evacuation

As the realized experiences of wildfires threatening communities increase, the importance of proactive evacuation preparation and wildfire risk mitigation on private property to reduce the loss of lives and property is shaping wildfire policy and programs. To date, research has focused on pre-wildfire evacuation preparation and risk mitigation independently.

This research builds from existing scholarship to highlight the important role social complexity plays on managing and mitigating wildfire risk in the wildland-urban interface.

The increasing frequency and severity of wildfires due to climate change pose health risks to migrant farm workers laboring in wildfire-prone regions. This study focuses on Sonoma County, California, investigating the effectiveness of air monitoring and safety protections for farmworkers.

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: The Camp Fire burned through communities in Butte County, California, on 8 November 2018. The fire destroyed over 18 000 structures and caused 85 fatalities, mostly within the first 12 h of the incident. Aims: A post-fire case study was conducted to learn from the devastating incident.

Wildfire is an annual threat for many rural communities in the Pacific Northwest region of the United States. In some severe events, evacuation is one potential course of action to gain safety from an advancing wildfire.

Wildfires pose a serious threat to life in many countries. For police, fire and emergency services authorities in most jurisdictions in North America and Australia evacuation is now the option that is preferred overwhelmingly. Wildfire evacuation modeling can assist authorities in planning evacuation responses to future threats.

Escape routes are essential components of wildland firefighter safety, providing pre-defined pathways to a safety zone. Among the many factors that affect travel rates along an escape route, landscape conditions such as slope, low-lying vegetation density, and ground surface roughness are particularly influential, and can be measured using airborne light detection and ranging (LiDAR) data.