# Using Drones to Estimate and Reduce the Risk of Wildfire Propagation in Wildland-Urban Interfaces
## 1 Introduction  
### Context  
Forest fires have become one of the most destructive natural disasters worldwide, causing catastrophic losses [1, 2]. In 2017, rural wildfires in Portugal destroyed a large area of forest and farmland and caused the death of 114 people. In the aftermath of this event, the Portuguese government launched an enquiry to determine the relevant factors that led to this disaster. The experts designated for this task concluded that one of the main factors was the high density and continuity of vegetation in urban-forest and road-forest interfaces. Figure 1 shows a site where the density of trees near a road contributed to several casualties.  
As a result, a new law was created (law 10/2018) [3], which aims to control the density of plant biomass near population centres, buildings, and roads in rural areas. It specifies buffer zones with minimum distances between tree canopies, minimum distances between tree canopies and buildings, and maximum density of the shrub layer near buildings. Figure 2 illustrates the main buffer zones around buildings.  
There are two major mandatory buffer zones: a 10-m buffer zone (A) adjacent to buildings and an additional 40-m buffer zone (B) to the unmanaged wildland, meaning that there must be at least a 50-m zone around buildings where the vegetation and trees must be managed. In zone A, there are two sub-zones with different requirements: in the first 5 m, no trees or shrubs are allowed, but in the following 5 m, small trees and shrubs are allowed, provided they are low-flammable species, are watered, and do not establish horizontal or vertical fuel continuity. In zone B, isolated trees are allowed if their crowns are separated by at least 4 m. However, pine and eucalyptus are considered more dangerous than other species, and the minimum distance between their crowns is 10 m.  
For roads and railways, the rules are simpler: there must be a single 10-m buffer zone between the road and the wildland with mandatory fuel management, as can be seen in Figure 3.  
Figure 1: Density of trees surrounding the road where several people perished.  
Figure 2: Buffer zones around buildings where fuel management is mandatory.  
Currently, the public authorities responsible for enforcing this law face serious challenges, because they rely solely on direct observations and manual measurements but lack the human resources needed to assess the huge area of wildland-urban/road interfaces that exist in Portugal. There is therefore an opportunity to use technology to automate and simplify the task of verifying compliance with this law, using aerial images, artificial intelligence, and web-based mapping frameworks.  
Unmanned aerial vehicles (UAVs), commonly known as drones, have emerged as important tools for tackling various aspects of forest fire science, from prevention to detection [4]. Currently, drones present several advantages when compared with traditional remote sensing platforms, such as satellites and manned aircraft, and both LiDAR and photogrammetry techniques are feasible solutions for measuring and monitoring aspects of complex forest structures [5].  
The EU Horizon CHAMELEON Project [6], developed by a consortium of twelve partner organisations distributed in nine European countries, aims to optimise production and identify potential problems in agriculture, livestock, forestry, and rural areas, using drones and software bundles for specific purposes. This study aims to explore the use of drones and some of the CHAMELON bundles to verify compliance with mandatory fuel management in buffer zones, helping to reduce the risk of forest fires spreading near buildings and roads. This is important because it can leverage the automation of compliance checks and allow a massive expansion of fire prevention operations in wildland-urban interfaces.