Image-Based 3D Reconstruction for Posthurricane Residential Building Damage Assessment

Zhou, Zixiang; Gong, Jie; Guo, Mengyang

doi:10.1061/(asce)cp.1943-5487.0000480

Cited by 60 publications

(29 citation statements)

References 48 publications

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“…Modern photogrammetry techniques offer the ability to produce point clouds from handheld digital cameras and UAS platforms with onboard cameras, with a distinct advantage being the much faster possibility for data acquisition as compared to GBL systems (minutes as opposed to hours). Zhou et al (2016) examined mobile-platform digital photogrammetric (DPG) techniques and mobile lidar platforms and found that these mobile platforms facilitated damage assessments consistent with >1 cm pixel size (Tier 3). Lidar scanning equipment is relatively costly and requires more time for data acquisition; however, later processing of acquired lidar data into a 3D point cloud is relatively fast and straightforward.…”

Section: Complementary Uses Of Photogrammetry and Lidar For Point Clomentioning

confidence: 99%

Multi-Scale Remote Sensing of Tornado Effects

Womble

Wood

Mohammadi

2018

Front. Built Environ.

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To achieve risk-based engineered structural designs that provide safety for life and property from tornadoes, sufficient knowledge of tornado wind speeds and wind flow characteristics is needed. Currently, sufficient understanding of the magnitude, frequency, and velocity structure of tornado winds remain elusive. Direct measurements of tornado winds are rare and nearly impossible to acquire, and the pursuit of in situ wind measurements can be precarious, dangerous, and even necessitating the development of safer and more reliable means to understand tornado actions. Remote-sensing technologies including satellite, aerial, lidar, and photogrammetric platforms, have demonstrated an ever-increasing efficiency for collecting, storing, organizing, and communicating tornado hazards information at a multitude of geospatial scales. Current remote-sensing technologies enable wind-engineering researchers to examine tornado effects on the built environment at various spatial scales ranging from the overall path to the neighborhood, building, and ultimately member and/or connection level. Each spatial resolution contains a unique set of challenges for efficiency, ease, and cost of data acquisition and dissemination, as well as contributions to the body of knowledge that help engineers and atmospheric scientists better understand tornado wind speeds. This paper examines the use of remote sensing technologies at four scales in recent tornado investigations, demonstrating the challenges of data collection and processing at each level as well as the utility of the information gleaned from each level in advancing the understanding of tornado effects.

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Section: Complementary Uses Of Photogrammetry and Lidar For Point Clomentioning

confidence: 99%

Multi-Scale Remote Sensing of Tornado Effects

Womble

Wood

Mohammadi

2018

Front. Built Environ.

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“…Furthermore, photogrammetry enables both a qualitative and a quantitative evaluation approach for monitoring changes or performances, and would be advantageous for an asset management system, easily data-logging its condition over time [9]. With researchers becoming more interested in using photogrammetry, comparative experimental studies between photogrammetry and Terrestrial Laser Scanning (TLS), for 3D reconstruction of civil and geotechnical infrastructure systems, have been documented [4][5][6][14][15][16][17][18][19][20][21][22][23]. While TLS has been implemented in areas of geotechnical engineering, because of improvements in scanning speed and mobility as well as capabilities for building management [24][25][26][27], few efforts emphasize photogrammetric techniques [9].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Photogrammetry and Inclusion of Control Points: Significance for Infrastructure Monitoring

