As climate change continues to impact the environment, forest fires are becoming more common in arid regions. Defining the characteristics of a fire and how to understand this data is the focus of RouteScene, a lidar unmanned aerial systems (UAS) company, case study.
Understanding how fires impact the ecosystem will help predict fire risk and develop more precise and site-specific fire impact studies as well as create post-fire management plans and improve fire containment.
RouteScene used lidar captured from a drone and satellite optical imagery to assess the site of the Yeste fire in the province of Albacete, Spain.
While satellite optical imagery is being used more to examine the extend of forest fires, this technology cannot penetrate through the canopy down to the low-level vegetation and the ground below. However, lidar overcomes these limitations.
Drone-mounted lidar can:
- Fly over the study area at low altitude collecting data through many vegetation layers.
- Penetrate through the gaps in the foliage
- Create 3D point cloud displays of the canopy.
- Detect individual trees and generate a profile of the vegetation which can be viewed.
The flights were made an altitude of 40 m above ground and flown in parallel lines 40 m apart with an overlap of 50%.
Data collected from ground and non-ground points were classified into three clusters. The lidar drone mapping found that crown leaf area index (LAI), crown leaf area density (LAD), crown volume, tree height and tree height skewness were the most significant tree structure variables to distinguish the three close groups.
RouteScene said that few studies have used lidar-attached to drones to characterize crown damage after fires at the individual tree level. The team was able to distinguish crown fire from surface fire through changes in the LAI and understory and mid-story vegetation.
They found that unburned and low severity burned areas where more diverse in tree structures than moderate and high severity burned ones. This data was previously unavailable using satellite imagery.
The project demonstrated the potential to distinguish between post-fire plant structures in detail using UAS lidar data to estimate the impact of fire on single trees, not just whole forested areas.
“UAV LiDAR, with its level of detail, was the obvious next choice of technology and natural evolution to further examine the levels of damage to individual trees,” said Olga Viedma, professor at the University of Castilla-La Mancha in Spain. “I am delighted to say the Routescene UAV LiDAR system worked well and proved to be very useful. We have since carried out further studies on forest fires using the system in central Spain and the Canary Islands.”
The full research can be found in the journal Remote Sensing.