Parameter optimization for creating reliable photogrammetric models in emergency scenarios

Gagliolo, S.; Fagandini, Roberta; Passoni, D.; Federici, Bianca; Ferrando, Ilaria; Pagliari, Diana; Pinto, Livio; Sguerso, Domenico

doi:10.1007/s12518-018-0224-4

Cited by 20 publications

(11 citation statements)

References 22 publications

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“…It ensured that all the flights were achieved along the same path and under the same conditions, e.g., cruising speed (4.0 m/s) and altitude (100 m AGL , above ground level) (Figure 3). Missions were planned to obtain an average Ground Sampling Distance (GSD) of 0.043 m/pix, a forward and side overlaps of 85% and 75%, respectively, as suggested by [42] and [43]. A total of 77 images per flight were acquired.…”

Section: Field Data Campaigns and Operative Workflowmentioning

confidence: 99%

Combining Interior Orientation Variables to Predict the Accuracy of Rpas–Sfm 3D Models

et al. 2020

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Remotely piloted aerial systems (RPAS) have been recognized as an effective low-cost tool to acquire photogrammetric data of low accessible areas reducing collection and processing time. Data processing techniques like structure from motion (SfM) and multiview stereo (MVS) techniques, can nowadays provide detailed 3D models with an accuracy comparable to the one generated by other conventional approaches. Accuracy of RPAS-based measures is strongly dependent on the type of adopted sensors. Nevertheless, up to now, no investigation was done about relationships between camera calibration parameters and final accuracy of measures. In this work, authors tried to fill this gap by exploring those dependencies with the aim of proposing a prediction function able to quantify the potential final error in respect of camera parameters. Predictive functions were estimated by combining multivariate and linear statistical techniques. Four photogrammetric RPAS acquisitions were considered, supported by ground surveys, to calibrate the predictive model while a further acquisition was used to test and validate it. Results are preliminary, but promising. The calibrated predictive functions relating camera internal orientation (I.O.) parameters with final accuracy of measures (root mean squared error) showed high reliability and accuracy.

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Section: Field Data Campaigns and Operative Workflowmentioning

confidence: 99%

Combining Interior Orientation Variables to Predict the Accuracy of Rpas–Sfm 3D Models

et al. 2020

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“…Finally, choosing once again a "medium" quality, the dense cloud could be computed through a Metashape command called "Build dense cloud" based on a computation of the collinearity equations system. With a computational time of about five hours, the final output was a 6.042.252 points dense cloud (Figure 2) with an 9mm accuracy; the "medium" quality represents a compromise between a good quality of the model and a reasonable time of computation (Gagliolo et al, 2018;.…”

Section: Figure 1 the Lavaiana Bridgementioning

confidence: 99%

Low-Cost Uas Photogrammetry for Road Infrastructures’ Inspection

Pinto

Bianchini

Nova

et al. 2020

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

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Abstract. All over the world, road infrastructures are getting closer to their life cycle and need to be constantly inspected: a consistent number of bridges are structurally deficient, and the risk of collapse can no longer be excluded. In contrast with the past, the interest in structure durability has recently grown rapidly. In order to make bridges durable, it is necessary to carry out ordinary maintenance, preceded by inspection activities, which can be traditionally divided in two categories: destructive and non-destructive (NDT). All the NDT inspections (visual, IR thermography, GPR) can be conducted by using UAS (Unmanned Aerial Systems), a technology that makes bridges inspections quicker, cheaper, objective and repeatable. This study presents the visual inspection and survey of two bridges by using a UAS DJI Mavic 2 Pro, equipped with a 20Mpixel Hasselblad camera that records 60fps 4K video and a 10bit radiometric resolution. Starting from the acquired data, a 3D model of each structure was built by using Structure from Motion (SfM) principles and software. To validate the two models, each of them characterized by a centimetric accuracy, the UAS camera generated cloud of points and was co-registered with the point cloud of a terrestrial laser-scanner using Ground Control Points (GCPs). To make this, CloudCompare comparison software was used; the plugin M3C2 automatically calculates the distance between the points of two compared clouds. Finally, some general rules concerning the UAS main characteristics for inspection of bridges and software for data processing are proposed.