Oats

Escobar-Wolf

Oommen

2019

Data

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Structure from Motion (SfM)/Photogrammetry is a powerful mapping tool in extracting three-dimensional (3D) models from photographs. This method has been applied to a range of applications, including monitoring of infrastructure systems. This technique could potentially become a substitute, or at least a complement, for costlier approaches such as laser scanning for infrastructure monitoring. This study expands on previous investigations, which utilize photogrammetry point cloud data to measure failure mode behavior of a retaining wall model, emphasizing further robust spatial testing. In this study, a comparison of two commonly used photogrammetry software packages was implemented to assess the computing performance of the method and the significance of control points in this approach. The impact of control point selection, as part of the photogrammetric modeling processes, was also evaluated. Comparisons between the two software tools reveal similar performances in capturing quantitative changes of a retaining wall structure. Results also demonstrate that increasing the number of control points above a certain number does not, necessarily, increase 3D modeling accuracies, but, in some cases, their spatial distribution can be more critical. Furthermore, errors in model reproducibility, when compared with total station measurements, were found to be spatially correlated with the arrangement of control points.The software uses the control points to best align all images in the dataset. The photogrammetry 105 point cloud models consist of numerous sets of points in 3D, on the order of several million. This 106 magnitude of points results in point densities of tens-to hundreds-of-thousands of points per m2 107 [9]. Figure 2b provides an illustration of the point cloud model, including the flagged referenced 108 control points within the testing environment. Control points on the moving wall panels were 109 compared between scenarios, but also with total station measurements of those same points. The 110 displacements were calculated by comparing the positions of the control points along the surfaces, 111 for different scenarios. The relative space coordinate locations of the control points were determined 112 in each of these scenarios, which were compared to the ground truth total station measurements. 113A focused evaluation, considering different amounts of control points, was also performed for 114 each of the five failure mode scenarios, specifically using the Photoscan software's 3D model. Three 115 sets of data, i.e., point cloud models, were created by aligning the collected images: (1) without any 116 of the reference control points, (2) with two of the stationary control points and (3) with all four 117 stationary control points. This strategy was implemented to consider the impact of control points for 118 the model creation, varying from zero to four control points. For all three datasets, the locations of 119 the wall panel control points, and two stationary points, were captured in the point cloud model...

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“…Nölke et al (2015) applied TLS and successfully estimated stem volume of 12 tropical tree species that have irregular stems. However, a TLS sensor is quite expensive and data processing is labour intensive, often requiring advanced technical skills, which have been a major obstacle for the wide use of this nondestructive approach (Heritage and Large 2009;Zhou et al 2015).…”

Section: Introductionmentioning

confidence: 99%

Application of Terrestrial Close-Range Photogrammetry for Estimating Stem Volume of Tree Species in Subtropical Forest in Okinawa, Japan

Tamaki

Konoshima

2019

FORMATH

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A nondestructive, practical and efficient in-situ tree measurement approach is desperately needed to address the problem of large data volume, enhancing data quality and improving our understanding of stem volume estimation in Okinawa. This issue has become important because of two forestry related policy issues that have received lots of attention in Okinawa. The two issues are the introduction of carbon certification program and the nomination of northern Okinawa Island as a World Natural Heritage site. In this study, our attention was turned to a more recent emerging low cost approach for estimating stem volume with minimum environmental impact on the site, that is, the terrestrial closerange photogrammetry. We explored the usefulness and evaluated the limitations of the approach. For examination of the accuracy of terrestrial photogrammetry, we compared the stem volume estimated from photogrammetry with the stem volume computed based on direct measurement using 3D magnetic motion tracker. The error of the estimated volume was 0.0053 m 3 root mean square error (RMSE) and the estimated surface was 0.0714 m 2. In order to explore the efficiency of the photogrammetry, we extended our approach to include the simultaneous reconstruction of 3D images of multiple tree stems within a plot. Using one of the latest image-processing software, we successfully reconstructed 3D models of 11 stems within a plot and computed stem volume for each. The error of the estimated volume and surface were 0.0128 m 3 and 0.1940 m 2 , respectively.

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Image-Based 3D Reconstruction for Posthurricane Residential Building Damage Assessment

Cited by 60 publications

References 48 publications

Multi-Scale Remote Sensing of Tornado Effects

Multi-Scale Remote Sensing of Tornado Effects

Evaluation of Photogrammetry and Inclusion of Control Points: Significance for Infrastructure Monitoring

Application of Terrestrial Close-Range Photogrammetry for Estimating Stem Volume of Tree Species in Subtropical Forest in Okinawa, Japan

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