A LiDAR-based framework for visualizing and quantifying forest void space: an intrinsic component of forest ecosystems

Abstract

Forest voids—three-dimensional (3D), unoccupied spaces within forest ecosystems—form a critical yet under-described component of stand structure. Shaped by vegetation, microclimate, and disturbance regimes, these voids govern light penetration, airflow, and habitat connectivity. We propose a LiDAR-based framework that identifies, visualizes, and quantifies forest voids directly from terrestrial and mobile laser-scanning (TLS/MLS) point clouds. By treating voids as the 3D regions between the digital elevation model (DEM) or digital surface model (DSM) where no returns are detected, our method bypasses canopy-centric metrics and simplified radiative assumptions, yielding a scalable, assumption-light representation of forest architecture. Across sites, void configurations reflect underlying stand architecture. Forests with high structural heterogeneity—multi-layered canopies and irregular stem distributions—exhibit diffuse, vertically extensive voids. In contrast, structurally uniform stands contain more confined voids, largely restricted to lower strata because of diminished understory development. These patterns demonstrate that forest voids integrate overstory and understory attributes, providing a structural lens on spatial openness under diverse conditions. Although challenges in scalability and independent validation remain, extending this framework to multi-platform LiDAR will enable broader applications in biodiversity monitoring, habitat suitability, and climate-adaptation research. By formalizing forest-void quantification, our study advances structural complexity assessment and offers fresh insights into ecosystem dynamics and function.