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Decomposition of Waveform Data

  1. One of the most important advantages of recording full waveform is that it allows the end user to decompose the data rather than rely on someone else.
  2. Qi Li claims that the use of the Expectation Maximum (EM) algorithm produces more accurate results.
  3. This can lead to more precise measurement of tree height and crown volume.

In a 2008 ISPRS paper Qi Li notes that “Data storage capacity and high processing speed available today has made it possible to digitally sample and store the entire reflected waveform of Small-Footprint Airborne Lidar (light detection and ranging), instead of only extracting the discrete coordinates which form the so-called point clouds. One of the most important advantages from waveform data is that it gives the user the chance to extract three-dimensional coordinates by himself in the post-processing.”

Qi Li found that most of the current vendor methods for decomposing the waveform are not as accurate as the Expectation Maximum (EM) algorithm that he uses and presents in the paper. By extracting the precise peak location and pulse width one will improve the accuracy of digital surface models (DSM) and height measurements for tree canopy.

This approach returns control of the decomposition to the end user, eliminating the black box nature of LiDAR equipment vendor’s systems. This is a very well written paper and recommended to all levels.

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