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Wednesday, April 11 • 10:15am - 10:30am
FOREST LANDSCAPE PROCESSES: Linking Terrestrial LIDAR to Landsat: Canopy Structural Complexity is Associated with Spectral Indices of Greenness and Brightness

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AUTHORS: Elizabeth A. LaRue, Purdue University; Jeff Atkins, Virginia Commonwealth University; Kyla Dahlin, Michigan State University; Robert Fahey, University of Connecticut; Songlin Fei, Purdue University; Chris Gough, Virginia Commonwealth University; Brady S. Hardiman, Purdue University

ABSTRACT: Forest canopy structure is closely coupled with ecosystem function, but traditional measures of horizontal canopy structure, such as leaf area index (LAI), do not fully explain light use efficiency and net primary production within forest ecosystems. Canopy structural complexity, which characterizes the cover and vegetation distribution within a canopy, together with LAI, may explain variation in forest ecosystem function more completely than LAI alone. Canopy structural complexity, is most effectively measured with below-canopy, upward-viewing terrestrial LIDAR, and thus has been restricted to small sub-hectare spatial scales. This limits quantification and understanding of canopy structural complexity at larger spatial scales important for inferring ecosystem functioning. Here, we examined associations between terrestrial LIDAR measurements of canopy structural complexity and Landsat spectral indices to evaluate the feasibility of scaling complexity. Canopy structural complexity measurements were obtained from plots within eight NEON forested sites across eastern North America, while spectral indices (NDVI, EVI, tasseled cap greenness/wetness/brightness) were calculated for the corresponding locations from Landsat 8 satellite imagery. Results showed that canopy greenness and brightness significantly predicted spatial variation in several categories of canopy structural complexity. We found that greener canopies were associated with a taller canopy, greater leaf area density and variability, a more fully covered and a less porous canopy. Among greenness indices, NDVI explained the largest fraction of variation in canopy structural complexity metrics (adj. R2 = 0.52 – 0.62 for six metrics), and robustly predicted six metrics with linear models. Additionally, we found that a brighter canopy was associated with greater leaf area density and variability, canopy cover, porosity, and lower leaf clumping. These results demonstrate the potential for the estimation of canopy structural complexity at regional scales using satellite imagery, and could greatly expand the scale at which these metrics can be incorporated into ecosystem and earth system models.

Wednesday April 11, 2018 10:15am - 10:30am CDT
Spire Parlor