Potential of terrestrial laser scanning for characterizing forest regeneration: A review and an experimental case study

Forest regeneration monitoring is essential for evaluating ecosystem recovery and informing sustainable forest management. Optical remote sensing methods such as NDVI and EVI are commonly used for this purpose, but they often fail to capture fine-scale structural information, particularly in early successional stages. Terrestrial Laser Scanning (TLS), in contrast, offers high-resolution, three-dimensional data capable of directly detecting tree structure, height distribution, and leaf area index (LAI). This study combines a systematic literature review with original TLS data collected from a regenerating forest plot affected by windstorm disturbance, where multispectral imagery was also acquired. The review highlights the advantages of TLS over optical techniques, particularly in detecting understory vegetation and capturing structural complexity. The experimental results support these findings: TLS enabled the accurate detection of tree saplings that were not visible in optical imagery and allowed for the extraction of height distributions and LAI. These results demonstrate that even single TLS acquisition can provide critical structural insights into forest regeneration that optical methods alone cannot deliver. We conclude that TLS is a valuable tool for monitoring post-disturbance recovery and advocates for its integration with optical remote sensing approaches such as NDVI and EVI to achieve a more comprehensive assessment of forest regeneration.

Forests naturally regrow after damage from storms or other events, but tracking this recovery is challenging, especially when trees are still small or hidden beneath larger plants. This study looked at how a technology called terrestrial laser scanning (TLS) can help. TLS uses ground-based lasers to create very detailed 3D maps of forest structure, capturing features like tree height, density, and leaf coverage. We reviewed recent research and also tested TLS in a forest in northern Italy damaged by a severe windstorm in 2018. The laser data were compared with satellite images that measure vegetation health through “greenness” indices like NDVI and EVI. TLS revealed small trees and undergrowth that the satellites could not detect, while the satellite images provided broader seasonal and yearly trends in plant growth. Our results show that using TLS alongside satellite data gives a fuller picture of forest recovery. This combined approach can help forest managers and conservationists make better decisions about post-storm recovery and long-term forest health.