A1 Refereed original research article in a scientific journal
3D Modeling of Coarse Fluvial Sediments Based on Mobile Laser Scanning Data
Authors: Yunsheng Wang, Xinlian Liang, Claude Flener, Antero Kukko, Harri Kaartinen, Matti Kurkela, Matti Vaaja, Hannu Hyyppä, Petteri Alho
Publisher: MDPI
Publication year: 2013
Journal: Remote Sensing
Journal acronym: Remote Sens.
Volume: 5
Issue: 9
First page : 4571
Last page: 4592
Number of pages: 22
ISSN: 2072-4292
eISSN: 2072-4292
DOI: https://doi.org/10.3390/rs5094571
Abstract
High quality sedimentary measurements are required for studying fluvial geomorphology and hydrological processes e.g., flood and river dynamics. Mobile laser scanning (MLS) currently provides the opportunity to achieve high precision measurements of coarse fluvial sediments in a large survey area. Our study aims to investigate the capability of single-track MLS data for individual particle-based sediment modeling. Individual particles are firstly detected and delineated from a digital surface model (DSM) that is generated from the MLS data. 3D MLS points of each detected individual particle are then extracted from the point cloud. The grain size and the sphericity as well as the orientation of each individual particle are estimated based on the extracted MLS points. According to the evaluations conduced in the paper, it is possible to detect and to model sediment particles above 63 mm from a single-track MLS point cloud with a high reliability. The paper further discusses the strength and the challenges of individual particle-based approach for sedimentary measurement.
High quality sedimentary measurements are required for studying fluvial geomorphology and hydrological processes e.g., flood and river dynamics. Mobile laser scanning (MLS) currently provides the opportunity to achieve high precision measurements of coarse fluvial sediments in a large survey area. Our study aims to investigate the capability of single-track MLS data for individual particle-based sediment modeling. Individual particles are firstly detected and delineated from a digital surface model (DSM) that is generated from the MLS data. 3D MLS points of each detected individual particle are then extracted from the point cloud. The grain size and the sphericity as well as the orientation of each individual particle are estimated based on the extracted MLS points. According to the evaluations conduced in the paper, it is possible to detect and to model sediment particles above 63 mm from a single-track MLS point cloud with a high reliability. The paper further discusses the strength and the challenges of individual particle-based approach for sedimentary measurement.
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