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“…In this respect, the study of remote-sensing techniques, together with the development of new sensors and new measures for the 3D data validation, has proved to be of considerable importance in supporting emergency mapping and Building Damage Assessment (BDA) [Gagliolo et al, 2018;Zaragoza et al, 2017]. In cases where it is required to intervene in areas that present problems of security and access, the possibility to define a correct correspondence between rapidity of surveying, accuracy of acquired data and surveying and processing techniques available is a key task.…”

Section: Geomatics Applied To Disaster Managementmentioning

confidence: 99%

Assessment of Earthquake-Induced Damage Level on Buildings: Analysis of Two Different Survey Methods for a Case Study

Croce

Crepaldi

Piemonte

2019

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

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Commission II, WG II/8 ABSTRACT:Purpose of this paper is to compare different methods for the assessment of earthquake-induced damage on buildings based on survey data, referring to the case study of Castelluccio di Norcia. The seismic events that occurred in Central Italy in 2016 threatened the future of many villages located along the Apennine ridge straddling the Regions of Umbria, Marche, Abruzzo and Lazio: in Castelluccio di Norcia, a minor historical center in the Municipality of Norcia (Umbria), the earthquake occurred on August the 24 th caused some damage on localized buildings, but the strongest seismic event -the one occurred on October the 30 th and with magnitude Mw 6.5, provoked numerous collapses and widespread failure on several buildings of the village, razing to the ground almost the 60% of the built heritage. After the two earthquakes respectively, the Fire Brigade organized a reconnaissance campaign and flew over the village via UAVs (Unmanned Aerial Vehicles). By acquiring the videos recorded in this framework, that are currently available on the net and originally not recorded for specific survey purposes, the authors produced 3D models of the village allowing to compare the configuration of Castelluccio in the phases pre-and post-the destructive event of 30 th October: in fact, since the level of damage after the earthquake of August the 24 th was very low, the model resulting from the video recorded after this earthquake could be used as a model showing the layout of the village before the main struck of October. The result of this study is the Damage Degree Evaluation (DDE) and the following definition of a map showing for each building its class of damage, according to the distinction provided by European Macro-seismic Scale EMS98. On the other hand, another damage level map was studied: the Civil Protection requested, immediately after the earthquake and for the management of disaster response activities, the activation of the COPERNICUS project, providing for the detection of most damaged buildings of the village for an early census of the non-safe areas. The map of the damage level produced within this project is of course more accurate and precise, since it was collected through different acquisition systems: UAV, close-range photogrammetry, LiDAR (Light Detection And Ranging) and SLAM (Simultaneous Location and Mapping)-based mapping. This paper proposes a comparison between the two different DDEs, in order to define whether the first method, even if based on data downloaded via the web and therefore at lower resolution, and even if acquired with a more rapid evaluation procedure not providing for ground-based surveys, can lead to the construction of damage level maps that are plausible and realistic. The question is if the first method of DDE, even if less accurate, can allow to obtain results that are satisfactory and useful in the process of management and monitoring of natural hazards, providing support for the several implied institutions, in terms of information on catastrophe...

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Parameter optimization for creating reliable photogrammetric models in emergency scenarios

Cited by 20 publications

References 22 publications

Combining Interior Orientation Variables to Predict the Accuracy of Rpas–Sfm 3D Models

Combining Interior Orientation Variables to Predict the Accuracy of Rpas–Sfm 3D Models

Low-Cost Uas Photogrammetry for Road Infrastructures’ Inspection

Assessment of Earthquake-Induced Damage Level on Buildings: Analysis of Two Different Survey Methods for a Case Study

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