Signal Photon Extraction Method for Weak Beam Data of ICESat-2 Using Information Provided by Strong Beam Data in Mountainous Areas

Zhiyu Zhang,Yue Ma,Song Li,Nan Xu,Xinyuan Liu,Wenhao Zhang

doi:10.3390/rs13050863

Abstract

The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) can measure the elevations of the Earth’s surface using a sampling strategy with unprecedented spatial detail. In the daytime of mountainous areas where the signal–noise ratio (SNR) of weak beam data is very low, current algorithms do not always perform well on extracting signal photons from weak beam data (i.e., many signal photons were missed). This paper proposes an effective algorithm to extract signal photons from the weak beam data of ICESat-2 in mountainous areas. First, a theoretical equation of SNR for ICESat-2 measured photons in mountainous areas was derived to prove that the available information provided by strong beam data can be used to assist the signal extraction of weak beam data (that may have very low SNR in mountainous areas). Then, the relationship between the along-track slope and the noise level was used as the bridge to connect the strong and weak beam data. To be specific, the along-track slope of the weak beam was inversed by the slope–noise relationship obtained from strong beam data, and then was used to rotate the direction of the searching neighborhood in the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm. With the help of this process, the number of signal photons included in the searching neighborhood will significantly increase in mountainous areas and will be easily detected from the measured noisy photons. The proposed algorithm was tested in the Tibetan Plateau, the Altun Mountains, and the Tianshan Mountains in different seasons, and the extraction results were compared with the results from the ATL03 datasets, the ATL08 datasets, and the classical DBSCAN algorithm. Based on the ground-truth signal photons obtained by visual inspection, the parameters of the classification precision, recall, and F-score of our algorithm and three other algorithms were calculated. The modified DBSCAN could achieve a good balance between the classification precision (93.49% averaged) and recall (89.34% averaged), and its F-score (more than 0.91) was higher than that of the other three methods, which successfully obtained a continuous surface profile from weak beam data with very low SNRs. In the future, the detected signal photons from weak beam data are promising to assess the elevation accuracy achieved by ICESat-2, estimate the along-track and cross-track slope, and further obtain the ground control points (GCPs) for stereo-mapping satellites in mountainous areas.

Highlights

This article is an open access articleThe Ice, Cloud, and land Elevation Satellite (ICESat) launched in 2003 has achieved great success in monitoring the changes in the Earth’s polar region and the datasets have been widely used in many other scopes such as retrieving forest canopy heights, assessing biomass changes, and monitoring sea levels [1,2,3,4,5,6]
Algorithm cannot successfully detect the signal photons from weak beam data. Both the classical Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm and the modified DBSCAN algorithm in this study were separately applied to extract terrain profile, and the results were compared with the truth-values, which were obtained by labeling the signal photons manually [30,35,38]
The signal-to-noise ratio (SNR) dropped quickly as the along-track slope rose, and when the along-track slope was higher than 25◦, the SNR of the weak beam data fell to around 4 dB, which is often taken as the threshold to judge whether signal photons can be extracted from measured noisy photons

Summary

Introduction

The Ice, Cloud, and land Elevation Satellite (ICESat) launched in 2003 has achieved great success in monitoring the changes in the Earth’s polar region and the datasets have been widely used in many other scopes such as retrieving forest canopy heights, assessing biomass changes, and monitoring sea levels [1,2,3,4,5,6]. Launched its successor (i.e., the Ice, Cloud, and land Elevation Satellite-2 (ICESat-2)), which was on board with a photon-counting laser altimeter. Benefiting from the low energy requirement of photon-counting detectors, the laser transmitter is able to operate at a frequency of 10 kHz and the along-track spacing intervals reduce to only 0.7 m, which can obtain the along-track terrain profiles with much higher spatial resolution compared to that from the ICESat laser altimeter. The slight yaw of the satellite separates the components (including a strong and a weak beam) in a beam pair by 90 m [11]

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Discussion

Conclusion