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Remote sensing of a Smithsonian forest with airborne LiDAR

The storage and flux of terrestrial carbon (C) is one of the most uncertain components of the global C budget and detailed quantification of forest C remains difficult to measure on a large scale. Remote sensing of forests with airborne LiDAR (Light Detection and Ranging) has proven to be an effective method of bridging the gap between data from plot-level mensuration and landscape-scale C storage estimates, but the standard method of assessing forest C is typically based on national or regional-scale allometric equations that are often not representative on the local-scale. The goals of this study were to determine if terrestrial LiDAR (TLS) can be used to improve local allometric equations and what are the implications of fusing these equations to airborne LiDAR data sources for biomass estimation.

Mapping Forest Biomass Carbon by Fusing Terrestrial and Airborne LiDAR Datasets. Available from: https://www.researchgate.net/publication/318990241_Mapping_Forest_Biomass_Carbon_by_Fusing_Terrestrial_and_Airborne_LiDAR_Datasets [accessed Oct 11 2017].

 

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