Evaluating the Combined Use of the NDVI and High-Density Lidar Data to Assess the Natural Regeneration of P. pinaster after a High-Severity Fire in NW Spain

Abstract

Pinus pinaster Ait. is an important timber species in NW Spain and is affected by forest fires every year. The persistence of this species after fire mainly depends on natural regeneration, which is very variable. In this study, we evaluated the combined use of the NDVI and LiDAR data for assessing P. pinaster regeneration success after fire in terms of density, cover and height. For this purpose, we selected a P. pinaster stand affected by a high-severity wildfire in October 2017. Field surveys and remotely piloted aircraft flights (with a high-density LiDAR sensor and multispectral camera) were conducted four years after the fire (October 2021). The study area is characterized as being particularly complex terrain, with a combination of pine trees and a high density of scrub and low vegetation. Field measurements were made in 16 study plots distributed over the burned area. Two different types of software and data processing methods were used to calculate the LiDAR-derived metrics. For pine variables, the LiDAR-based estimates of structural characteristics calculated with both data processing methods proved inadequate and were very poorly correlated with the field-measured data, while for shrubland the estimates proved to be more comparable to the field measurements. The inability of the laser pulses to reach the ground due to the complexity of the area/vegetation could lead to loss of information, calling into question the accuracy of LiDAR data in this type of scenario. LiDAR technology continues to expand in different areas and applications, and in forestry, future studies should focus on application in more complex terrain.