Next Article in Journal
Evaluating and Optimizing Urban Green Spaces for Compact Urban Areas: Cukurova District in Adana, Turkey
Next Article in Special Issue
Saddle Position-Based Method for Extraction of Depressions in Fengcong Areas by Using Digital Elevation Models
Previous Article in Journal
Integrated Participatory and Collaborative Risk Mapping for Enhancing Disaster Resilience
Previous Article in Special Issue
An Automated Processing Algorithm for Flat Areas Resulting from DEM Filling and Interpolation
Article Menu
Issue 2 (February) cover image

Export Article

Open AccessArticle
ISPRS Int. J. Geo-Inf. 2018, 7(2), 69; doi:10.3390/ijgi7020069

Roughness Spectra Derived from Multi-Scale LiDAR Point Clouds of a Gravel Surface: A Comparison and Sensitivity Analysis

1
Department of Geodesy and Geoinformation (GEO), Technische Universität Wien (TU Wien), Gußhausstraße 27-29, 1040 Vienna, Austria
2
Institute for Photogrammetry, University of Stuttgart, Geschwister-Scholl-Str. 24D, 70174 Stuttgart, Germany
*
Author to whom correspondence should be addressed.
Received: 29 November 2017 / Revised: 7 February 2018 / Accepted: 18 February 2018 / Published: 22 February 2018
(This article belongs to the Special Issue Leading Progress in Digital Terrain Analysis and Modeling)
View Full-Text   |   Download PDF [9026 KB, uploaded 23 February 2018]   |  

Abstract

The roughness spectrum (i.e., the power spectral density) is a derivative of digital terrain models (DTMs) that is used as a surface roughness descriptor in many geomorphological and physical models. Although light detection and ranging (LiDAR) has become one of the main data sources for DTM calculation, it is still unknown how roughness spectra are affected when calculated from different LiDAR point clouds, or when they are processed differently. In this paper, we used three different LiDAR point clouds of a 1 m × 10 m gravel plot to derive and analyze the roughness spectra from the interpolated DTMs. The LiDAR point clouds were acquired using terrestrial laser scanning (TLS), and laser scanning from both an unmanned aerial vehicle (ULS) and an airplane (ALS). The corresponding roughness spectra are derived first as ensemble averaged periodograms and then the spectral differences are analyzed with a dB threshold that is based on the 95% confidence intervals of the periodograms. The aim is to determine scales (spatial wavelengths) over which the analyzed spectra can be used interchangeably. The results show that one TLS scan can measure the roughness spectra for wavelengths larger than 1 cm (i.e., two times its footprint size) and up to 10 m, with spectral differences less than 0.65 dB. For the same dB threshold, the ULS and TLS spectra can be used interchangeably for wavelengths larger than about 1.2 dm (i.e., five times the ULS footprint size). However, the interpolation parameters should be optimized to make the ULS spectrum more accurate at wavelengths smaller than 1 m. The plot size was, however, too small to draw particular conclusions about ALS spectra. These results show that novel ULS data has a high potential to replace TLS for roughness spectrum calculation in many applications. View Full-Text
Keywords: laser scanning; UAV; surface interpolation; power spectral density; spectral slope; gravel roughness laser scanning; UAV; surface interpolation; power spectral density; spectral slope; gravel roughness
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Supplementary material

Share & Cite This Article

MDPI and ACS Style

Milenković, M.; Ressl, C.; Karel, W.; Mandlburger, G.; Pfeifer, N. Roughness Spectra Derived from Multi-Scale LiDAR Point Clouds of a Gravel Surface: A Comparison and Sensitivity Analysis. ISPRS Int. J. Geo-Inf. 2018, 7, 69.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
ISPRS Int. J. Geo-Inf. EISSN 2220-9964 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top