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Modelling spatiotemporal patterns of wildfire risk in the Garden Route District biodiversity hotspots using analytic hierarchy process in South Africa

Author

Listed:
  • Phindile Siyasanga Shinga

    (University of Fort Hare
    Université Côte d’Azur)

  • Solomon G. Tesfamichael

    (University of Johannesburg)

  • Phila Sibandze

    (Université Côte d’Azur)

  • Ahmed Mukalazi Kalumba

    (University of Fort Hare
    University of Fort Hare)

  • Gbenga Abayomi Afuye

    (University of Fort Hare
    University of Fort Hare)

Abstract

The increasing frequency and intensity of wildfires necessitate effective risk management in biodiversity hotspots to mitigate the potential impacts of wildfire hazards. The study utilised a multi-criteria decision analysis-analytic hierarchy process (MCDA-AHP) model to analyse wildfire risk patterns in the Garden Route District (GRD), focusing on biodiversity hotspots in the Western Cape, South Africa. The study used weight assignment and overlay analysis to evaluate wildfire risk factors, including human, topographic, and climatic factors, using data from Landsat and WorldClim from 1991 to 2021. The wildfire risk model was validated using MODIS historical fire data from the Global Forest Watch database and Confusion Matrix, with the burned area extent identified using differenced Normalized Burn Ratio (dNBR). The results show that despite 53% of the most burned area, only 12% was burned, with the high-risk zone accounting for only 11%, indicating a higher likelihood of wildfires spreading and intensifying. The results reveal a weak positive correlation (r = 0.28) between historical fire occurrences and burned areas and a negative correlation (r = − 0.27) between historical fire occurrences and fire seasons. Human and climatic factors significantly impact wildfire propagation in high-risk zones, while topographic factors have less influence, indicating a lower risk of ignition. The findings show that 26% of high-risk zones in the southwestern region dominated GRD biodiversity hotspots, while 27% were in the low-moderate-risk zone in the northwestern parts. The results of this study can aid in assigning fire risk-based criterion weights to support decision-makers in regional and global wildfire prevention and management.

Suggested Citation

  • Phindile Siyasanga Shinga & Solomon G. Tesfamichael & Phila Sibandze & Ahmed Mukalazi Kalumba & Gbenga Abayomi Afuye, 2025. "Modelling spatiotemporal patterns of wildfire risk in the Garden Route District biodiversity hotspots using analytic hierarchy process in South Africa," 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. 121(2), pages 1945-1969, January.
    • Handle: RePEc:spr:nathaz:v:121:y:2025:i:2:d:10.1007_s11069-024-06877-7
    DOI: 10.1007/s11069-024-06877-7
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    References listed on IDEAS

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    1. Michael Nones & Hossein Hamidifar & Seyed Mohammad Bagher Shahabi-Haghighi, 2024. "Exploring EM-DAT for depicting spatiotemporal trends of drought and wildfires and their connections with anthropogenic pressure," 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. 120(1), pages 957-973, January.
    2. Kinley Tshering & Phuntsho Thinley & Mahyat Shafapour Tehrany & Ugyen Thinley & Farzin Shabani, 2020. "A Comparison of the Qualitative Analytic Hierarchy Process and the Quantitative Frequency Ratio Techniques in Predicting Forest Fire-Prone Areas in Bhutan Using GIS," Forecasting, MDPI, vol. 2(2), pages 1-23, March.
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