Article
Environmental Sciences
Szymon Sledz, Marek W. Ewertowski
Summary: This study identifies three different processing workflows for efficiently processing image sets in the context of earth surface dynamics studies. The workflows were determined through testing 375 variations of setup parameters in the Agisoft Metashape software.
Article
Chemistry, Analytical
Ivan Jakopec, Ante Marendic, Igor Grgac
Summary: A new data processing method for calculating landslide displacements based on UAS photogrammetric survey data is presented in this paper, which does not require the production of dense point clouds, digital terrain models, and digital orthomosaic maps, enabling faster and simpler displacement determination. The proposed method matches features between images from two different UAS surveys and calculates displacements based only on the comparison of two reconstructed sparse point clouds. The method shows the ability to determine displacements with centimeter-level accuracy in ideal conditions, and sub-decimeter level accuracy in the Kostanjek landslide.
Article
Construction & Building Technology
Xiang Wang, Eric Lo, Luca De Vivo, Tara C. Hutchinson, Falko Kuester
Summary: The study proposes a vision-based analysis method to extract the dynamic response of structures using UAV aerial videos. By strategically placing geo-referenced targets on structures and background regions, the accuracy of image feature detection is enhanced. Image processing and photogrammetric techniques are used to recover camera motion and extract dynamic structural response.
STRUCTURAL CONTROL & HEALTH MONITORING
(2022)
Article
Environmental Sciences
Yajie Liu, Kevin Han, William Rasdorf
Summary: This paper evaluates the significance levels of five influence factors on UAS-based photogrammetry accuracy and investigates their interactions using multiple regression. It also develops prediction models for horizontal and vertical accuracies. The findings of this study can guide surveyors in designing flight configurations for high accuracies and provide reasonable predictions for different flight configurations.
Article
Geography, Physical
Yunus Kaya, Halil Ibrahim Senol, Abdurahman Yasin Yigit, Murat Yakar
Summary: Determining car density in parking lots is crucial for executing existing management systems and making precise plans for the future. In this study, high-resolution UAV images and deep learning methods were used to detect cars in parking lots. Two deep learning approaches, YOLOv3 and Mask R-CNN, were tested using the deep learning tool of Esri ArcGIS Pro. The performance of the algorithms was evaluated based on metrics such as recall, F1 score, precision ratio/uncertainty accuracy, and average producer accuracy.
PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING
(2023)
Article
Anthropology
Carolina Collaro, Carmen Enriquez-Munoz, Alfonso Lopez, Carlos Enriquez, Juan M. Jurado
Summary: This study explores the use of unmanned aerial systems (UAS) to reconstruct the Castle of Puerta Arenas fortress in 3D. By using RGB and thermographic images collected from a UAS, the researchers were able to detect unknown towers and anomalies through statistical analysis.
ARCHAEOLOGICAL AND ANTHROPOLOGICAL SCIENCES
(2023)
Article
Plant Sciences
Minghui Li, Enping Yan, Hui Zhou, Jiaxing Zhu, Jiawei Jiang, Dengkui Mo
Summary: The cliff ecosystem is one of the least disturbed ecosystems in nature. This study presents a method to evaluate vegetation cover of karst cliffs using high-resolution imagery captured by a smart unmanned aerial vehicle (UAV) and three-dimensional reconstruction. The results show a high-low-high distribution of vegetation cover from the bottom to the top of the cliffs.
FRONTIERS IN PLANT SCIENCE
(2022)
Article
Geochemistry & Geophysics
Guoqing Zhou, Xin Bao, Siqi Ye, Haoyu Wang, Hongbo Yan
Summary: This article presents an optimization method for selecting optimal building facade texture images from oblique images captured by multiple cameras onboard UAV. By using multiobjective functions and considering geometric correction, color equalization, and texture repair, the proposed method significantly reduces memory usage while maintaining high image quality.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2021)
Article
Green & Sustainable Science & Technology
Patricia Arranz, Fredrik Christiansen, Maria Glarou, Shane Gero, Fleur Visser, Machiel G. Oudejans, Natacha Aguilar de Soto, Kate Sprogis
Summary: This study examined the body shape, allometric relationships, and body condition of short-finned pilot whales in the North Atlantic. The researchers used unmanned aerial vehicles to measure the body length, width, and height of the whales. They found that there was no difference in body condition among reproductive classes or locations.
