Signal-to-noise ratio–based quality assessment method for ICESat/GLAS waveform data

Sheng Nie; Cheng Wang; Guicai Li; Feifei Pan; Xiaohuan Xi; Shezhou Luo

doi:10.1117/1.OE.53.10.103104

8 October 2014 Signal-to-noise ratio–based quality assessment method for ICESat/GLAS waveform data

Sheng Nie, Cheng Wang, Guicai Li, Feifei Pan, Xiaohuan Xi, Shezhou Luo

Author Affiliations +

Optical Engineering, Vol. 53, Issue 10, 103104 (October 2014). https://doi.org/10.1117/1.OE.53.10.103104

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.

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Sheng Nie, Cheng Wang, Guicai Li, Feifei Pan, Xiaohuan Xi, and Shezhou Luo "Signal-to-noise ratio–based quality assessment method for ICESat/GLAS waveform data," Optical Engineering 53(10), 103104 (8 October 2014). https://doi.org/10.1117/1.OE.53.10.103104

Published: 8 October 2014

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