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Application of Photogrammetry into Engineering Practice: Advances and Experience

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Engineering Remote Sensing".

Deadline for manuscript submissions: closed (1 July 2022) | Viewed by 13472

Special Issue Editors


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Guest Editor
School of Engineering and Built Environment, Griffith University, Parklands Drive, Southport, QLD 4222, Australia
Interests: rock slope stability; remote sensing; rock mechanics; landslides
Special Issues, Collections and Topics in MDPI journals
Department of Earth Sciences, Simon Fraser University, 8888 University Drive, Burnaby, BC V5A 1S6, Canada
Interests: rock slope stability; landslides; remote sensing; MR/VR; numerical modelling

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Guest Editor
CEO of Aiclops Inc., 283, Goyangdae-Ro, Ilsanseo-Gu, Goyang-Si 10223, Gyeonggi-Do, Republic of Korea
Interests: image analysis; photogrammetry; IoT; safety monitoring; geotechnical engineering
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

As you know, photogrammetry is a powerful tool that has been used in the past decade for a number of engineering projects including a range of tasks such as the interpretation of aerial photos, topographic maps, rock mass stability and infrastructure monitoring. With the continuous improvement in the technology, photogrammetry finds more new areas and applications where it can provide reliable data for cutting-edge engineering solutions. Recent advances in photogrammetry and its successful practical application has highlighted the importance of this remote sensing method in our practice and emphasized the need for the development of more systematic methods that will benefit engineers and practitioners.

This special issue aims at providing a platform for all interested parties to share their experience and innovative approaches for the use of photogrammetry in engineering practice. This issue welcomes all publications related to the latest advances in the photogrammetric technology which cover a wide range of subjects related to application of photogrammetry in practice including structural, geotechnical, geological, costal, water and management engineering.

Dr. Ivan Gratchev
Dr. Doug Stead
Dr. Dong-Hyun Kim
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Photogrammetry
  • Engineering practice
  • advances
  • practical solutions
  • innovative applications

Published Papers (5 papers)

