A Merging Solution for Close-Range DEMs to Optimize Surface Coverage and Measurement Resolution

Abstract

The process of efficient and effective DEM merging is increasingly becoming more important. To allow DEM analysis for features of different scales, an increase in surface coverage cannot result in reduced measurement resolution. It is thus inevitable that merging individual high-resolution DEMs will become common practice for applications such as hydraulic roughness studies for fluvial surfaces. This paper presents an efficient and effective merging solution, whereby accurate co-registration of individual DEMs collected from consistent viewpoints and standard averaging for overlapping elevations ensure seamless merging. The presented method is suitable for DEMs collected using any measurement technology, as long as individual DEMs overlap and are arranged on regular grids. The merging solution is applied to the study of a laboratory gravel bed measured with vertical stereo photogrammetry at the grain scale (>106 points/m2). We show that the approach can be integrated into the DEM collection workflow at the design stage, which optimizes the measurement performance. We present how resampling before merging can be beneficial to keep data handling requirements practical, whilst ensuring accurate surface representation. Finally, the effect of scale variation is studied, showing that seamless merging applies to DEMs with variable resolution.