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Optical Engineering

Signal-to-noise ratio–based quality assessment method for ICESat/GLAS waveform data
Author(s): Sheng Nie; Cheng Wang; Guicai Li; Feifei Pan; Xiaohuan Xi; Shezhou Luo
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Paper Abstract

Data quality determines the accuracy of results associated with remote sensing data processing and applications. However, few effective studies have been carried out on quality assessment methods for the full-waveform light detecting and ranging data. Using the geoscience laser altimeter system (GLAS) waveform data as an example, a signal-to-noise ratio (SNR)-based waveform quality assessment method is proposed to analyze the relationship between the SNR and its controlling factors, i.e., laser type, laser using time, topographic relief, and land cover type, and study the impacts of these factors on the quality of the GLAS waveform data. Results show that the SNR-based data quality assessment method can quantitatively and effectively assess the GLAS waveform data quality. The SNR linearly attenuates with the laser using time, and the attenuation rate varies with laser type. The topographic relief is inversely correlated with the SNR of the GLAS data. As the land cover structure (especially the vertical structure) becomes more complex, the SNR of the GLAS data decreases. It was found that land cover types in descending order of the SNR values are desert, farmland, water body, grassland, city, and forest.

Paper Details

Date Published: 8 October 2014
PDF: 9 pages
Opt. Eng. 53(10) 103104 doi: 10.1117/1.OE.53.10.103104
Published in: Optical Engineering Volume 53, Issue 10
Show Author Affiliations
Sheng Nie, Institute of Remote Sensing and Digital Earth (China)
Cheng Wang, Institute of Remote Sensing and Digital Earth (China)
Guicai Li, China Meteorological Administration (China)
Feifei Pan, Univ. of North Texas (United States)
Xiaohuan Xi, Institute of Remote Sensing and Digital Earth (China)
Shezhou Luo, Institute of Remote Sensing and Digital Earth (China)

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