Classifying ecosystems with metaproperties from terrestrial laser scanner data

Paynter, Ian; Genest, Daniel; Saenz, E. J.; Peri, Francesco; Boucher, Peter; Ли, Жан; Strahler, Alan H.; Schaaf, Crystal B.

doi:10.1111/2041-210x.12854

Cited by 9 publications

(12 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Previous studies have focused on comparisons of ALS and TLS at a single site or forest type in a localized region, but consistent with our results, these have found that ALS and TLS are comparable in their capacity to delineate features such as canopy height, cover, and vertical stratification [23][24][25][26]. TLS systems are a well-established method to provide high resolution, functionally meaningful measurements of structural diversity in forest ecosystems at the stand-scale [2,19,20,22,25,35], but these results demonstrate that ALS could potentially be used to scale the characterization of canopy structural diversity to much broader spatial extents.…”

Section: Discussionsupporting

confidence: 88%

“…LiDAR is a useful tool for the multi-dimensional characterization of forest structure that has versatile terrestrial and aerial deployment platforms spanning a multiple of spatial extents and resolutions [14][15][16][17][18]. Terrestrial laser scanners (TLS) and aerial laser scanners (ALS) have both been shown to be effective at quantifying components of forest structural diversity [14][15][16][17][18][19][20], however, each LiDAR platform has trade-offs for data resolution and spatial coverage. TLS and ALS scan the forest from opposite angles and occlusion by the canopy constrains the capacity of each to obtain data from portions of the canopy distal to the instrument [21] (Fig.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Compatibility of Aerial and Terrestrial LiDAR for Quantifying Forest Structural Diversity

LaRue¹,

Wagner²,

Fei³

et al. 2020

Preprint

View full text Add to dashboard Cite

Structural diversity is a key feature of forest ecosystems that influences ecosystem functions from local to macroscales. The ability to measure structural diversity in forests with varying ecological composition and management history can improve the understanding of linkages between forest structure and ecosystem functioning. Terrestrial LiDAR has often been used to provide a detailed characterization of structural diversity at local scales, but it is largely unknown whether these same structural features are detectable using aerial LiDAR data that are available across larger spatial scales. We used univariate and multivariate analyses to quantify cross-compatibility of structural diversity metrics from terrestrial versus aerial LiDAR in seven National Ecological Observatory Network sites across the eastern USA. We found strong univariate agreement between terrestrial and aerial LiDAR metrics of canopy height, openness, internal heterogeneity, and leaf area, but found marginal agreement between metrics that describe heterogeneity of the outer most layer of the canopy. Terrestrial and aerial LiDAR both demonstrated the ability to distinguish forest sites from structural diversity metrics in multivariate space, but terrestrial LiDAR was able to resolve finer-scale detail within sites. Our findings indicate that aerial LiDAR can be of use in quantifying broad-scale variation in structural diversity across macroscales.

show abstract

Section: Discussionsupporting

confidence: 88%

Section: Introductionmentioning

confidence: 99%

Compatibility of Aerial and Terrestrial LiDAR for Quantifying Forest Structural Diversity

LaRue¹,

Wagner²,

Fei³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…1a; Whittaker 1970). These vegetation structural types can be viewed as an agglomeration of canopy traits describing the arrangement of vegetation elements in canopy space and generally relate to three primary components of variation: canopy height, vertical layering and horizontal openness/patchiness (Aber et al 1982;Brokaw & Lent 1999;Ehbrecht et al 2016;Paynter et al 2018;Cushman & Kellner 2019), as well as higher-order metrics that combine or describe variation in these traits to characterise the arrangement of canopy elements in two-dimensional (2D) or 3D space (Hardiman et al 2011;Chen et al 2012;Seidel et al 2016).…”

Section: Introductionmentioning

confidence: 99%

Defining a spectrum of integrative trait‐based vegetation canopy structural types

et al. 2019

View full text Add to dashboard Cite

Vegetation canopy structure is a fundamental characteristic of terrestrial ecosystems that defines vegetation types and drives ecosystem functioning. We use the multivariate structural trait composition of vegetation canopies to classify ecosystems within a global canopy structure spectrum. Across the temperate forest sub‐set of this spectrum, we assess gradients in canopy structural traits, characterise canopy structural types (CST) and evaluate drivers and functional consequences of canopy structural variation. We derive CSTs from multivariate canopy structure data, illustrating variation along three primary structural axes and resolution into six largely distinct and functionally relevant CSTs. Our results illustrate that within‐ecosystem successional processes and disturbance legacies can produce variation in canopy structure similar to that associated with sub‐continental variation in forest types and eco‐climatic zones. The potential to classify ecosystems into CSTs based on suites of structural traits represents an important advance in understanding and modelling structure–function relationships in vegetated ecosystems.

show abstract

“…TLS observations in HF have been used to demonstrate the ability of lidar instruments to be sensitive to the ecosystem type and condition of the scanned space. CBL scans from HF have shown promise in separating distinctly different forest structures by using the method of metaproperties analysis to distil aggregate statistics from the geometry and pulse properties of the data [ 25 ]. Furthermore, expensive, high-resolution scanners are not necessary for such scan-based techniques.…”

Section: Discussionmentioning

confidence: 99%

The potential to characterize ecological data with terrestrial laser scanning in Harvard Forest, MA

et al. 2018

Self Cite

View full text Add to dashboard Cite

Contemporary terrestrial laser scanning (TLS) is being used widely in forest ecology applications to examine ecosystem properties at increasing spatial and temporal scales. Harvard Forest (HF) in Petersham, MA, USA, is a long-term ecological research (LTER) site, a National Ecological Observatory Network (NEON) location and contains a 35 ha plot which is part of Smithsonian Institution's Forest Global Earth Observatory (ForestGEO). The combination of long-term field plots, eddy flux towers and the detailed past historical records has made HF very appealing for a variety of remote sensing studies. Terrestrial laser scanners, including three pioneering research instruments: the Echidna Validation Instrument, the Dual-Wavelength Echidna Lidar and the Compact Biomass Lidar, have already been used both independently and in conjunction with airborne laser scanning data and forest census data to characterize forest dynamics. TLS approaches include three-dimensional reconstructions of a plot over time, establishing the impact of ice storm damage on forest canopy structure, and characterizing eastern hemlock (Tsuga canadensis) canopy health affected by an invasive insect, the hemlock woolly adelgid (Adelges tsugae). Efforts such as those deployed at HF are demonstrating the power of TLS as a tool for monitoring ecological dynamics, identifying emerging forest health issues, measuring forest biomass and capturing ecological data relevant to other disciplines. This paper highlights various aspects of the ForestGEO plot that are important to current TLS work, the potential for exchange between forest ecology and TLS, and emphasizes the strength of combining TLS data with long-term ecological field data to create emerging opportunities for scientific study.

show abstract

Classifying ecosystems with metaproperties from terrestrial laser scanner data

Cited by 9 publications

References 12 publications

Compatibility of Aerial and Terrestrial LiDAR for Quantifying Forest Structural Diversity

Compatibility of Aerial and Terrestrial LiDAR for Quantifying Forest Structural Diversity

Defining a spectrum of integrative trait‐based vegetation canopy structural types

The potential to characterize ecological data with terrestrial laser scanning in Harvard Forest, MA

Contact Info

Product

Resources

About