Wildland-urban interface (WUI)

Wildfire is increasing in frequency, extent, and severity in many parts of the USA. Considering the unequal burden of natural hazards on socially vulnerable populations, we ask here, how are characteristics of social vulnerability associated with wildfire occurrence nationwide, at different scales and across differing levels of wildland–urban interface development?

Wildfire risk is increasing all over the world, particularly in the western United States and the communities in wildland-urban interface (WUI) areas are at the greatest risk of fire.

Background: Wildland–urban interface (WUI) maps identify areas with wildfire risk, but they are often outdated owing to the lack of building data. Convolutional neural networks (CNNs) can extract building locations from remote sensing data, but their accuracy in WUI areas is unknown.

As wildfires increase in both severity and frequency, understanding the role of risk saliency on human behaviors in the face of fire risks becomes paramount. While research has shown that homebuyers capitalize wildfire risk following a fire, studies of the role that risk saliency plays on residential development is limited.

We integrated a mechanistic wildfire simulation system with an agent-based landscape change model to investigate the feedbacks among climate change, population growth, development, landowner decision-making, vegetative succession, and wildfire.

Due to the associated fire risk, the wildland–urban interface (WUI) has drawn the attention of researchers and managers from a range of backgrounds. From a land management point of view, it is important to identify the WUI to determine areas to prioritise for fire risk prevention.