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Jiann-Yeou Rau
Department of Geomatics, National Cheng Kung University, 34912 Tainan, Taiwan

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Journal article
Published: 12 May 2021 in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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The original multispectral (MS) images obtained from multi-lens multispectral cameras (MSCs) have significant misregistration errors, which require image registration for precise spectral measurement. However, due to the non-linearity intensity differences among MS images, performing image matching is difficult to find sufficient correct matches (CMs) for image registration, and results in a complex coarse-to-fine solution. Based on the modification of Speed-up Robust Feature (SURF), we proposed a normalized SURF (N-SURF) that can significantly increase the amount of CMs among different pairs of MS images and make one-step image registration possible. In this study, we first introduce N-SURF and adopt different MS datasets acquired from three representative MSCs (MCA-12, Altum, and Sequoia) to evaluate its matching ability. Meanwhile, we utilized three image transformation modelsAffine Transform (AT), Projective Transform (PT), and an Extended Projective Transform (EPT) to correct the misregistration errors of MSCs and evaluate their co-registration correctness. The results show that N-SURF can obtain 620 times more CMs than SURF and can successfully match all pairs of MS images, while SURF failed in the cases of significant spectral differences. Moreover, visual comparison, accuracy assessment, and residual analysis show that EPT can more accurately correct the viewpoint and lens distortion differences of MSCs than AT and PT, and it can obtain co-registration accuracy of 0.20.4 pixels. Subsequently, using the successful N-SURF matching and EPT model, we developed an automatic MS image registration tool that is suitable for various multi-lens MSCs.

ACS Style

Jyun-Ping Jhan; Jiann-Yeou Rau. A Generalized Tool for Accurate and Efficient Image Registration of UAV Multi-lens Multispectral Cameras by N-SURF Matching. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2021, PP, 1 -1.

AMA Style

Jyun-Ping Jhan, Jiann-Yeou Rau. A Generalized Tool for Accurate and Efficient Image Registration of UAV Multi-lens Multispectral Cameras by N-SURF Matching. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2021; PP (99):1-1.

Chicago/Turabian Style

Jyun-Ping Jhan; Jiann-Yeou Rau. 2021. "A Generalized Tool for Accurate and Efficient Image Registration of UAV Multi-lens Multispectral Cameras by N-SURF Matching." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing PP, no. 99: 1-1.

Journal article
Published: 21 April 2021 in Journal of Volcanology and Geothermal Research
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Mount Agung (the highest volcano in Bali, Indonesia) began to erupt on November 21, 2017, after having been dormant for 53 years. More than 100,000 people were evacuated within the hazard zone between September 2017 (when the highest volcanic alert was issued) and early 2018. The eruptions continued until June 2019, accompanied by at least 110 explosions. During the eruptive crisis, the observation of the lava dome's emplacement was essential for mitigating the potential hazard. Details of the lava dome growth, including the volumetric changes and effusion rates, provide valuable information about potential eruption scenarios and lahar depositions. In this paper, the essential role of multi-temporal unmanned aerial vehicle (UAV) images in the monitoring of Mt. Agung's lava dome, and in determining the areas of potential lahar hazards during the crisis between 2017 and 2019 is described. A fixed-wing UAV was launched outside the hazard zone to photograph the lava dome on five occasions. Image enhancement, machine learning, and photogrammetry were combined to improve image quality, remove point clouds outliers, and generate digital terrain models (DTMs) and orthoimages. The analysis of the obtained DTMs and orthoimages resulted in qualitative and quantitative data highlighting the changes inside the crater and on the surrounding slopes. These results reveal that, from November 25 to December 16, 2017, the lava dome grew vertically by 126 m and reached a volume of 26.86 ± 0.64 × 106 m3. In addition, its surface experienced a maximal uplift of approximately 52 m until July 2019 with the emergence of a new dome with a volume estimated at 9.52 ± 0.086 × 106 m3. The difference between the DTMs of 2017 and 2019 reveals the total volume of erupted material (886,100 ± 8000 m3) that was deposited on the surrounding slopes. According to the lahar inundation simulation, the deposited material may cause dangerous lahars in 21 drainages, which extend in the north (N), north-east (N-E), south (S), south-east (S-E), and south-west (S-W) sectors of the volcano. This paper presents the use of UAV remote sensing for the production of high-spatial resolution DTMs, which can be used to both observe the emplacement of a lava dome, and to identify areas with potential lahar risk during a volcano crisis.

