Terrain slope estimation within footprint from ICESat/GLAS waveform: model and method

Abstract

Terrain slope of Greenland is usually calculated from surface elevation on a large scale. Novel physical models were established to estimate the terrain slope within laser footprints on a smaller scale. Based on the time-stamped waveforms of ice, clouds, and land elevation satellite/ geoscience laser altimeter system (ICESat/GLAS), the physical models for calculating the slopes were established in two cases: zero attitude angles and non-zero attitude angles, respectively. The expressions of waveform slopes are related not only to the waveform width and the mean pulse delay of the time-stamped waveform, both in nanoseconds, but also to the attitude of the satellite and the laser divergence angle. In order to calculate the waveform width and the mean pulse delay, a non-Gaussian mathematical function was proposed to curve-fit the waveforms. The slopes estimated from the waveforms were compared with the slopes calculated from surface elevations. Results show that the two methods generate almost identical slope estimations for the same terrain. Calculation results also indicate that the method for slope estimation proposed in this paper performs better for extreme sloping terrain than for gentle sloping terrain.

Estimating Terrain Slope from ICESat-2 Data in Forest Environments

“…As the first earth observation LiDAR system, the Ice, Cloud, and Land Elevation Satellite (ICESat)/Geoscience Laser Altimeter System (GLAS) has been successfully applied for terrain slope estimation [21][22][23][24]. According to previous studies, there are two methods capable of deriving terrain slopes from large-footprint LiDAR waveform data [20,21,[25][26][27].…”

“…As the first earth observation LiDAR system, the Ice, Cloud, and Land Elevation Satellite (ICESat)/Geoscience Laser Altimeter System (GLAS) has been successfully applied for terrain slope estimation [21][22][23][24]. According to previous studies, there are two methods capable of deriving terrain slopes from large-footprint LiDAR waveform data [20,21,[25][26][27]. The first type of method can simultaneously calculate along-track slopes and across-track slopes based on repeated tracks, but they fail to obtain accurate small-scale terrain slopes due to the limitation of sparse footprint distribution.…”

“…The first type of method can simultaneously calculate along-track slopes and across-track slopes based on repeated tracks, but they fail to obtain accurate small-scale terrain slopes due to the limitation of sparse footprint distribution. The other kind of method can estimate within-footprint terrain slopes by analyzing the received waveforms [20][21][22]28]. Specifically, the within-footprint slopes were obtained by examining the relationship between laser characteristics, surface topography, and waveform feature parameters.…”