Wavelet Analysis for ICESat/GLAS Waveform Decomposition and Its Application in Average Tree Height Estimation

摘要

A waveform decomposition method, i.e., multiscale wavelet analysis, is proposed in this letter for light detection and ranging waveform characterization and average tree height estimation. First, the waveform decomposition was applied to ICESat/Geoscience Laser Altimeter System (GLAS) data to extract the waveform characteristics (waveform peaks) through performing Gaussian wavelet functions at five increasing scales. Then, the waveform length and average tree height were derived from the waveform decomposition information. This method was applied to the GLAS waveform data in Yunnan province, China, for average tree height estimation. Finally, the results were validated by field measurements and compared with the relevant parameters in the GLA14 product provided by NASA. This study indicates that, for simple-peak waveforms, the waveform decomposition was consistent with that of the GLA14 product, while for bimodal or multipeak waveforms, the result was more accurate and reasonable than that of the GLA14 product.