Feasibility of UAV Photogrammetry for Coastal Monitoring: A Case Study in Imlang Beach, South Korea

Kim, Seongheon; Park, Soyoung; Han, Jae-Bok; Son, Sanghun; Lee, Seong-Hyeok; Han, Kyung-Soo; Kim, Jae‐Jin

doi:10.2112/si90-049.1

Cited by 8 publications

(8 citation statements)

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“…Furthermore, the use of UAVs are subject to a growing number of regulations and restrictions prohibiting flight. Multiple studies compared the two techniques concluding both should coexist, with their respective primary fields of application 16 – 18 .…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the Apple iPhone 12 Pro LiDAR for an Application in Geosciences

Luetzenburg

Kroon

Bjørk

2021

Sci Rep

130

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Traditionally, topographic surveying in earth sciences requires high financial investments, elaborate logistics, complicated training of staff and extensive data processing. Recently, off-the-shelf drones with optical sensors already reduced the costs for obtaining a high-resolution dataset of an Earth surface considerably. Nevertheless, costs and complexity associated with topographic surveying are still high. In 2020, Apple Inc. released the iPad Pro 2020 and the iPhone 12 Pro with novel build-in LiDAR sensors. Here we investigate the basic technical capabilities of the LiDAR sensors and we test the application at a coastal cliff in Denmark. The results are compared to state-of-the-art Structure from Motion Multi-View Stereo (SfM MVS) point clouds. The LiDAR sensors create accurate high-resolution models of small objects with a side length > 10 cm with an absolute accuracy of ± 1 cm. 3D models with the dimensions of up to 130 × 15 × 10 m of a coastal cliff with an absolute accuracy of ± 10 cm are compiled. Overall, the versatility in handling outweighs the range limitations, making the Apple LiDAR devices cost-effective alternatives to established techniques in remote sensing with possible fields of application for a wide range of geo-scientific areas and teaching.

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Section: Introductionmentioning

confidence: 99%

Evaluation of the Apple iPhone 12 Pro LiDAR for an Application in Geosciences

Luetzenburg

Kroon

Bjørk

2021

Sci Rep

130

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“…The UAV studies mainly consist of taking images using a red–green–blue (RGB) camera mounted onto a suitable UAV platform and processing those images using a SfM workflow within a suitable software to derive DSMs/DEMs/orthomosaics [ 67 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 ]. Although most authors used only a single type of UAV for conducting the studies [ 86 , 87 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 ], others used different types of UAVs [ 67 ] and different models of the same UAV [ 88 ] to discern any differences in the output induced due to different UAV types/models. While [ 67 ] found that the markedly lower cost quadcopter outperformed the more expensive fixed-wing UAV with DSM accuracy values comparable to a reference lidar DEM and the ground truth data, Ref.…”

Section: Categories Of Low-cost Sensors For Monitoring Climate Induce...mentioning

confidence: 99%

“…Additionally, even while flying at a constant height, the captured images may not have the same GSD due to terrain elevation differences and changes in camera angle while shooting, but since the DSMs and the orthomosaics are created using the 3D point cloud and camera positions, an average GSD is computed and used [ 97 ]. The UAVs were flown at different heights such as 50 m [ 93 ], 60 m [ 89 , 92 ], 65 and 85 m [ 88 ], 90 m [ 67 ], 100 m [ 90 , 94 , 95 ], 120 m [ 87 ], and 150 m [ 86 , 96 ], yielding different resolutions of the aerial images. The authors also used different ratios for the front/side overlap of the aerial images during flight planning such as 60%/40% [ 86 ], 85%/75% [ 87 , 95 ], 80%/50% and 75%/55% [ 88 ], 80%/70% [ 89 , 96 ], 70%/70% [ 67 , 90 ], 60%/60% [ 91 ], 70%/60% [ 92 ], 85%/70% [ 93 ], and 75%/75% [ 94 ].…”

