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TFmini--Improving Measurement of Forest Structural Parameters

Discussion in 'Member Drone Product Reviews' started by sophia lee, Dec 15, 2017.

  1. sophia lee

    sophia lee Member

    Nov 22, 2017
    Posted by sophia lee, Dec 15, 2017 #1
    TFmini is a milestone for Benewake to promote the process of low cost LiDAR. With its unique optical, structural, and electronic designs, the product possesses 3 major advantages: low cost, tiny volume and low power consumption. The built-in algorithm adapted to indoor and outdoor environments can guarantee an excellent ranging performance at a low cost and in a tiny volume, which highly expands the application fields andscenarios of LiDAR and lays a solid foundation for future “eyes” in the smart era.
    Forest structural parameters, such as tree height and crown width, are indispensable for evaluating forest biomass or forest volume. LiDAR is a revolutionary technology for measurement of forest structural parameters, however, the accuracy of crown width extraction is not satisfactory when using a low density LiDAR, especially in high canopy cover forest. We used high resolution aerial imagery with a low density LiDAR system to overcome this shortcoming. A morphological filtering was used to generate a DEM (Digital Elevation Model) and a CHM (Canopy Height Model) from LiDAR data. The LiDAR camera image is matched to the aerial image with an automated keypoints search algorithm. As a result, a high registration accuracy of 0.5 pixels was obtained. A local maximum filter, watershed segmentation, and object-oriented image segmentation are used to obtain tree height and crown width. Results indicate that the camera data collected by the integrated LiDAR system plays an important role in registration with aerial imagery. The synthesis with aerial imagery increases the accuracy of forest structural parameter extraction when compared to only using the low density LiDAR data.

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