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MDPI, Remote Sensing, 3(13), p. 424, 2021

DOI: 10.3390/rs13030424

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Inversion of Terrain Slope and Roughness with Satellite Laser Altimeter Full-Waveform Data Assisted by Shuttle Radar Topographic Mission

Journal article published in 2021 by Zhiqiang Zuo ORCID, Xinming Tang, Guoyuan Li, Yue Ma, Wenhao Zhang, Song Li
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Slope and roughness are basic geophysical properties of terrain surface, and also sources of error in satellite laser altimetry systems. The full-waveform satellite laser altimeter records the complete echo waveform backscattered from the target surface worldwide, so it may be used for both range measurement and inversion analysis of geometric parameters of the target surface. This paper proposes a new method for inversion of slope and roughness of the bare or near-bare terrain within laser footprint using full-waveform satellite laser altimeter data, Shuttle Radar Topographic Mission (SRTM) and topographic prior knowledge. To solve the non-uniqueness of the solution to the inversion problem, this paper used the SRTM and airborne Light Detection and Ranging (LiDAR) data in North Rhine-Westphalia, Germany, to establish a priori hypothesis about real information of topographic parameters. Then, under the constraints of prior hypothesis, the theoretical formulas and rules for slope and roughness inversion using the pulse-width broadening knowledge of satellite laser altimeter echo full-waveform were developed. Finally, based on the full-waveform data from the Geoscience Laser Altimeter System (GLAS) that was borne on ICE, Cloud, and Land Elevation Satellite (ICESat) and SRTM in the West Valley City, Utah and Jackson City, Wyoming, United States of America, the inversion was carried out. The experiment compares the results of proposed method with those of existing ones and evaluates the inversion results using high precision terrain slope and roughness information, which indicates that our proposed method is superior to the state-of-the-art methods, and the inversion accuracy for slope is 0.667° (Mean Absolute Error, MAE) and 1.054° (Root Mean Square Error, RMSE), the inversion accuracy for roughness is 0.171 m (MAE) and 0.250 m (RMSE).