., Wu, Z., Parsons, R. A., Lin, S., Wu, B., & Sun, L. (2022). Assessing spatial patterns and drivers of burn severity in subtropical forests in Southern China based on Landsat 8. Forest Ecology and Management, 524(September). https://doi.org/10.1016/j.foreco.2022.120515

Downloads

Published

2024-12-25

How to Cite

Tout, F., Rebouh, N. ., Dinar, H. . ., Benzid, Y. . ., & Zouak, Z. (2024). The Contribution of Roads to Forest Fire Protection in Tamza Municipality, Northeast Algeria. International Journal of Disaster Risk Management, 6(2), 39–50. https://doi.org/10.18485/ijdrm.2024.6.2.3More Citation Formats

Issue

Vol. 6 No. 2 (2024): International Journal of Disaster Risk Management (IJDRM)

Section

Articles

License

Copyright (c) 2024 International Journal of Disaster Risk Management

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

International Journal of Disaster Risk Management (IJDRM) allows authors to deposit publisher’s version/PDF in an institutional repository, research gate, Academia.edu, and non-commercial subject-based repositories, or to publish it on Author’s personal website (including social networking sites) and/or departmental website, at any time after publication in compliance with the Creative Commons Attribution-NonCommercial – NoDerrivatives 4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/). The Publisher’s copyright and source must be acknowledged and a link must be made to the article’s DOI (HTML link).

Most read articles by the same author(s)

Similar Articles

You may also start an advanced similarity search for this article.

Leave a Reply

Your email address will not be published. Required fields are marked *