Spectral and Structural Differences Between Coniferous and Broadleaf Forest derived from LIDAR and AVIRIS
Dar
Alexander
Roberts, Dept. of Geography, UC Santa Barbara, dar@geog.ucsb.edu
(Presenting)
Keely
L
Roth, Dept. of Geography, UC Santa Barbara, klroth84@gmail.com
Eliza
S
Bradley, Dept. of Geography, UC Santa Barbara, eliza.bradley@gmail.com
Parker
G
Geoffrey, Smithsonian Environmental Research Center, parkerg@si.edu
Dennison
E
Philip, Dept. of Geography, University of Utah, dennison@geog.utah.edu
Natour
Bothaina, Dept. of Geography, University of Utah, bothaina.natour@geog.utah.edu
Combined LIDAR and hyperspectral measures can improve our ability to estimate carbon stocks and fluxes, through improved maps of forest structure, tree species and biophysical attributes. In past research, we have demonstrated strong relationships between small footprint (discrete) LIDAR and canopy albedo across an age chronosequence in coniferous forest. We have also shown strong relationships between LIDAR-derived height measures and biomass in several coniferous ecosystems. In this poster we extend this analysis to compare LIDAR and AVIRIS-derived measures in a broadleaf deciduous forest (SERC) to those derived from a coniferous forest at Wind River.
Analysis at SERC focused on three main sensors, discrete LIDAR, waveform LIDAR (LVIS) and AVIRIS. Discrete LIDAR data were processed to generate a digital terrain model (DTM), then used to create a digital canopy model (DCM). A comparison between canopy height measures derived from LVIS, and height derived from the discrete LIDAR showed both systems to be highly correlated over the same spatial footprint. Height measures from LVIS and discrete LIDAR were validated using canopy height derived from a stem map and by comparison to simulated canopy ellipsoids generated through a model. Comparison between modeled canopy height and LIDAR derived height were generally good, improving when species-level differences were incorporated into simulated canopy ellipsoids.
Correlation between AVIRIS-derived albedo, and canopy shade at SERC was very high. However, correlation between the standard deviation of LIDAR-height (rugosity) and albedo was low, contrary to previous findings at Wind River. Likely mechanisms accounting for differences between SERC and Wind River include 1) a lack of a large range of age classes at SERC; 2) architectural differences between conifer and broadleaf trees; and 3) differences in the spatial scale of analysis, where correlations are high when the data are aggregated to stand scales, but lower when aggregated over fixed window sizes
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