ACS Style

Ruli Andaru; Jiann-Yeou Rau; Devy Kamil Syahbana; Ardy Setya Prayoga; Heruningtyas Desi Purnamasari. The use of UAV remote sensing for observing lava dome emplacement and areas of potential lahar hazards: An example from the 2017–2019 eruption crisis at Mount Agung in Bali. Journal of Volcanology and Geothermal Research 2021, 415, 107255 .

AMA Style

Ruli Andaru, Jiann-Yeou Rau, Devy Kamil Syahbana, Ardy Setya Prayoga, Heruningtyas Desi Purnamasari. The use of UAV remote sensing for observing lava dome emplacement and areas of potential lahar hazards: An example from the 2017–2019 eruption crisis at Mount Agung in Bali. Journal of Volcanology and Geothermal Research. 2021; 415 ():107255.

Chicago/Turabian Style

Ruli Andaru; Jiann-Yeou Rau; Devy Kamil Syahbana; Ardy Setya Prayoga; Heruningtyas Desi Purnamasari. 2021. "The use of UAV remote sensing for observing lava dome emplacement and areas of potential lahar hazards: An example from the 2017–2019 eruption crisis at Mount Agung in Bali." Journal of Volcanology and Geothermal Research 415, no. : 107255.

Journal article
Published: 12 August 2020 in Remote Sensing
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The Zengwen desilting tunnel project installed an Elephant Trunk Steel Pipe (ETSP) at the bottom of the reservoir that is designed to connect the new bypass tunnel and reach downward to the sediment surface. Since ETSP is huge and its underwater installation is an unprecedented construction method, there are several uncertainties in its dynamic motion changes during installation. To assure construction safety, a 1:20 ETSP scale model was built to simulate the underwater installation procedure, and its six-degrees-of-freedom (6-DOF) motion parameters were monitored by offline underwater 3D rigid object tracking and photogrammetry. Three cameras were used to form a multicamera system, and several auxiliary devices—such as waterproof housing, tripods, and a waterproof LED—were adopted to protect the cameras and to obtain clear images in the underwater environment. However, since it is difficult for the divers to position the camera and ensure the camera field of view overlap, each camera can only observe the head, middle, and tail parts of ETSP, respectively, leading to a small overlap area among all images. Therefore, it is not possible to perform a traditional method via multiple images forward intersection, where the camera’s positions and orientations have to be calibrated and fixed in advance. Instead, by tracking the 3D coordinates of ETSP and obtaining the camera orientation information via space resection, we propose a multicamera coordinate transformation and adopted a single-camera relative orientation transformation to calculate the 6-DOF motion parameters. The offline procedure is to first acquire the 3D coordinates of ETSP by taking multiposition images with a precalibrated camera in the air and then use the 3D coordinates as control points to perform the space resection of the calibrated underwater cameras. Finally, we calculated the 6-DOF of ETSP by using the camera orientation information through both multi- and single-camera approaches. In this study, we show the results of camera calibration in the air and underwater environment, present the 6-DOF motion parameters of ETSP underwater installation and the reconstructed 4D animation, and compare the differences between the multi- and single-camera approaches.

ACS Style

Jyun-Ping Jhan; Jiann-Yeou Rau; Chih-Ming Chou. Underwater 3D Rigid Object Tracking and 6-DOF Estimation: A Case Study of Giant Steel Pipe Scale Model Underwater Installation. Remote Sensing 2020, 12, 2600 .

AMA Style

Jyun-Ping Jhan, Jiann-Yeou Rau, Chih-Ming Chou. Underwater 3D Rigid Object Tracking and 6-DOF Estimation: A Case Study of Giant Steel Pipe Scale Model Underwater Installation. Remote Sensing. 2020; 12 (16):2600.

Chicago/Turabian Style

Jyun-Ping Jhan; Jiann-Yeou Rau; Chih-Ming Chou. 2020. "Underwater 3D Rigid Object Tracking and 6-DOF Estimation: A Case Study of Giant Steel Pipe Scale Model Underwater Installation." Remote Sensing 12, no. 16: 2600.