Quantifying vegetation and canopy structural complexity from terrestrial LiDAR data using the FORESTR R package

Atkins, Jeff W.; Bohrer, Gil; Fahey, Robert T.; Hardiman, Brady S.; Morin, Timothy H.; Stovall, Atticus L.; Zimmerman, Naupaka; Gough, Christopher M.

doi:10.1111/2041-210x.13061

Title: Quantifying vegetation and canopy structural complexity from terrestrial LiDAR data using the FORESTR R package

Journal Article · Sat Jul 07 00:00:00 EDT 2018 · Methods in Ecology and Evolution (Online)

DOI:https://doi.org/10.1111/2041-210x.13061· OSTI ID:1610891

^[1]; Bohrer, Gil ^[2]; Fahey, Robert T. ^[3]; Hardiman, Brady S. ^[3]; Morin, Timothy H. ^[4];

^[5]; Zimmerman, Naupaka ^[6]; Gough, Christopher M. ^[7]

Univ. of Richmond, VA (United States)
The Ohio State Univ., Columbus, OH (United States)
Univ. of Connecticut, Storrs, CT (United States)
State Univ. of New York (SUNY), Syracuse, NY (United States). College of Environmental Science and Forestry; The Ohio State Univ., Columbus, OH (United States); Purdue Univ., West Lafayette, IN (United States)
Purdue Univ., West Lafayette, IN (United States); Univ. of Virginia, Charlottesville, VA (United States)
University of San Francisco, San Francisco, CA (United States)
Virginia Commonwealth Univ., Richmond, VA (United States)

Abstract Terrestrial Li DAR (light detection and ranging) technologies have created new means of quantifying forest canopy structure, allowing not only the estimation of biomass, but also descriptions of the position and variability in canopy elements in space. Such measures provide novel structural information broadly useful to ecologists. There is a growing need for both a detailed taxonomy of forest canopy structural complexity ( CSC ) and open, transparent, and flexible tools to quantify complexity in ways that will advance foundational ecological knowledge of structure‐function relationships. The CSC taxonomy we present groups structural descriptors into five categories: leaf area and density, canopy height, canopy arrangement, canopy openness, and canopy variability. This paper also introduces the r package forestr , the first open‐source r package for the calculation of CSC metrics from terrestrial Li DAR data. The r package forestr is an analysis toolbox that works with portable canopy Li DAR ( PCL ) data and other pixelated/voxelized point clouds derived from terrestrial Li DAR scanning ( TLS ) data to calculate CSC metrics of interest to ecologists, modellers, forest managers, and remote sensing scientists.

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Research Organization:: The Ohio State University, Columbus, OH (United States); Rutgers Univ., Piscataway, NJ (United States)

Sponsoring Organization:: USDOE Office of Science (SC)

Grant/Contract Number:: SC0006708; SC0007041; DE‐SC0006708; DE‐SC0007041

OSTI ID:: 1610891

Alternate ID(s):: OSTI ID: 1464572

Journal Information:: Methods in Ecology and Evolution (Online), Vol. 9, Issue 10; ISSN 2041-210X

Publisher:: British Ecological SocietyCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 71 works

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54 ENVIRONMENTAL SCIENCES
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Title: Quantifying vegetation and canopy structural complexity from terrestrial LiDAR data using the FORESTR R package

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