4.5 Article

Field application of close-range digital photogrammetry (CRDP) for grain-scale fluvial morphology studies

期刊

EARTH SURFACE PROCESSES AND LANDFORMS
卷 41, 期 10, 页码 1358-1369

出版社

WILEY
DOI: 10.1002/esp.3906

关键词

fieldwork; gravel-bed river; photogrammetry; DEM; grain roughness

资金

  1. Marsden Fund [UOA1412]

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In situ measurement of grain-scale fluvial morphology is important for studies on grain roughness, sediment transport and the interactions between animals and the geomorphology, topics relevant to many river practitioners. Close-range digital photogrammetry (CRDP) and terrestrial laser scanning (TLS) are the two most common techniques to obtain high-resolution digital elevation models (DEMs) from fluvial surfaces. However, field application of topography remote sensing at the grain scale is presently hindered mainly by the tedious workflow challenges that one needs to overcome to obtain high-accuracy elevation data. A recommended approach for CRDP to collect high-resolution and high-accuracy DEMs has been developed for gravel-bed flume studies. The present paper investigates the deployment of the laboratory technique on three exposed gravel bars in a natural river environment. In contrast to other approaches, having the calibration carried out in the laboratory removes the need for independently surveyed ground-control targets, and makes for an efficient and effective data collection in the field. Optimization of the gravel-bed imagery helps DEM collection, without being impacted by variable lighting conditions. The benefit of a light-weight three-dimensional printed gravel-bed model for DEM quality assessment is shown, and confirms the reliability of grain roughness data measured with CRDP. Imagery and DEM analysis evidences sedimentological contrasts between gravel bars within the reach. The analysis of the surface elevations shows the effect variable grain-size and sediment sorting have on the surface roughness. By plotting the two-dimensional structure functions and surface slopes and aspects we identify different grain arrangements and surface structures. The calculation of the inclination index allows determining the surface-forming flow direction(s). We show that progress in topography remote sensing is important to extend our knowledge on fluvial morphology processes at the grain scale, and how a technique customized for use by fluvial geomorphologists in the field benefits this progress. Copyright (c) 2016 John Wiley & Sons, Ltd.

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