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Research

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15 pages, 6495 KiB  
Article
Comparative Evaluation for Tracking the Capability of Solar Cell Malfunction Caused by Soil Debris between UAV Video versus Photo-Mosaic
by Young-Seok Hwang, Stephan Schlüter, Seong-Il Park and Jung-Sup Um
Remote Sens. 2022, 14(5), 1220; https://doi.org/10.3390/rs14051220 - 2 Mar 2022
Cited by 2 | Viewed by 1999
Abstract
Monitoring the malfunction of the solar cells (for instance, 156 mm by 156 mm) caused by the soil debris requires a very low flight altitude when taking aerial photos, utilizing the autopilot function of unmanned aerial vehicle (UAV). The autopilot flight can only [...] Read more.
Monitoring the malfunction of the solar cells (for instance, 156 mm by 156 mm) caused by the soil debris requires a very low flight altitude when taking aerial photos, utilizing the autopilot function of unmanned aerial vehicle (UAV). The autopilot flight can only operate at a certain level of altitude that can guarantee collision avoidance for flight obstacles (for instance, power lines, trees, buildings) adjacent to the place where the solar panel is installed. For this reason, aerial photos taken by autopilot flight capture unnecessary objects (surrounding buildings and roads) around the solar panel at a tremendous level. Therefore, the autopilot-based thermal imaging causes severe data redundancy with very few matched key-points around the malfunctioned solar cells. This study aims to explore the tracking capability on soil debris defects in solar cell scale between UAV video versus photo-mosaic. This study experimentally validated that the video-based thermal imaging can track the thermal deficiency caused by the malfunction of the solar cell at the level of the photo-mosaic in terms of correlation of thermal signatures (0.98–0.99), detection on spatial patterns (81–100%), and distributional property (90–95%) with 2.5–3.4 times more matched key-points on solar cells. The results of this study could serve as a valuable reference for employing video stream in the process of investigating soil debris defects in solar cell scale. Full article
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20 pages, 8620 KiB  
Article
Study on High-Resolution Suspended Sediment Distribution under the Influence of Coastal Zone Engineering in the Yangtze River Mouth, China
by Lina Cai, Songyu Chen, Xiaojun Yan, Yan Bai and Juan Bu
Remote Sens. 2022, 14(3), 486; https://doi.org/10.3390/rs14030486 - 20 Jan 2022
Cited by 5 | Viewed by 2421
Abstract
In this study, we analyzed the influence of coastal zone engineering on suspended sediment concentration (SSC) in the Yangtze River mouth based on HY-1C and Chinese GaoFen (GF) satellite data. The results show that: (1) SSC in the Yangtze River mouth is mainly [...] Read more.
In this study, we analyzed the influence of coastal zone engineering on suspended sediment concentration (SSC) in the Yangtze River mouth based on HY-1C and Chinese GaoFen (GF) satellite data. The results show that: (1) SSC in the Yangtze River mouth is mainly in the range of 200–1300 mg/L, which changes due to natural factors as well as coastal zone engineering; (2) The sand blocking engineering effectively protects the channel from siltation, and SSC in the central line of the channel is 100–300 mg/L lower than that near the dikes in the north and south; (3) Qingcaosha Reservoir plays a stabilizing role in the hydrodynamic force, promoting the deposition of suspended matter, so that the water in the reservoir is clear. SSC inside the Qingcaosha Reservoir, located in the center of the estuary, is 100–500 mg/L lower than the high SSC water outside the reservoir; (4) The bridges interact with the current, facilitating the transport of local sediment, resulting in the increase in SSC downstream of these bridges, and obvious vortexes appear with the length up to nearly 2400 m; and (5) Corresponding protection and development suggestions were put forward as follows. A linear array of wind power plants can be built near and parallel to dikes and leading jetties; to increase the depth of the southeast end of the reservoir; and the location of the bridge should be selected in the place of river where siltation is easy. This study aimed to study the SSC distribution under the complex impact of coastal zone engineering with satellite and to provide possible improvement suggestions. Full article
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16 pages, 16210 KiB  
Article
From Point to Region: Accurate and Efficient Hierarchical Small Object Detection in Low-Resolution Remote Sensing Images
by Jingqian Wu and Shibiao Xu
Remote Sens. 2021, 13(13), 2620; https://doi.org/10.3390/rs13132620 - 3 Jul 2021
Cited by 10 | Viewed by 3476
Abstract
Accurate object detection is important in computer vision. However, detecting small objects in low-resolution images remains a challenging and elusive problem, primarily because these objects are constructed of less visual information and cannot be easily distinguished from similar background regions. To resolve this [...] Read more.
Accurate object detection is important in computer vision. However, detecting small objects in low-resolution images remains a challenging and elusive problem, primarily because these objects are constructed of less visual information and cannot be easily distinguished from similar background regions. To resolve this problem, we propose a Hierarchical Small Object Detection Network in low-resolution remote sensing images, named HSOD-Net. We develop a point-to-region detection paradigm by first performing a key-point prediction to obtain position hypotheses, then only later super-resolving the image and detecting the objects around those candidate positions. By postponing the object prediction to after increasing its resolution, the obtained key-points are more stable than their traditional counterparts based on early object detection with less visual information. This hierarchical approach, HSOD-Net, saves significant run-time, which makes it more suitable for practical applications such as search and rescue, and drone navigation. In comparison with the state-of-art models, HSOD-Net achieves remarkable precision in detecting small objects in low-resolution remote sensing images. Full article
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15 pages, 7009 KiB  
Technical Note
Evaluation of Field Applicability of High-Speed 3D Digital Image Correlation for Shock Vibration Measurement in Underground Mining
by Seunghwan Seo, Younghun Ko and Moonkyung Chung
Remote Sens. 2022, 14(13), 3133; https://doi.org/10.3390/rs14133133 - 29 Jun 2022
Cited by 7 | Viewed by 1475
Abstract
When combined with high-speed photography technology, the digital image correlation (DIC) method provides an excellent photographic image processing capability that can be used to convert the evolving full-field surface properties of structures to sets of two-dimensional (2D) or three-dimensional (3D) coordinate values. In [...] Read more.
When combined with high-speed photography technology, the digital image correlation (DIC) method provides an excellent photographic image processing capability that can be used to convert the evolving full-field surface properties of structures to sets of two-dimensional (2D) or three-dimensional (3D) coordinate values. In this study, the applicability of the DIC method and high-speed cameras in underground mining was investigated by measuring the displacement and vibration of rock pillars caused by blasting. This technique is used extensively in engineering and is increasingly being applied to new fields. As a result of comparing the DIC results for blast vibration with the measured values of the contact sensor through field tests, the maximum displacement and vibration speed were found to be 86% and 93% accurate, respectively. In addition, the obtained values appeared similar to those predicted through numerical analysis. Field test results indicate that both methods yielded similar results. Therefore, it is concluded that it is feasible to use the DIC and high-speed camera to measure ground displacements and vibrations from blasting in underground mining. In addition, the system conditions required for blast vibration measurement were considered by comparing the accuracy with the existing measurement methods. Full article
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17 pages, 8629 KiB  
Technical Note
Application of Optical Flow Technique and Photogrammetry for Rockfall Dynamics: A Case Study on a Field Test
by Dong-Hyun Kim and Ivan Gratchev
Remote Sens. 2021, 13(20), 4124; https://doi.org/10.3390/rs13204124 - 14 Oct 2021
Cited by 5 | Viewed by 2513
Abstract
Optical flow is a vision-based approach that is used for tracking the movement of objects. This robust technique can be an effective tool for determining the source of failures on slope surfaces, including the dynamic behavior of rockfall. However, optical flow-based measurement still [...] Read more.
Optical flow is a vision-based approach that is used for tracking the movement of objects. This robust technique can be an effective tool for determining the source of failures on slope surfaces, including the dynamic behavior of rockfall. However, optical flow-based measurement still remains an issue as the data from optical flow algorithms can be affected by the varied photographing environment, such as weather and illuminations. To address such problems, this paper presents an optical flow-based tracking algorithm that can be employed to extract motion data from video records for slope monitoring. Additionally, a workflow combined with photogrammetry and the optical flow technique has been proposed for producing highly accurate estimations of rockfall motion. The effectiveness of the proposed approach has been evaluated with the dataset obtained from a photogrammetry survey of field rockfall tests performed by the authors in 2015. The results show that the workflow adopted in this study can be suitable to identify rockfall events overtime in a slope monitoring system. The limitations of the current approach are also discussed. Full article
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