Comparative use of PPK-integrated close-range terrestrial photogrammetry and a handheld mobile laser scanner in the measurement of forest road surface deformation

Eker, Remzi

doi:10.1016/j.measurement.2022.112322

Cited by 15 publications

(17 citation statements)

References 71 publications

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“…Both SfM photogrammetry and MLS showed satisfactory results in the measurement of rutting and soil displacement [98,99]. Both techniques were used by Marra et al [98] to assess soil rutting after the passage of the same forestry-fitted farm tractor while skidding and forwarding logs; for both extraction techniques there were no significant differences between the results obtained via SfM and MLS.…”

Section: Monitoring Environmental Sustainability Of Forest Operationsmentioning

confidence: 99%

“…On the other hand, data acquisition time with MLS is much more rapid than with photogrammetry. Eker reported 30 min for an MLS survey on a 120 m unpaved forest road established in 2021 in eastern Turkey, whereas to perform the same task with photogrammetry, up to two hours were needed [99]. MLS is a more complex technique than photogrammetry, and therefore the skill of the operator is a crucial parameter; indeed, it is important to keep the instrument in the same direction during scanning, to allow the SLAM (Simultaneous localisation and mapping) algorithm to perform reliable positioning of the point cloud [99].…”

Section: Monitoring Environmental Sustainability Of Forest Operationsmentioning

confidence: 99%

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Recent Applications of Smart Technologies for Monitoring the Sustainability of Forest Operations

Venanzi

Latterini

Civitarese

et al. 2023

Forests

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Precision forestry is a useful technique to help forest stakeholders with proper sustainable forest management. Modern sensors and technologies, with special reference to the sustainability of forest operations, can be applied on a variety of levels, including the monitoring of forest activities regarding the three pillars (economy, environment, and society). In this review, we summarised the current level of knowledge regarding the use of precision forestry techniques for monitoring forest operations. We concentrated on recent data from the last five years (2019–2023). We demonstrated how an Industry 4.0 strategy for remote and proximal monitoring of working performance can be effective when using CAN-bus and StanForD data collected by modern forest machines. The same information can be effectively used to create maps of soil trafficability and to evaluate the patterns of skid tracks or strip roads built as a result of forest intervention. Similar information can be gathered in the case of small-scale forestry by using GNSS-RF (Global Navigation Satellite Systems—Radio Frequency) or even monitoring systems based on smartwatches or smartphones. LiDAR and Structure for Motion (SfM) photogrammetry are both useful tools for tracking soil rutting and disturbances caused by the passage of forest machinery. SfM offers denser point clouds and a more approachable method, whereas laser scanning can be considerably faster but needs a more experienced operator and better data-processing skills. Finally, in terms of the social component of sustainability, the use of location sharing technologies is strongly advised, based for instance on GNSS—RF to monitor the security of forest workers as they operate.

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Section: Monitoring Environmental Sustainability Of Forest Operationsmentioning

confidence: 99%

Section: Monitoring Environmental Sustainability Of Forest Operationsmentioning

confidence: 99%

Recent Applications of Smart Technologies for Monitoring the Sustainability of Forest Operations

Venanzi

Latterini

Civitarese

et al. 2023

Forests

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“…The point cloud distance is a fundamental index of the accuracy of a point cloud model, and the M3C2 algorithm is adopted to calculate the distance between the established point cloud model and the reference ones, which enables the calculation of the distance between two point cloud models [37]. The flow of the M3C2 algorithm is shown in Figure 9 and it mainly involves core point calculation, point cloud normal vector fitting, point cloud distance calculation and roughness analysis calculation.…”

Section: B M3c2 Algorithmmentioning

confidence: 99%

Defect Detection and Recognition of Crane Girder Structure Based on 3D Reconstruction of UAV

Liu,

Yu,

Liang

et al. 2023

IEEE Access

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The traditional detection process of deformation or crack of crane main girder structure is tedious, inefficient and difficult to control safety risk. In this work, combining unmanned aerial vehicle (UAV) images with photogrammetry technology, an efficient and high-precision method for crane main girder defect detection and identification based on UAV 3D reconstruction is proposed. Firstly, the flight path, suitable for the chamfered rectangular section is selected, according to the structural characteristics of the main girder and the flight requirements of the UAV photography, and the calculation equation of flight strategy parameters is deduced. Secondly, based on 3D reconstruction methods and crucial techniques, the influence of image number, marker points and structure size effects on the accuracy of 3D reconstruction model are investigated, separately, thus comprehensively verifying the accuracy of the 3D reconstructed model. Finally, the proposed method is tested and evaluated by the experiments for deformation detection of crane main girder structure and crack identification of scaled carton, obtaining millimeter-level accurate results, and the high precision deformation detection and crack identification using non-contact 3D reconstruction are realized. The results demonstrate that the combination of UAV and photogrammetry show potential in the deformation detection of crane main girder structure, it also has a prospect in accurately evaluating the geometry of cracks and helping structural engineers to assess the health status of structures.INDEX TERMS Crane, UAV, 3D reconstruction, point cloud model, deformation, crack identification.

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“…Researchers have explored the potential of mobile handheld laser scanners in assessing external structures influencing the quality of wood in trees [32]. These technologies have been employed to compare various scanning approaches, including SLAM-based HMLS called TORCH, and close-range terrestrial photogrammetry for measuring surface deformation on forest roads [33]. Garden settings have been the subject of extensive laser scanning studies, evaluating both static TLS and mobile laser scanning (MLS), utilizing equipment such as the Focus 3D S120 and the Leica BLK2GO [34].…”

Section: Introductionmentioning

confidence: 99%

Prompt Mapping Tree Positions with Handheld Mobile Scanners Based on SLAM Technology

Chudá,

Výbošťok,

Tomaštík

et al. 2024

Land

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In this study, we evaluated the performance of GeoSLAM ZEB Horizon and Stonex X120GO SLAM handheld mobile laser scanners (HMLS) to address two primary objectives. First, we aimed to assess and compare the accuracy of positioning achieved using HMLS instruments. Second, we sought to investigate the influencing factors and their impact on estimation accuracies. The factors influencing the accuracy of positioning in HMLS Simultaneous Localization and Mapping-aided solutions were defined, considering the scanner type, distance from the trajectory, forest structure, tree species, and Diameter at Breast Height. The same type of trajectory was tested in five different stand structures. The evaluation of GeoSLAM HMLS point clouds yielded an average positional RMSE of 17.91 cm, while the data extracted from the Stonex HMLS resulted in an average positional RMSE of 17.33 cm. These results underscore the significant potential of HMLS technology in addressing the critical need for precise positioning data in various applications, from forestry management to environmental monitoring, wildlife habitat assessment, and climate change studies. By harnessing the power of handheld mobile laser scanners, our research aims to enhance the accuracy and efficiency of geospatial data capture in challenging.

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Comparative use of PPK-integrated close-range terrestrial photogrammetry and a handheld mobile laser scanner in the measurement of forest road surface deformation

Cited by 15 publications

References 71 publications

Recent Applications of Smart Technologies for Monitoring the Sustainability of Forest Operations

Recent Applications of Smart Technologies for Monitoring the Sustainability of Forest Operations

Defect Detection and Recognition of Crane Girder Structure Based on 3D Reconstruction of UAV

Prompt Mapping Tree Positions with Handheld Mobile Scanners Based on SLAM Technology

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