Global Wildland-Urban Interface

Fire risks that threaten the planet's wildlands and civilizations do not threaten every place equally. The [SILVIS lab] at University of Wisconsin-Madison used a global approach to identify wildland and human assets which by their spatial arrangement have an elevated risk of fire. The Global Wildland-Urban Interface layer can be used to evenhandedly assess risk to a company's assets or other global operations using a single global map. The Wildland-Urban Interface (WUI) is the area where urban development occurs near wildland vegetation. SILVIS Lab generated this global WUI map using a globally consistent method based on remote sensing-derived built-up area and wildland vegetation datasets. SILVIS lab used the European Space Agency (ESA) [WorldCover 2020] as their wildland vegetation dataset. For built-up areas, SILVIS lab used the European Commission, Joint Research Centre’s (JRC) [GHS built-up surface grid], derived from Sentinel2 composite and Landsat, multitemporal (1975-2030). For more information about sources and methodology, please see the SILVIS lab [Global WUI project page]. Intermix vs Interface The two types or intensities of WUI classified in this map are intermix and interface. Intermix WUI is where buildings and wildland vegetation intermingle. Interface WUI is where buildings approach large patches of wildland vegetation. Intermix WUI has more than 6.17 buildings per km² (or one building per 40 acres) and a wildland vegetation area of greater than or equal to 50%. Interface WUI is where buildings are close to large wildland vegetation patches. These are areas with more than 6.17 buildings per km² but less than 50% wildland vegetation that lie in proximity (less than 2400m) of a large patch (at least 5 km²) of wildland vegetation (with a share of more than 75%). The minimum patch size excludes small urban parks from wildland vegetation. The minimum distance of 2400m (1.5 miles) is included in the US Federal Register definition and represents the distance embers can fly during a wildfire. This map is designed so that areas of WUI intermix and interface show up in a brighter color against shades of cool, dull green in the background. Here are the principles that went into the design for the layer: * Focus on the WUI first. * Don't make the layer look threatening or scary. * Use intuitive earth tones. * Imply a hierarchy with the set of oranges being the forested/shrubs/more risk; yellow next as grasslands; and desaturated/less emphasis greens for the Non-WUI. Urban areas are a cement brown gray. * Make sure the palette is suited for color vision deficiency. * Ensure that it works well with multiply blend mode and terrain. Classes in this layer The mapping algorithm utilized definitions of the WUI from the [U.S. Federal Register (USDA & USDI, 2001)] operationalized in [Radeloff et al. (2005)]. According to these definitions, the following classes of WUI were derived: 0. Inland Water - May include coastal ocean and estuary (transparent by default) 1. Forest/Shrubland/Wetland-dominated Intermix WUI 2. Forest/Shrubland/Wetland-dominated Interface WUI 3. Grassland-dominated Intermix WUI 4. Grassland-dominated Interface WUI 5. Forest/Shrubland/Wetland-dominated Wildland non-WUI 6. Grassland-dominated Wildland non-WUI 7. Urban Non-wildland non-WUI 8. Other Non-wildland non-WUI Dataset summary Variable Mapped: WUI class Data Projection: [Equi7] (six Lambert Azimuthal projections, one for each continent) Service Projection: Equal Earth Extent: Global (except Antarctica and far northern Greenland) Cell Size: 10m Source Type: Thematic Data Source: [SILVIS Lab University of Wisconsin-Madison] Global Map Covers the Year: 2020 Data Publication Date: 2023 What can you do with this layer? This layer can be used in analysis to estimate and compare vulnerability of structures to wildfire worldwide based on their proximity to wildland vegetation. This layer can be used to identify and scrutinize areas of habitat fragmentation and loss due to continuous human presence and activity. This layer can be used to identify areas of possible contact with zoonotic diseases. This layer can be used to identify places where predation by human companions such as cats and dogs affect wildlife populations. Data Citation Schug, F., et al. Map of the Global Wildland-urban Interface. 1.1, Zenodo, 1 Apr. 2023, [doi:10.5281/zenodo.7941460]. Paper Citation Schug, F., Bar-Massada, A., Carlson, A.R. et al. The global wildland–urban interface. Nature 621, 94–99 (2023). [https://doi.org/10.1038/s41586-023-06320-0].