Size, shape and orientation matter: fast and semi-automatic measurement of grain geometries from 3D point clouds

[摘要] The grain-scale morphology and size distribution ofsediments are important factors controlling the erosion efficiency, sediment transport and the aquatic ecosystem quality. In turn, characterizing thespatial evolution of grain size and shape can help understand the dynamicsof erosion and sediment transport in coastal, hillslope and fluvialenvironments. However, the size distribution of sediments is generallyassessed using insufficiently representative field measurements, anddetermining the grain-scale shape of sediments remains a real challenge ingeomorphology. Here we determine the size distribution and grain-scale shapeof sediments located in coastal and river environments with a newmethodology based on the segmentation and geometric fitting of 3D pointclouds. Point cloud segmentation of individual grains is performed using awatershed algorithm applied here to 3D point clouds. Once the grains aresegmented into several sub-clouds, each grain-scale morphology is determinedby fitting a 3D geometrical model applied to each sub-cloud. If differentgeometrical models can be tested, this study focuses mostly on ellipsoids todescribe the geometry of grains. G3Point is a semi-automatic approach thatrequires a trial-and-error approach to determine the best combination ofparameter values. Validation of the results is performed either by comparingthe obtained size distribution to independent measurements (e.g., handmeasurements) or by visually inspecting the quality of the segmented grains.The main benefits of this semi-automatic and non-destructive method are thatit provides access to (1) an un-biased estimate of surface grain-sizedistribution on a large range of scales, from centimeters to meters; (2) avery large number of data, mostly limited by the number of grains in thepoint cloud data set; (3) the 3D morphology of grains, in turn allowing thedevelopment of new metrics that characterize the size and shape of grains;and (4) the in situ orientation and organization of grains. The main limit ofthis method is that it is only able to detect grains with a characteristicsize significantly greater than the resolution of the point cloud.

[学科分类] 土壤学