Mapping Natural Regeneration in Canopy Gaps from Seedlings to Saplings in Uneven-Aged Deciduous Forests using ALS Data

Introduction :
Assessing regeneration state is essential for forests sustainable management. However, field surveys to collect data on regeneration are time consuming and difficult to implement. Remote sensing could therefore be an effective way to characterize regeneration. Only few studies focused on forest regeneration characterisation using ALS data: understory coverage estimation (Latifi et al. 2017, Venier et al. 2019), post-fire vegetation characterization (Martin- Alcon et al. 2015), regeneration stems density and height estimation (Debouk et al. 2013, Imangholiloo et al. 2020). Regeneration dynamic depends on the characteristics of canopy gaps. They increase availability of understory light, which is beneficial for regeneration development, especially for less shade-tolerant species (Ligot et al. 2014). Moreover, the regeneration that develops within canopy gaps is not overtopped by dominant trees and is therefore favourable to the production of high value wood. Some studies focus on the identification of understory types in canopy gaps (Vehmas et al. 2011). Another method was developed to distinct non-regenerating gaps from regenerated ones (Sénécal et al. 2018). The height growth of regeneration saplings within canopy gaps was also estimated using ALS time series (Vepakomma et al. 2008). Using ALS data, the study’s objectives were (i) to detect and map canopy gaps, (ii) to characterize and delineate four regeneration development stages within these canopy gaps and (iii) to differentiate ligneous stems from herbaceous and soil for the first development stage (height < 1.5 m).