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Wildfire risk for global wildland–urban interface areas

Nature Sustainability volume 7, pages 474–484 (2024)Cite this article

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Abstract

Intensifying wildfires and human settlement expansion have placed more people and infrastructure at the wildland–urban interface (WUI) areas under risk. Effective wildfire management and policy response are needed to protect ecosystems and residential communities; however, maps containing spatially and temporally explicit information on the distribution of WUI areas are limited to certain countries or local regions, and global WUI patterns and associated wildfire exposure risk therefore remain unclear. Here we generated the global WUI data layers for the 2020 baseline and the 1985–2020 time series by integrating fine-resolution housing and vegetation mapping. We estimated the total global WUI area to be 6.62 million km2. Time-series analysis revealed that global WUI areas increased by 12.56% between 1985 and 2020. By overlapping 2001–2020 wildfire burned area maps and fine-resolution population datasets, our analysis uncovered that globally, 7.07% (12.54%) of WUI areas housing 4.47 million (10.11 million) people are within a 2,400 m (4,800 m) buffer zone of wildfire threat. Regionally, we found that the United States, Brazil, China, India and Australia account for the majority of WUI areas, but African countries experience higher wildfire risk. Our quantification of global WUI spatiotemporal patterns and the associated wildfire risk could support improvement of wildfire management.

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Fig. 1: Global distribution of WUIs.
Fig. 2: Global WUI area at the country and state levels.
Fig. 3: Spatiotemporal changes in global WUI areas.
Fig. 4: Temporal changes in global WUI areas.
Fig. 5: WUI areas within wildfire threat areas.

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Data availability

The global hierarchy of administrative unit layers are from the Food and Agriculture Organization of the United Nations (https://data.apps.fao.org). The population dataset is from WorldPop (https://www.worldpop.org). The global baseline land-cover product for 2020 (WorldCover) is from the European Space Agency (https://esa-worldcover.org). The Meta (formerly Facebook) HRPD maps are from the Data for Good platform (https://dataforgood.facebook.com/dfg/tools/high-resolution-population-density-maps). The WSF maps are from the Scientific Data repository (https://www.nature.com/articles/s41597-020-00580-5). The wildfire burned area datasets are from the MODIS data archive in Google Earth Engine (https://earthengine.google.com). The global urban area boundaries are from the FROM-GLC research group (https://data-starcloud.pcl.ac.cn/). The global industrial and smallholder oil palm map is from Zenodo (https://zenodo.org/record/4473715). WUI data in the United States for validation are from the SILVIS lab (http://silvis.forest.wisc.edu/data/wui-change). The 30 m GLC-FCS product is from Zenodo (https://zenodo.org/record/3986872). The 100 m global human settlement layers are from the Joint Research Centre of the European Commission (https://ghsl.jrc.ec.europa.eu/ghs_buS2023.php). The global WUI datasets for the 2020 baseline and 1985–2020 time series have been deposited in the following repository: https://datahub.hku.hk/projects/GlobalWUI/191163.

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Acknowledgements

This work was supported by the National Key Research and Development Program of China (grant no. 2022YFB3903703 to B.C. and B.X.), the University of Hong Kong HKU-100 Scholars Fund (to B.C.), the Research Grants Council of Hong Kong Early Career Scheme (grant no. HKU27600222 to B.C.) and General Research Fund (grant no. HKU17601423 to B.C.), University Research Committee Seed Funding for Strategic Interdisciplinary Research Scheme (to B.C.), the National Natural Science Foundation of China/RGC Joint Research Scheme (grant no. N_HKU722/23 to B.C. and S.W.), the Faculty of Business and Economics and Shenzhen Research Institutes (grant no. SZRI2023-CRF-04 to B.C.), the Croucher Foundation (grant no. CAS22902/CAS22HU01 to P.G.), the International Research Center of Big Data for Sustainable Development Goals (grant nos CBAS2022GSP04 to P.G. and CBAS2022ORP02 to B.X.) and the Major Program of the National Natural Science Foundation of China (grant no. 42090015 to P.G.). S.V. acknowledges support from the Russian State Assignment of the Federal Research Centre, Southern Scientific Centre of the Russian Academy of Sciences (grant no. 122013100131-9).

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Authors and Affiliations

  1. Future Urbanity & Sustainable Environment (FUSE) Lab, Division of Landscape Architecture, Department of Architecture, Faculty of Architecture, The University of Hong Kong, Hong Kong SAR, China

    Bin Chen & Shengbiao Wu

  2. Urban Systems Institute and Institute for Climate and Carbon Neutrality, The University of Hong Kong, Hong Kong SAR, China

    Bin Chen, Chris Webster & Peng Gong

  3. Musketeers Foundation Institute of Data Science, The University of Hong Kong, Hong Kong SAR, China

    Bin Chen & Chris Webster

  4. Department of Land, Air and Water Resources, University of California, Davis, Davis, CA, USA

    Yufang Jin

  5. School of the Environment, Yale University, New Haven, CT, USA

    Yimeng Song

  6. Wilkes Center for Climate Science and Policy, University of Utah, Salt Lake City, UT, USA

    Chao Wu

  7. School of Biological Sciences, University of Utah, Salt Lake City, UT, USA

    Chao Wu

  8. Department of Earth System Science, Ministry of Education Ecological Field Station for East Asian Migratory Birds, and Institute for Global Change Studies, Tsinghua University, Beijing, China

    Sergey Venevsky & Bing Xu

  9. Southern Scientific Centre of RAS, Rostov-on-Don, Russia

    Sergey Venevsky

  10. HKUrbanLabs, Faculty of Architecture, The University of Hong Kong, Hong Kong SAR, China

    Chris Webster

  11. Department of Geography and Department of Earth Sciences, The University of Hong Kong, Hong Kong SAR, China

    Peng Gong

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Contributions

B.C. conceived the research idea, designed the study, performed the main data analysis and wrote the manuscript. S.W. contributed to data collection. S.W., Y.J., Y.S., C. Wu, S.V., B.X., C. Webster and P.G. contributed to result interpretation and reviewed and edited the manuscript.

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Correspondence to Bin Chen.

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Nature Sustainability thanks Antonio Bento-Gonçalves, Hong S. He and Jiafu Mao for their contribution to the peer review of this work.

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Chen, B., Wu, S., Jin, Y. et al. Wildfire risk for global wildland–urban interface areas. Nat Sustain 7, 474–484 (2024). https://doi.org/10.1038/s41893-024-01291-0

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