Feature Classification Benefits of Full-Waveform Airborne Laser Terrain Mapping
Abstract
We present the feature classification benefits of full-waveform return analysis from airborne laser terrain mapping (ALTM). Through the examination of the characteristics of clusters of return pulses in terms of range, number of returns, scattered amplitude, and scattered width, we are able to discriminate among a number of classes of ground features. The University of Texas Center for Space Research has obtained several distinct full-waveform datasets over several ecosystem types including urban and low-height vegetation environments. The UT ALTM system is equipped with a waveform digitizer that allows the simultaneous recording of conventional first and last return lidar data and the corresponding reflection waveforms at the 25 kHz laser pulse repetition rate. Reflecting targets or surfaces within the return laser path are identified using a Gaussian decomposition of the return waveform. We present the waveform properties from different classes of scatters including man-made and natural targets and draw some conclusions about the potential for unsupervised, untrained classification of objects. Finally, we discuss the applications where full-waveform is likely to most benefit ALTM including the ability to identify ground returns in the presence of understory.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2007
- Bibcode:
- 2007AGUFM.G43D..08A
- Keywords:
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- 9805 Instruments useful in three or more fields