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A Modeling Approach for Predicting the Resolution Capability in Terrestrial Laser Scanning

Authors :
Wieser, Sukant Chaudhry
David Salido-MonzĂș
Andreas
Source :
Remote Sensing; Volume 13; Issue 4; Pages: 615
Publication Year :
2021
Publisher :
Multidisciplinary Digital Publishing Institute, 2021.

Abstract

The minimum size of objects or geometrical features that can be distinguished within a laser scanning point cloud is called the resolution capability (RC). Herein, we develop a simple analytical expression for predicting the RC in angular direction for phase-based laser scanners. We start from a numerical approximation of the mixed-pixel bias which occurs when the laser beam simultaneously hits surfaces at grossly different distances. In correspondence with previous literature, we view the RC as the minimum angular distance between points on the foreground and points on the background which are not (severely) affected by a mixed-pixel bias. We use an elliptical Gaussian beam for quantifying the effect. We show that the surface reflectivities and the distance step between foreground and background have generally little impact. Subsequently, we derive an approximation of the RC and extend it to include the selected scanning resolution, that is, angular increment. We verify our model by comparison to the resolution capabilities empirically determined by others. Our model requires parameters that can be taken from the data sheet of the scanner or approximated using a simple experiment. We describe this experiment herein and provide the required software on GitHub. Our approach is thus easily accessible, enables the prediction of the resolution capability with little effort and supports assessing the suitability of a specific scanner or of specific scanning parameters for a given application.

Details

Language :
English
ISSN :
20724292
Database :
OpenAIRE
Journal :
Remote Sensing; Volume 13; Issue 4; Pages: 615
Accession number :
edsair.multidiscipl..59fa6f45aa796ec547f445cef5150274
Full Text :
https://doi.org/10.3390/rs13040615