3 years ago

Non-destructive estimation of above-ground surface and near-surface biomass using 3D terrestrial remote sensing techniques

Samuel Hillman, Karin Reinke, Bryan Hally, Luke Wallace
Quantitative measurements of above-ground vegetation biomass are vital to a range of ecological and natural resource management applications. Remote-sensing techniques, such as terrestrial laser scanning (TLS) and image-based point clouds, are potentially revolutionary techniques for measuring vegetation biomass and deriving other related, structural metrics for these purposes. Surface vegetation biomass (up to 25 cm) in pasture, forest, and woodland environments is estimated from a 3D point cloud derived from a small number of digital images. Volume is calculated, using the 3D cloud and regressed against dry weight to provide an estimate of biomass. Assessment of the method is made through comparison to 3D point clouds collected through TLS surveys. High correlation between destructively sampled biomass and vegetation volume derived from TLS and image-based point clouds in the pasture (TLS r2=0·75, image based r2=0·78), dry grassy forest (TLS r2=0·73, image based r2=0·87) and lowland forest (TLS r2=0·74, image based r2=0·63) environments was found. Occlusion caused by standing vegetation in the woodland environment resulted in moderate correlation between TLS derived volume and biomass (r2=0·50). The effects of surrounding vegetation on the image-based technique resulted in 3D point clouds being resolved for only 40% of the samples in this environment. The results of this study demonstrate that image-based point cloud techniques are highly viable for the measurement of surface biomass. In contrast to TLS, volume and biomass data can be captured using low-cost equipment and relatively little expertise.

Publisher URL: http://onlinelibrary.wiley.com/resolve/doi

DOI: 10.1111/2041-210X.12759

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