FU-CHUN WUWang C.-KLo H.P.2022-04-252022-04-25202118650473https://www.scopus.com/inward/record.uri?eid=2-s2.0-85110286067&doi=10.1007%2fs12145-021-00660-z&partnerID=40&md5=065408a1f451345ebfbf8c581e6b7f6ehttps://scholars.lib.ntu.edu.tw/handle/123456789/605813The grain size distribution (GSD) of a river bed is fundamental information required for studies of fluvial, morphological, and ecological processes. To achieve higher efficiency, numerous efforts have been devoted to developing the techniques of automated grain sizing. These techniques can be categorized as the image-based or topography-based approach according to the input data used. Each category is further subdivided into three groups based on the output result, namely: individual GSD, statistical GSD, or characteristic grain sizes. Existing software for automated grain sizing covers the image-based approaches for all three types of output, and topography-based approaches for statistical GSD and characteristic grain sizes. To date, however, no software has been developed that uses 3D topographic data to delineate individual grains and estimate their GSD. Here, we present a first-ever topography-based software tool, FKgrain, for automated grain segmentation and sizing. FKgrain adopts factorial kriging to decompose the grain-scale component of digital elevation model (DEM), whose zero-level contours are then used as the input for morphological grain segmentation. FKgrain exports the shapefiles of the delineated grains and their ellipse fits, whose minor axes can be used to derive the individual GSD. An application example demonstrates that FKgrain is efficient in producing useful results that are comparable to those obtained by traditional, time-consuming and laborious manual digitization of grain images. ? 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.Digital elevation model (DEM)Factorial kriging (FK)Grain size distribution (GSD)Morphological grain segmentationkrigingriver bedsegmentationsize distributionsoftwaretopographyVenustaconcha ellipsiformisjournal article10.1007/s12145-021-00660-z2-s2.0-85110286067