Section: Categories Of Low-cost Sensors For Monitoring Climate Induce...mentioning

confidence: 99%

“…The UAVs were flown at different heights such as 50 m [ 93 ], 60 m [ 89 , 92 ], 65 and 85 m [ 88 ], 90 m [ 67 ], 100 m [ 90 , 94 , 95 ], 120 m [ 87 ], and 150 m [ 86 , 96 ], yielding different resolutions of the aerial images. The authors also used different ratios for the front/side overlap of the aerial images during flight planning such as 60%/40% [ 86 ], 85%/75% [ 87 , 95 ], 80%/50% and 75%/55% [ 88 ], 80%/70% [ 89 , 96 ], 70%/70% [ 67 , 90 ], 60%/60% [ 91 ], 70%/60% [ 92 ], 85%/70% [ 93 ], and 75%/75% [ 94 ]. Most authors except for [ 93 ] used different software such as ArduPilot [ 67 , 86 , 98 ], MikroKopter OSD Tool [ 87 , 99 ], Litchi application [ 88 , 100 ], Pix4DCapture [ 89 , 90 , 95 , 101 ], MapPilot app [ 91 , 94 , 102 ], and DroneDeploy web platform [ 93 , 103 ] for automating the UAV flights.…”

Section: Categories Of Low-cost Sensors For Monitoring Climate Induce...mentioning

confidence: 99%

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Low-Cost Sensors for Monitoring Coastal Climate Hazards: A Systematic Review and Meta-Analysis

Ahmed

Creedon²,

Gharbia

2023

Sensors

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Unequivocal change in the climate system has put coastal regions around the world at increasing risk from climate-related hazards. Monitoring the coast is often difficult and expensive, resulting in sparse monitoring equipment lacking in sufficient temporal and spatial coverage. Thus, low-cost methods to monitor the coast at finer temporal and spatial resolution are imperative for climate resilience along the world’s coasts. Exploiting such low-cost methods for the development of early warning support could be invaluable to coastal settlements. This paper aims to provide the most up-to-date low-cost techniques developed and used in the last decade for monitoring coastal hazards and their forcing agents via systematic review of the peer-reviewed literature in three scientific databases: Scopus, Web of Science and ScienceDirect. A total of 60 papers retrieved from these databases through the preferred reporting items for systematic reviews and meta-analyses (PRISMA) protocol were analysed in detail to yield different categories of low-cost sensors. These sensors span the entire domain for monitoring coastal hazards, as they focus on monitoring coastal zone characteristics (e.g., topography), forcing agents (e.g., water levels), and the hazards themselves (e.g., coastal flooding). It was found from the meta-analysis of the retrieved papers that terrestrial photogrammetry, followed by aerial photogrammetry, was the most widely used technique for monitoring different coastal hazards, mainly coastal erosion and shoreline change. Different monitoring techniques are available to monitor the same hazard/forcing agent, for instance, unmanned aerial vehicles (UAVs), time-lapse cameras, and wireless sensor networks (WSNs) for monitoring coastal morphological changes such as beach erosion, creating opportunities to not only select but also combine different techniques to meet specific monitoring objectives. The sensors considered in this paper are useful for monitoring the most pressing challenges in coastal zones due to the changing climate. Such a review could be extended to encompass more sensors and variables in the future due to the systematic approach of this review. This study is the first to systematically review a wide range of low-cost sensors available for the monitoring of coastal zones in the context of changing climate and is expected to benefit coastal researchers and managers to choose suitable low-cost sensors to meet their desired objectives for the regular monitoring of the coast to increase climate resilience.

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“…And the environmental monitoring studies were also conducted from the OISST, ARGO, MODIS, Landsat, and TerraSAR-X images (Baek and Moon, 2019;Chen et al, 2019a;Eom et al, 2019;Hong et al, 2019;Jeong et al, 2019;Jung et al, 2019;Lee et al, 2019a;Li et al, 2019;Ma et al, 2019;Mu et al, 2019;Sun et al, 2019;Tong et al, 2019;Qing, Hao, and Bao, 2019;Ren et al, 2019b;Xiao, Zhang, and Qin, 2019;Zhang et al, 2019aZhang et al, , 2019b The research topics of the oil spill, typhoon, flood, and nuclear radiation emergent have been carried out by using optical and SAR images (Bing et al, 2019;Jin et al, 2019;Kim and Moon, 2019;Park et al, 2019b;Syifa et al, 2019;Yang et al, 2019). Moreover, the specific topics related to marine spatial planning have been studied (Achmad et al, 2019;Bae et al, 2019;Chu et al, 2019;Chun and Lee, 2019;Jang et al, 2019;Kim et al, 2019b;Kim, Baek, and Hwang, 2019;Ko and Lee, 2019;Koo et al, 2019;Lee et al, 2019bLee et al, , 2019cLee et al, , 2019dOh et al, 2019aOh et al, , 2019bPark, 2019;Park et al 2019c;Ren et al, ...…”

Section: Previous Special Issue Related To Geospatial Research Of Coamentioning

confidence: 99%