A Methodological Approach for Assessing the Resilience of <i>Pinus halepensis</i> Mill. Plant Communities Using UAV-LiDAR Data

Abstract

The assessment of fire effects in Aleppo pine forests is crucial for guiding the recovery of burned areas. This study presents a methodology using UAV-LiDAR data to quantify malleability in three burned areas (1970, 1995, 2008) through the statistical analysis of tree height and Profile Area Change (PAC) metrics. Significant differences in vegetation height (99th percentile) among the three fires, with specific maximum absolute differences (D) depending on the fire year, have been identified. Positive PAC values in 2008 indicate deeper LiDAR penetration, resulting in lower regeneration, while values close to 0 in 1970 suggest more uniform regeneration. The use of LiDAR metrics and uni-temporal sampling between burned sectors and controls aids in understanding community resilience and identifying recovery stages in P. halepensis forests.

Keywords

• forest fire
• malleability
• recovery
• vegetation structure
• drone
• Aleppo pine forests