Quantifying the scales of spatial variation in gravel beds using terrestrial and airborne laser scanning data

3Citations
Citations of this article
7Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Previous studies measured gravel bed surfaces by terrestrial laser scanning (TLS) and close-range photogrammetry suggested the presence of at least two different scales of spatial variation in gravel bed surfaces. This study investigated the spatial variation of airborne laser scanning (ALS) point clouds acquired in gravel bed. Due to the large footprint of ALS systems, a smoother surface is expected, but there exists some uncertainty over the precise scale of ALS measurement (hereafter referred to as the spatial support). As a result, we applied the regularization method, which is a variogram upscaling approach, to investigate the true support of ALS data. The regularization results suggested that the gravel bed surface described by the ALS is much smoother than expected in terms of the ALS reported measurement scale. Moreover, we applied the factorial kriging (FK) method, which allows mapping of different scales of variation present in the data separately (different from ordinary kriging which produces a single map), to obtain the river bed topography at each scale of spatial variation. We found that the short-range and long-range FK maps of the TLS-derived DSMs were able to highlight the edges of gravels and clusters of gravels, respectively. The long-range FK maps of the ALS data shows a pattern of gravel-bed clusters and aggregations of gravels. However, the short-range FK maps of the ALS data produced noisy maps, due to the smoothing effect. This analysis, thus, shows clearly that ALS data may be insufficient for geomorphological and hydraulic engineering applications that require the resolution of individual gravels.

References Powered by Scopus

Analysis of LiDAR-derived topographic information for characterizing and differentiating landslide morphology and activity

435Citations
N/AReaders
Get full text

Quantifying submerged fluvial topography using hyperspatial resolution UAS imagery and structure from motion photogrammetry

336Citations
N/AReaders
Get full text

The effectiveness of airborne LiDAR data in the recognition of channel-bed morphology

232Citations
N/AReaders
Get full text

Cited by Powered by Scopus

GRAINet: Mapping grain size distributions in river beds from UAV images with convolutional neural networks

34Citations
N/AReaders
Get full text

Madograms help to quantify mountain frontal zones—An approach towards comparative spatial analysis of complex landforms

2Citations
N/AReaders
Get full text

A method for segmentation of pebble images in the presence of shadows

0Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Huang, G. H., Atkinson, P. M., & Wang, C. K. (2018). Quantifying the scales of spatial variation in gravel beds using terrestrial and airborne laser scanning data. Open Geosciences, 10(1), 607–617. https://doi.org/10.1515/geo-2018-0048

Readers over time

‘18‘19‘20‘21‘2300.511.52

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 3

60%

Lecturer / Post doc 1

20%

Researcher 1

20%

Readers' Discipline

Tooltip

Earth and Planetary Sciences 2

40%

Environmental Science 1

20%

Arts and Humanities 1

20%

Engineering 1

20%

Save time finding and organizing research with Mendeley

Sign up for free
0