Optimization of Geoscience Laser Altimeter System waveform metrics to support vegetation measurements

Abstract

The Geoscience Laser Altimeter System (GLAS) has collected over 250 million measurements of vegetation height over forests globally. Accurate vegetation heights can be determined using waveform metrics that include vertical extent and extent of the waveform's trailing and leading edges. All three indices are highly dependent upon the signal strength, background noise and signal-to-noise ratio of the waveform, as the background noise contribution to the waveforms has to be removed before their calculation. Over the last six years, GLAS has collected data during thirteen observation periods using illumination from three different lasers. The power levels of these lasers have changed over time, resulting in variable signal power and noise characteristics. Atmospheric conditions vary continuously, also influencing signal power and noise. To minimize these effects, we optimized a noise coefficient which could be constant or vary according to observation period or noise metric. This parameter is used with the mean and standard deviation of the background noise to determine a noise level threshold that is removed from each waveform. An optimization analysis was used with a global dataset of waveforms that are near-coincident with waveforms from other observation periods; the goal of the optimization was to minimize the difference in vertical extent between spatially overlapping GLAS observations. Optimizations based on absolute difference in height led to situations in which the total extent was minimized as well; further optimizations reduced a normalized difference in height extent. The simplest optimizations were based on a constant value to be applied to all observations; noise coefficients of 2.7, 3.2, 3.4 and 4.0 were determined for datasets consisting of global forests, global vegetation, forest in the legal Amazon basin and boreal forests respectively. Optimizations based on the power level or the signal-to-noise ratio of waveforms best minimized differences in waveform extent, decreasing the percent root mean squared height difference by 25–54% over the constant value approach. Further development of methods to ensure temporal consistency of waveform indices will be necessary to support long-term satellite lidar missions and will result in more accurate and precise estimates of canopy height.