An Adaptive Density-Based Model for Extracting Surface Returns From Photon-Counting Laser Altimeter Data

Abstract-The Ice, Cloud and land Elevation Satellite-2 (ICESat-2) mission of the National Aeronautics and Space Administration is scheduled to launch in 2017. This upcoming mission aims to provide data to determine the temporal and spatial changes of ice sheet elevation, sea ice freeboard, and veget...

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Bibliographic Details
Main Authors: Jiashu Zhang, Senior Member, IEEE John Kerekes
Other Authors: The Pennsylvania State University CiteSeerX Archives
Format: Text
Language:English
Subjects:
Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1089.391
http://www.cis.rit.edu/people/faculty/kerekes/pdfs/GRSL_2015_Zhang.pdf
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Summary:Abstract-The Ice, Cloud and land Elevation Satellite-2 (ICESat-2) mission of the National Aeronautics and Space Administration is scheduled to launch in 2017. This upcoming mission aims to provide data to determine the temporal and spatial changes of ice sheet elevation, sea ice freeboard, and vegetation canopy height. A photon-counting lidar onboard ICESat-2 yields point clouds resulting from surface returns and noise. In support of the ICESat-2 mission, this letter derives an adaptive density-based model that is capable of detecting the ground surface and vegetation canopy in photon-counting laser altimeter data. Based on results from point clouds generated by a first principle simulation and those observed by the Multiple Altimeter Beam Experimental Lidar, the ground and canopy returns can be reliably extracted using the proposed approach. Further study on performance assessment shows that smoother surfaces will result in improved accuracy of ground height estimation. In addition, the proposed detection approach has better performance in environments with lower noise, although the performance evaluation metric F -measure does not vary significantly over a range of noise rates (0.5-5 MHz). This proposed approach is generally applicable for surface and canopy finding from photon-counting laser altimeter data. Index Terms-Density-Based Spatial Clustering of Applications with Noise (DBSCAN), Ice, Cloud and land Elevation Satellite-2 (ICESat-2), lidar, surface finding.