Characterizing leaf area index (LAI) and vertical foliage profile (VFP) over the United States
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Abstract
Leaf area index (LAI) and vertical foliage profile (VFP) are among the important canopy structural variables. Recent advances in lidar remote sensing technology have demonstrated the capability of accurately mapping LAI and VFP over large areas. The primary objective of this study was to derive and validate a LAI and VFP product over the contiguous United States (CONUS) using spaceborne waveform lidar data. This product was derived at the footprint level from the Geoscience Laser Altimeter System (GLAS) using a biophysical model. We validated GLAS-derived LAI and VFP across major forest biomes using airborne waveform lidar. The comparison results showed that GLAS retrievals of total LAI were generally accurate with little bias (r2 = 0.67, bias = –0.13, RMSE = 0.75). The derivations of GLAS retrievals of VFP within layers were not as accurate overall (r2 = 0.36, bias = –0.04, RMSE = 0.26), and these varied as a function of height, increasing from understory to overstory – 0 to 5m layer: r2 = 0.04, bias = 0.09, RMSE = 0.31; 10 to 15m layer: r2 = 0.53, bias = –0.08, RMSE = 0.22; and 15 to 20m layer: r2 = 0.66, bias = –0.05, RMSE = 0.20. Significant relationships were also found between GLAS LAI products and different environmental factors, in particular elevation and annual precipitation. In summary, our results provide a unique insight into vertical canopy structure distribution across North American ecosystems. This data set is a first step towards a baseline of canopy structure needed for evaluating climate and land use induced forest changes at the continental scale in the future, and should help deepen our understanding of the role of vertical canopy structure in terrestrial ecosystem processes across varying scales.
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Funding for Open Access provided by the UMD Libraries Open Access Publishing Fund.