Utilities to Support Lidar Applications at the Landscape, Forest, and Tree Scale

Implements algorithms for terrestrial, mobile, and airborne lidar processing, tree detection, segmentation, and attribute estimation (Donager et al., 2021) , and a hierarchical patch delineation algorithm 'PatchMorph' (Girvetz & Greco, 2007) . Tree detection uses rasterized point cloud metrics (relative neighborhood density and verticality) combined with RANSAC cylinder fitting to locate tree boles and estimate diameter at breast height. Tree segmentation applies graph-theory approaches inspired by Tao et al. (2015) with cylinder fitting methods from de Conto et al. (2017) . PatchMorph delineates habitat patches across spatial scales using organism-specific thresholds. Built on 'lidR' (Roussel et al., 2020) .

spanner

Definition of spanner
1 (chiefly British): WRENCH
2: a wrench that has a hole, projection, or hook at one or both ends of the head for engaging with a corresponding device on the object that is to be turned
3: implements algorithms for terrestrial, mobile, and airborne lidar processing, tree detection, segmentation, and attribute estimation (Donager et al., 2021), and hierarchical patch delineation (Girvetz & Greco, 2007).

Install spanner

Get the latest released version of spanner from github.

remotes::install_github('bi0m3trics/spanner')

Workflows

Terrestrial Lidar Tree Attributes and Segmentation

This package implements the tree detection and segmentation algorithm described in Donager et al. (2021). The algorithm estimates tree locations and DBH by rasterizing individual point cloud values of relative neighborhood density and verticality within a slice of the normalized point cloud around breast height (1.37 m), then performs individual tree (instance) segmentation following ecological principles for "growing" trees based on input locations in a graph-theory approach. Implementation relies on work of Roussel et al. (2020), Tao et al. (2015), and de Conto et al. (2017).

Citation: Donager, Jonathon J., Andrew J. Sánchez Meador, and Ryan C. Blackburn 2021. Adjudicating Perspectives on Forest Structure: How Do Airborne, Terrestrial, and Mobile Lidar-Derived Estimates Compare? Remote Sensing 13, no. 12: 2297. https://doi.org/10.3390/rs13122297

PatchMorph: Patch Delineation Algorithm

The patchwoRk function implements a patch delineation algorithm [at present it only implements 'PatchMorph' (Girvetz & Greco 2007), which can delineate patches across a range of spatial scales based on three organism-specific thresholds - (1) land cover density threshold, (2) habitat gap maximum thickness (gap threshold), and (3) habitat patch minimum thickness (spur threshold)].

Citation: Girvetz EH, and Greco SE. 2007. How to define a patch: a spatial model for hierarchically delineating organism-specific habitat patches. Landscape Ecology 22: 1131-1142. http://dx.doi.org/10.1007/s10980-007-9104-8