Paper
2 May 2009 Fundamental relationships inherent to lidar waveforms for classification
Amy Neuenschwander, Lori Magruder, Alexis Londo, Scott Tweddale
Author Affiliations +
Abstract
Full-waveform laser altimetry has been used in the research community since the mid-1990s and this technology holds great potential for the science and defense communities. Laser waveforms are a digital recording of the entire temporal profile from the reflected laser energy. The shape of the returned laser waveform is a function of both laser and surface properties. Waveform metrics were extracted for each waveform and include peak amplitude, peak standard deviation, integrated canopy energy, integrated ground energy, total waveform energy, ratio between canopy and ground energy, rise time to the first peak, fall time of the last peak, and vegetation height. The utilization of such metrics provides a potential for discriminating and identifying discrete targets on a per-shot basis. Analysis of the entire reflected laser energy profile provides a detailed description of distributed targets/features along the laser line-of-sight. Waveform data collected over Camp Shelby, Mississippi reveal separation of conifer from broadleaf vegetation. Metrics such as integrated canopy energy and fall time were found to be higher in hardwood forest than pine forest. Other landscape features such as the presence of a burn are also detected with full-waveform data, which would otherwise be missed with discrete return elevation data. With new full-waveform systems entering the commercial sector, new possibilities emerge to utilize the lidar data to classify land cover as well as quantify surface parameters.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Amy Neuenschwander, Lori Magruder, Alexis Londo, and Scott Tweddale "Fundamental relationships inherent to lidar waveforms for classification", Proc. SPIE 7323, Laser Radar Technology and Applications XIV, 73230A (2 May 2009); https://doi.org/10.1117/12.818607
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Cited by 1 scholarly publication.
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KEYWORDS
LIDAR

Vegetation

Laser energy

Composites

Defense and security

Ecosystems

Feature extraction

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