Evaluating TIFFS (Toolbox for LiDAR Data Filtering and Forest Studies) in Deriving Forest Measurements from LiDAR Data

John Chapman, I-Kuai Hung, Jeff Tippen


The recent advances in LiDAR (Light Detection and Ranging) have allowed for the remote sensing of important forest characteristics to be more reliable and commercially available. Studies have shown that this technology can accurately estimate forest characteristics including individual tree location, canopy height, and crown diameter. These values are used to estimate biophysical properties of forests such as basal area and stand volume. This study assesses the accuracy of LiDAR-derived estimates of forest characteristics including diameter and height against traditional timber cruising through field sampling. A commercially available program, TiFFS (Toolbox for LiDAR Data Filtering and Forest Studies), is used for comparison. Results are discussed with the focus on forestry operation.  MCFNS 2(2):145-152.


Lidar, remote sensing, forestry

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