Article
Environmental Sciences
Benjamin T. Fraser, Russell G. Congalton
Summary: The research utilizes Unmanned Aerial Systems (UAS) and advanced image processing techniques to estimate tree diameters and various stand-level parameters in forests, with an average error reported. Stand-level parameters were either overestimated or underestimated, with a lesser overestimation for stands larger than 9 hectares. Random forest supervised classification achieved a promising overall accuracy of 85% in identifying large trees, offering local land managers opportunities for better understanding forested ecosystems. Future research on individual tree crown detection, especially for co-dominant or suppressed trees, will further enhance these efforts.
Article
Engineering, Multidisciplinary
Ismail Elkhrachy
Summary: This study aimed to produce accurate geospatial 3D data from UAV images. The solution generated met the 2015 ASPRS accuracy standards, with horizontal RMSE values of 4-6 cm and vertical accuracy of 5-6 cm, which were twice and three times the Ground Sample Distance (GSD), respectively.
ALEXANDRIA ENGINEERING JOURNAL
(2021)
Article
Computer Science, Interdisciplinary Applications
Carlos Alberto Villarreal, Carlos Guillermo Garzon, Jose Pedro Mora, Julian David Rojas, Carlos Alberto Rios
Summary: This paper presents a methodological approach for capturing difficult-to-access geological outcrops using unmanned aerial vehicle-based digital photogrammetric data. The obtained data can be used for geomodelling of mineral deposits and oil and gas geological structures.
JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION
(2022)
Article
Automation & Control Systems
Xinyu Cai, Shane Kyi Hla Win, Hitesh Bhardwaj, Shaohui Foong
Summary: In this study, a novel modular aerial robotic platform called ARROWs is introduced, which can be easily reconfigured with customized wing and control modules. Unlike conventional multirotor aerial vehicles, ARROWs generate more lift through revolving wings. However, the complex dynamics pose challenges in flight controller development. To address this, a cascaded flight controller is designed based on simplified flight dynamics and relaxed hovering conditions, while inertial measurement units are employed to estimate flight configuration. Experimental results validate the proposed platform and flight control strategy in 12 different configurations.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2023)
Article
Geochemistry & Geophysics
Yu-Hsuan Tu, Kasper Johansen, Bruno Aragon, Bonny M. Stutsel, Yoseline Angel, Omar A. Lopez Camargo, Samir K. M. Al-Mashharawi, Jiale Jiang, Matteo G. Ziliani, Matthew F. McCabe
Summary: This study evaluates the geometric accuracy of four UAV-based image acquisition and data processing scenarios in topographic surveying applications in complex terrain, finding that integrating oblique and facade imagery significantly improves the accuracy of point cloud data reconstruction. The improvements achieved have value for a range of applications, including geotechnical and geohazard investigations.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2021)
Article
Forestry
Facundo Pessacg, Francisco Gomez-Fernandez, Matias Nitsche, Nicolas Chamo, Sebastian Torrella, Ruben Ginzburg, Pablo De Cristoforis
Summary: Forestry aerial photogrammetry using Unmanned Aerial Systems (UAS) helps bridge the gap between detailed fieldwork and broad-range satellite imagery-based analysis. However, optical sensors face limitations in collecting and classifying ground points in woodlands. This study proposes a novel method to generate accurate Digital Terrain Models (DTMs) in forested environments and develops a realistic simulator for controlled experimentation.
