Towards 3D tree spatial pattern analysis: Setting the cornerstone of LiDAR advancing 3D forest structural and spatial ecology

Abstract

The potential of Light Detection and Ranging (LiDAR) on expanding the horizon of forest ecology has been realized, but this does not mean that the related interdisciplinary branches, often considered as attractive independent fields as well, can readily step into their 3D stages. To go along with this, the core task confronted by the community now is to explore solutions aiming at the cornerstones of their 3D upgrading. In the common cases of forest structural and spatial ecology, tree spatial pattern is such a cornerstone-like theme, which is of fundamental significance on reflecting their various aspects. However, the mainstream methods of spatial point pattern analysis that are rooted in the traditional tools of forest inventory, as our review indicated, cannot directly take the advantage of LiDAR remote sensing in 3D characterization of trees. To break this bottleneck, we proposed 3D tree spatial pattern analysis, as a theoretical reconstruction from top firstly. We further proposed 3D data forms and 3D spatial statistics models to comprise a general principle framework for supporting future developments of 3D methods. These foundational outlooks at the level of transiting potential to practice are of referencing implication on, in a broader sense, boosting 3D plant spatial pattern analysis for setting the cornerstone of LiDAR advancing 3D structural and spatial ecology.