Abstract
A method of extracting bare-earth points from photogrammetric point clouds by partially using an existing lower resolution digital terrain model (DTM) is presented. The bare-earth points are extracted based on a threshold defined by local slope. The local slope is estimated from the lower resolution DTM. A gridded DTM is then interpolated from the extracted bare-earth points. Five different interpolation algorithms are implemented and evaluated to identify the most suitable interpolation method for such non-uniformly scattered data. The algorithm is tested on four test sites with varying topographic and ground cover characteristics. The results are evaluated against a reference DTM created using aerial laser scanning. The deviations of the extracted bare-earth points, and the interpolated DTM, from the reference DTM increases with increasing forest canopy density and terrain roughness. The DTM created by the method is significantly closer to the reference DTM than the lower resolution national DTM. The ANUDEM (Australian National University Digital Elevation Modelling) interpolation method is found to be the best performing interpolation method in terms of reducing the deviations and in terms of modelling the terrain realistically with minimum artefacts, although the differences among the interpolation methods are not considerably large.
Highlights
Photogrammetry has long been limited by technological difficulties in acquiring dense 3D topographic data
Such constraints make ground filtering algorithms used in ALS inapplicable of filtering photogrammetric point clouds, at least without modifications
The Photogrammetric point clouds: The aerial images were acquired with radiometric resolution of 12 bit and ground sampling distance (GSD) of 35 cm with 60% along- and 20% across-track overlap
Summary
Photogrammetry has long been limited by technological difficulties in acquiring dense 3D topographic data. Behind each discriminant function lies an assumption or a model of some attributes of the terrain such as elevation, slope, curvature, etc Such assumption is often made based on the point clouds themselves making the problem somewhat ill-posed. Photogrammetry is typically constrained under those conditions Such constraints make ground filtering algorithms used in ALS inapplicable of filtering photogrammetric point clouds, at least without modifications. A priori information about the local terrain might help improve the ground filtering in photogrammetry One interesting such information is low resolution DTM that often exists at national level in many countries with varying qualities. The algorithm uses a lower resolution national DTM to model the local terrain on which the extraction of the ground points is based. The study investigates the performances of some interpolation methods in creating gridded DTM from the extracted ground points
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