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
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
Remote Sensing
Matteo Cutugno, Umberto Robustelli, Giovanni Pugliano
Summary: With the performance improvement of free-and-open-source software (FOSS) for image processing and the advancement of unmanned aerial vehicle (UAV) technology, researchers and surveyors now have more possibilities. This study aims to assess the quality of sparse point clouds obtained using a consumer UAV and FOSS, and compares the results with those from commercial software. The findings indicate that the quality of sparse clouds obtained by both methods is comparable.
Article
Environmental Sciences
Daniele Ventura, Luca Grosso, Davide Pensa, Edoardo Casoli, Gianluca Mancini, Tommaso Valente, Michele Scardi, Arnold Rakaj
Summary: This study evaluated an integrated approach using low-cost unmanned aerial and surface vehicles to collect detailed remote sensing data and accurately map shallow benthic communities. Photogrammetric outputs from UAV and USV were classified using OBIA approach and achieved overall classification accuracies over 70%. The results demonstrated the practicality and feasibility of using aerial and underwater ultra-high spatial resolution imagery for detailed analysis.
FRONTIERS IN MARINE SCIENCE
(2023)
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
Chemistry, Multidisciplinary
Adel Khelifi, Gabriele Ciccone, Mark Altaweel, Tasnim Basmaji, Mohammed Ghazal
Summary: This paper proposes an end-to-end framework for archaeological sites detection and monitoring using autonomous service drones. By mounting multiple sensors on drones and utilizing advanced algorithms, the framework is able to accurately identify and monitor changes in archaeological sites. Experimental results show the framework's potential value in the field of archaeology.
APPLIED SCIENCES-BASEL
(2021)
Article
Remote Sensing
Alexandros Skondras, Eleni Karachaliou, Ioannis Tavantzis, Nikolaos Tokas, Elena Valari, Ifigeneia Skalidi, Giovanni Augusto Bouvet, Efstratios Stylianidis
Summary: This paper discusses the importance of using appropriate tools in urban space management and explores the impact of emerging technologies on urban development. The focus is on the role of UAVs in spatial mapping of urban areas and the goal of using collected information for 3D modeling. The research findings can be used for participatory decision-making and urban regeneration processes.
Article
Chemistry, Analytical
Nicolas Jacob-Loyola, Felipe Munoz-La Rivera, Rodrigo F. Herrera, Edison Atencio
Summary: This research proposes a method for recording the actual progress of a construction site through manual operation of UAVs and the use of point clouds obtained under photogrammetric techniques, which is then compared with actual progress in a 4D BIM environment. The results demonstrate the effectiveness of this method for UAV operation and monitoring actual progress.
Article
Automation & Control Systems
Danial Sufiyan, Luke Soe Thura Win, Shane Kyi Hla Win, Ying Hong Pheh, Gim Song Soh, Shaohui Foong
Summary: This study discusses the development of a multimodal, nature-inspired unmanned aerial vehicle (UAV) that can operate in three different flight modes. The UAV achieves efficient hover through a nature-inspired method and has the flexibility to enter more agile states using additional modes. The study documents the mechanical configuration and software/control architecture used to enable the three-mode capability. A sigmoid blending control is implemented for transition control, and an optimization routine is performed to improve the transition sequence based on performance goals. The optimized parameters are experimentally verified and shown to improve altitude variation and throttle usage compared to baseline.
ADVANCED INTELLIGENT SYSTEMS
(2023)
Article
Robotics
D. C. Schedl, I Kurmi, O. Bimber
Summary: Autonomous drones have shown great potential in finding hidden persons in densely occluded forests during search and rescue missions. Through field experiments, it has been proven that these drones can adaptively sample and improve classification confidence, leading to quicker and more reliable detection of individuals. This technology also enables SAR operations in remote areas with unstable network coverage, ensuring effective communication with rescue teams.
Article
Multidisciplinary Sciences
Aishwarya Raghunatha, Emma Lindkvist, Patrik Thollander, Erika Hansson, Greta Jonsson
Summary: In this paper, systems analyses are conducted to assess the impacts of large delivery drones on the environment, economy, and delivery time. The results show that large drones have lower emissions than diesel trucks in rural areas, and they do not compete with electric trucks due to the high energy demand for take-off and landing. Additionally, electric drones are found to be a more cost-effective option than road-bound transport modes and provide faster delivery times. However, to promote drones as an emission-friendly option, it is important to determine the optimal size, avoid low landings in urban areas, and implement home deliveries instead of pick-up points.