Article
Geography, Physical
Sheng He, Shenhong Li, San Jiang, Wanshou Jiang
Summary: This paper proposes a hierarchical multi-scale matching network (HMSM-Net) for the disparity estimation of high-resolution satellite stereo images. The network leverages multi-scale features and a hierarchical coarse-to-fine matching strategy to handle challenging regions and achieves superior accuracy compared to state-of-the-art methods. The authors also create a dense stereo matching dataset and provide the source codes and evaluation dataset for further research.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2022)
Article
Geography, Physical
San Jiang, Wanshou Jiang, Bingxuan Guo
Summary: This paper presents an integrated workflow for match pair selection and guided feature matching for image orientation. The proposed algorithm explores the index structure of both inverted and direct indexes in the context of vocabulary tree-based image retrieval. The experimental results demonstrate that the proposed method achieves match pair selection with linear time complexity and provides refined matches for image orientation.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2022)
Article
Environmental Sciences
Chenni Zhang, Yunfan Cui, Zeyao Zhu, San Jiang, Wanshou Jiang
Summary: This paper proposes a solution for the estimation of building height from GF-7 satellite images, using a roof contour constrained stereo matching algorithm and DSM based bottom elevation estimation. The results demonstrate that the proposed method improves the accuracy of height estimation for high-rise buildings.
Article
Environmental Sciences
Haihan Luo, Kai Liu, San Jiang, Qingquan Li, Lizhe Wang, Wanshou Jiang
Summary: This study proposes a reliable outlier-removal algorithm by combining two affine-invariant geometric constraints to address the issue of high outlier ratios in initial matches. Through experiments and comparative analysis, the results demonstrate that the algorithm outperforms other methods in overall performance and is suitable for the workflow of SfM-based UAV image orientation.
Article
Environmental Sciences
Wanshou Jiang, San Jiang, Xiongwu Xiao
Article
Engineering, Electrical & Electronic
Qingquan Li, Hui Huang, Wenshuai Yu, San Jiang
Summary: Unmanned aerial vehicles have become widely used in remote sensing and are critical in the construction of smart cities. However, urban environments pose challenges for secure and accurate data acquisition for 3D modeling. This study presents optimized views photogrammetry as a solution and verifies its precision and potential in large-scale 3D modeling.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2023)
Article
Environmental Sciences
Juan Liu, Kun Sun, San Jiang, Kunqian Li, Wenbing Tao
Summary: In this paper, a novel robust feature called Mutual Structure Shift Feature (MSSF) is proposed to remove incorrect keypoint correspondences. The feature measures the bidirectional relative ranking difference for the neighbors of a reference correspondence, and combines spatially nearest neighbors with geometrically good neighbors to reduce the negative effect of incorrect correspondences. The proposed method is evaluated through extensive experiments on raw matching quality and downstream tasks.
Article
Environmental Sciences
San Jiang, Junhuan Liu, Yaxin Li, Duojie Weng, Wu Chen
Summary: This study proposes a reliable feature matching algorithm for spherical images using a combination of local geometric rectification and CNN learned descriptor. Experimental results demonstrate that the algorithm efficiently reduces geometric distortions and provides reliable feature matches for complete reconstruction.
Article
Geochemistry & Geophysics
Shenhong Li, Sheng He, San Jiang, Wanshou Jiang, Lin Zhang
Summary: The article introduces that stereo matching of high-resolution satellite images is still a fundamental but challenging task, and presents a large-scale dataset called WHU-Stereo for training and testing of deep learning networks. The dataset is created using airborne LiDAR point clouds and high-resolution stereo imageries from the Chinese GF-7 satellite, and includes ground-truth disparities considering occlusions. Experimental results demonstrate that the WHU-Stereo dataset can serve as a challenging benchmark for stereo matching and performance evaluation of DL models.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Engineering, Electrical & Electronic
San Jiang, Yichen Ma, Junhuan Liu, Qingquan Li, Wanshou Jiang, Bingxuan Guo, Lelin Li, Lizhe Wang
Summary: This article proposes an efficient method for UAV image orientation using structure from motion (SfM). By training an individual codebook and aggregating local features into global descriptors, the match pair retrieval is accelerated and the efficiency of SfM reconstruction is improved.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2023)
Article
Geochemistry & Geophysics
San Jiang, Qingquan Li, Wanshou Jiang, Wu Chen
Summary: This article proposes an algorithm for extracting the global model for cluster merging in unmanned aerial vehicle (UAV) image orientation. It also presents a parallel ISfM solution to achieve efficient and accurate image orientation. The experimental results demonstrate significant improvements in efficiency and orientation accuracy.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Geochemistry & Geophysics
San Jiang, Wanshou Jiang, Lizhe Wang
IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE
(2022)
