Uav Photogrammetry: Block Triangulation Comparisons

Gini, Rossana; Pagliari, Diana; Passoni, D.; Pinto, Livio; Sona, Giovanna; Dosso, Paolo

doi:10.5194/isprsarchives-xl-1-w2-157-2013

Cited by 50 publications

(28 citation statements)

References 8 publications

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“…The next phase of the work was the processing of the on site acquired data; the images of the different flights were processed in several blocks with the software Pix4D Mapper (Gini et al, 2013;Ostrowski & Hanus 2016;Rodrigues et al, 2016). As previously reported, we decided to use a specific product for our evaluations about the main topic of this article, then the processes of all the seven projects were stopped at the phase of point cloud generation (no other products such as meshes or ortophotos were created in this phase).…”

Section: Processing Workflow With Pix4dmentioning

confidence: 99%

THE INFLUENCE OF FLIGHT PLANNING AND CAMERA ORIENTATION IN UAVs PHOTOGRAMMETRY. A TEST IN THE AREA OF ROCCA SAN SILVESTRO (LI), TUSCANY

Chiabrando

Lingua

Maschio

et al. 2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:The purpose of this paper is to discuss how much the phases of flight planning and the setting of the camera orientation can affect a UAVs photogrammetric survey. The test site chosen for these evaluations was the Rocca of San Silvestro, a medieval monumental castle near Livorno, Tuscany (Italy). During the fieldwork, different sets of data have been acquired using different parameters for the camera orientation and for the set up of flight plans. Acquisition with both nadiral and oblique orientation of the camera have been performed, as well as flights with different direction of the flight lines (related with the shape of the object of the survey). The different datasets were then processed in several blocks using Pix4D software and the results of the processing were analysed and compared. Our aim was to evaluate how much the parameters described above can affect the generation of the final products of the survey, in particular the product chosen for this evaluation was the point cloud.

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Section: Processing Workflow With Pix4dmentioning

confidence: 99%

THE INFLUENCE OF FLIGHT PLANNING AND CAMERA ORIENTATION IN UAVs PHOTOGRAMMETRY. A TEST IN THE AREA OF ROCCA SAN SILVESTRO (LI), TUSCANY

Chiabrando

Lingua

Maschio

et al. 2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…PhotoScan was selected according to [37] and [38], who demonstrated that it provides the most reliable results among existing softwares based on Structure from Motion algorithms. For each flight, between 5 to 12 ground control points (GCP) were identified on the Google Earth image ( Figure 1) and used in PhotoScan to get the absolute coordinates of the DPC.…”

Section: Point Cloud Derived From Overlapping Rgb Imagesmentioning

confidence: 99%

Using 3D Point Clouds Derived from UAV RGB Imagery to Describe Vineyard 3D Macro-Structure

2017

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Abstract:In the context of precision viticulture, remote sensing in the optical domain offers a potential way to map crop structure characteristics, such as vegetation cover fraction, row orientation or leaf area index, that are later used in decision support tools. A method based on the RGB color model imagery acquired with an unmanned aerial vehicle (UAV) is proposed to describe the vineyard 3D macro-structure. The dense point cloud is first extracted from the overlapping RGB images acquired over the vineyard using the Structure from Motion algorithm implemented in the Agisoft PhotoScan software. Then, the terrain altitude extracted from the dense point cloud is used to get the 2D distribution of height of the vineyard. By applying a threshold on the height, the rows are separated from the row spacing. Row height, width and spacing are then estimated as well as the vineyard cover fraction and the percentage of missing segments along the rows. Results are compared with ground measurements with root mean square error (RMSE) = 9.8 cm for row height, RMSE = 8.7 cm for row width and RMSE = 7 cm for row spacing. The row width, cover fraction, as well as the percentage of missing row segments, appear to be sensitive to the quality of the dense point cloud. Optimal flight configuration and camera setting are therefore mandatory to access these characteristics with a good accuracy.

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“…무인항공사진측량의 정확도 수준이 기존의 전문적인 항 공사진측량에 버금가는지 여부에 관한 최근의 연구들은 확실한 결론을 내리지 못하고 있다 (Vallet et al 2011;Gini et al 2013;Colomina and Molina 2014 (Fig. 4(a)).…”

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A Preliminary Study on UAV Photogrammetry for the Hyanho Coast Near the Military Reservation Zone, Eastern Coast of Korea

Kim¹,

Yun²,

Chang³

et al. 2017

Ocean and Polar Research

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: To evaluate the accuracy of UAV photogrammetry for Hyangho coast, eastern coast of Korea, we conducted a field experiment wherein UAV photogrammetry test was repeated three times. Since the Haygho coast is located within a military reservation zone, it was necessary to obtain permission to gain access to the beach and to have sensitive aerial photographs showing military facilities inspected and cropped. The standard deviation of the UAV shooting position between the three tests was less than 1 m, but repeatability of footprint on the ground was low due to wind-driven variability of the UAV pose. Selfcalibrating bundle adjustment(SCBA) of implementing non-metric camera calibration was failed in one test. In two tests, the vertical error was twice as large as the pixel size except for those areas that were subject to security inspection and cropping. Given the problems that can arise with regard to the repeatability of the shooting area as well as the possibility of failure with regard to SCBA, we strongly recommend that UAV photogrammetry in coastal areas needs to be repeated at least twice.

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Uav Photogrammetry: Block Triangulation Comparisons

Cited by 50 publications

References 8 publications

THE INFLUENCE OF FLIGHT PLANNING AND CAMERA ORIENTATION IN UAVs PHOTOGRAMMETRY. A TEST IN THE AREA OF ROCCA SAN SILVESTRO (LI), TUSCANY

THE INFLUENCE OF FLIGHT PLANNING AND CAMERA ORIENTATION IN UAVs PHOTOGRAMMETRY. A TEST IN THE AREA OF ROCCA SAN SILVESTRO (LI), TUSCANY

Using 3D Point Clouds Derived from UAV RGB Imagery to Describe Vineyard 3D Macro-Structure

A Preliminary Study on UAV Photogrammetry for the Hyanho Coast Near the Military Reservation Zone, Eastern Coast of Korea

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