SENSOR INTEGRATION AND APPLICATION OF LOW-SIZED MOBILE MAPPING PLATFORM EQUIPPED WITH LIDAR, GPR AND PHOTOGRAMMETRIC SENSORS

Author:

Bakuła K.,Lejzerowicz A.,Pilarska-Mazurek M.,Ostrowski W.,Górka J.,Biernat P.,Czernic P.,Załęgowski K.,Kleszczewska K.,Węzka K.,Gąsiewski M.,Dmowski H.,Styś N.

Abstract

Abstract. The article aims to analyse the possibilities of GPR, LiDAR, and photogrammetric sensors integration in a specific application, considering the various combination of sensor and their parameters. This text also discusses the possibility of using LiDAR sensors in a low-sized mobile platform for the inventory of the road lane in a dense urban area. The text presents the opportunities and recommendations of GPR and LiDAR sensors for their selection and the possibility of using them. In the case of LiDAR and photogrammetric data, two planned applications were indicated: platform georeferencing and mapping. The accuracy and noise of the Livox Avia LiDAR sensor and point cloud obtained from the Sony A7R camera with image-matching were analysed for a surface inventory. Despite the sufficient density and detail of the data, the intensity distinguishing different surfaces, the noise of LiDAR data at the level of 2 cm was too high to do the inventory of minor damages and analyse road surfaces. Higher accuracy was achieved at the level of 1 cm for photogrammetric point clouds. The article also presents the concept of integrating multi-source data visualised into the form of an oriented point cloud showing both what is above and below the earth's surface, which enables the synergy effect and joint analysis of data with entirely different characteristics.

Publisher

Copernicus GmbH

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Energy Efficiency in Agricultural Production—Experience from Land Consolidation in Poland and Finland;Energies;2023-11-15

2. SELECTED QUALITATIVE ASPECTS OF LIDAR POINT CLOUDS: GEOSLAM ZEB-REVO AND FARO FOCUS 3D X130;The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences;2023-10-19

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