Coupling fine-scale root and canopy structure using ground-based remote sensingAuthor(s): Brady Hardiman; Christopher Gough; John Butnor; Gil Bohrer; Matteo Detto; Peter Curtis
Source: Remote Sensing
Publication Series: Scientific Journal (JRNL)
Station: Southern Research Station
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Ecosystem physical structure, defined by the quantity and spatial distribution of biomass, influences a range of ecosystem functions. Remote sensing tools permit the non-destructive characterization of canopy and root features, potentially providing opportunities to link above- and belowground structure at fine spatial resolution in functionally meaningful ways. To test this possibility, we employed ground-based portable canopy LiDAR (PCL) and ground penetrating radar (GPR) along co-located transects in forested sites spanning multiple stages of ecosystem development and, consequently, of structural complexity. We examined canopy and root structural data for coherence (i.e., correlation in the frequency of spatial variation) at multiple spatiascales 10 m within each site using wavelet analysis. Forest sites varied substantially in vertical canopy and root structure, with leaf area index and root mass more becoming even vertically as forests aged. In all sites, above- and belowground structure, characterized as mean maximum canopy height and root mass, exhibited significant coherence at a scale of 3.5–4 m, and results suggest that the scale of coherence may increase with stand age. Our findings demonstrate that canopy and root structure are linked at characteristic spatial scales, which provides the basis to optimize scales of observation. Our study highlights the potential, and limitations, for fusing LiDAR and radar technologies to quantitatively couple above- and belowground ecosystem structure.
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CitationHardiman, Brady; Gough, Christopher; Butnor, John; Bohrer, Gil; Detto, Matteo; Curtis, Peter. 2017. Coupling fine-scale root and canopy structure using ground-based remote sensing. Remote Sensing, Vol. 9(2): 182-194. 13 p. DOI:10.3390/rs9020182
Keywordscanopy, root, biomass, spatial wavelet coherence, radar, LiDAR
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