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Methodology for Road Defect Detection and Administration Based on Mobile Mapping Data

Computer Modeling in Engineering & Sciences 2021年第10期129卷 207-226页

作者： Marina Davidovic Tatjana Kuzmic Dejan Vasic Valentin Wich ansgar brunn Vladimir Bulatovic Department for Civil Engineering and Geodesy Faculty of Technical SciencesUniversity of Novi SadNovi Sad21000Serbia University of Applied Sciences Wurzburg-Schweinfurt W urzburg-Schweinfurt97070Germany

A detailed inspection of roads requires highly detailed spatial data with sufficient precision to deliver an accurate geometry and to describe road defects *** paper presents a novel method for the detection of road *** input data for road defect detection included point clouds and orthomosaics gathered by mobile mapping *** defects were categorized in three major groups with the following geometric primitives:points,lines and *** method suggests the detection of point objects from matched point clouds,panoramic images and ortho *** were mapped as point,line or polygon geometries,directly derived from orthomosaics and panoramic *** the geometric position of road defects,all objects were assigned to a variety of attributes:defect type,surface material,center-of-gravity,area,length,corresponding image of the defect and degree of damage.A spatial dataset comprising defect values with a matching data type was created to perform the attribute analysis quickly and *** final product is a spatial vector data set,consisting of points,lines and polygons,which contains attributes with further information and *** paper demonstrates that mobile mapping suits a large-scale feature extraction of road infrastructure *** its simplicity and flexibility,the presented methodology allows it to be easily adapted to extract further feature types with their *** makes the proposed approach a vital tool for data extraction settings with multiple mobile mapping data analysts,e.g.,offline crowdsourcing.

关键词： Deformation detection engineering visual inspection data analyses mobile mapping GIS

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