Performance analysis of freeware filtering algorithms for determining ground surface from airborne laser scanning data

Kalev Julge; Artu Ellmann; Anti Gruno

doi:10.1117/1.JRS.8.083573

8 August 2014 Performance analysis of freeware filtering algorithms for determining ground surface from airborne laser scanning data

Kalev Julge, Artu Ellmann, Anti Gruno

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 8, Issue 1, 083573 (August 2014). https://doi.org/10.1117/1.JRS.8.083573

Abstract

Numerous filtering algorithms have been developed in order to distinguish the ground surface from nonground points acquired by airborne laser scanning. These algorithms automatically attempt to determine the ground points using various features such as predefined parameters and statistical analysis. Their efficiency also depends on landscape characteristics. The aim of this contribution is to test the performance of six common filtering algorithms embedded in three freeware programs. The algorithms’ adaptive TIN, elevation threshold with expand window, maximum local slope, progressive morphology, multiscale curvature, and linear prediction were tested on four relatively large (4 to 8 km²) and diverse landscape areas, which included steep sloped hills, urban areas, ridge-like eskers, and a river valley. The results show that in diverse test areas each algorithm yields various commission and omission errors. It appears that adaptive TIN is suitable in urban areas while the multiscale curvature algorithm is best suited in wooded areas. The multiscale curvature algorithm yielded the overall best results with average root-mean-square error values of 0.35 m.

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Kalev Julge, Artu Ellmann, and Anti Gruno "Performance analysis of freeware filtering algorithms for determining ground surface from airborne laser scanning data," Journal of Applied Remote Sensing 8(1), 083573 (8 August 2014). https://doi.org/10.1117/1.JRS.8.083573

Published: 8 August 2014

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