SCIENTIFIC REPORTS
(2023)
Review
Computer Science, Theory & Methods
Alessio Rugo, Claudio A. Ardagna, Nabil El Ioini
Summary: Unmanned Aerial Vehicles (UAVs) are being widely used in various commercial applications, but they have also become a target for criminals. This article presents a comprehensive literature review on UAV cybersecurity, examining threats, vulnerabilities, and countermeasures. It highlights the importance of communication, sensors, and system configuration, as well as the existence of unique attacks.
ACM COMPUTING SURVEYS
(2023)
Article
Computer Science, Information Systems
Ruba Alkadi, Noura Alnuaimi, Chan Yeob Yeun, Abdulhadi Shoufan
Summary: The paper discusses the utilization of blockchain technology in unmanned aerial vehicle (UAV) networks-based applications. It highlights the limitations of isolated blockchains for each application and proposes the need for a cross-blockchain platform. The paper surveys the existing cross-blockchain frameworks and reviews the latest advances in blockchain-based UAV networks applications. It introduces potential scenarios in UAV networks that can leverage the currently available cross-blockchain solutions. The paper also identifies open issues and potential challenges associated with implementing a cross-blockchain scheme for UAV networks to guide future research directions.
Article
Computer Science, Software Engineering
David Jurado-Rodriguez, Juan M. Jurado, Luis Pauda, Alexandre Neto, Rafael Munoz-Salinas, Joaquim J. Sousa
Summary: This paper proposes an automatic procedure for the generation and semantic segmentation of 3D cars obtained from UAV-based imagery, and demonstrates its capabilities for the semantic segmentation of car models.
COMPUTERS & GRAPHICS-UK
(2022)
Article
Remote Sensing
Nathalie Guimaraes, Luis Padua, Joaquim J. Sousa, Albino Bento, Pedro Couto
Summary: In Portugal, almonds are important due to their nutritional properties. This study explores the classification of almond cultivars using remote-sensing data and machine learning classifiers. The results demonstrate the importance of feature selection in optimizing classifier performance.
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2023)
Article
Environmental Sciences
Miguel Marchamalo-Sacristan, Antonio Miguel Ruiz-Armenteros, Francisco Lamas-Fernandez, Beatriz Gonzalez-Rodrigo, Ruben Martinez-Marin, Jose Manuel Delgado-Blasco, Matus Bakon, Milan Lazecky, Daniele Perissin, Juraj Papco, Joaquim J. Sousa
Summary: This study validates the monitoring of the Beninar Dam using Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) and dam modeling, opening the way to enhanced integrated monitoring systems. MT-InSAR proves to be a reliable and continuous monitoring system for dam deformation, surpassing previously installed systems in terms of precision. The study concludes that MT-InSAR and dam modeling are important elements for the integrated monitoring systems of embankment dams.
Review
Agronomy
Igor Teixeira, Raul Morais, Joaquim J. Sousa, Antonio Cunha
Summary: In recent years, the use of remote sensing data for crop classification tasks has increased, and artificial intelligence techniques, particularly deep learning, have been employed to analyze the data. This systematic review evaluates the effectiveness of deep learning techniques, including various architectures and data augmentation methods, for crop classification using remote sensing data. The review also examines the impact of factors such as resolution, annotation, and sample quality on classification accuracy. The study emphasizes the need for large amounts of training data and the integration of non-crop classes to improve accuracy in crop classification tasks.
Review
Agronomy
Ana Claudia Teixeira, Jose Ribeiro, Raul Morais, Joaquim J. Sousa, Antonio Cunha
Summary: Globally, insect pests pose a significant threat to crop yield and quality. The use of pesticides can have negative impacts on the environment and human health. Integrated pest management and artificial intelligence technologies offer alternative solutions for insect pest control, with automatic detection and monitoring systems showing promise. This article provides an overview of the leading techniques in automated insect detection and identifies challenges and recommendations for future research. Rating: 8/10.
Article
Environmental Sciences
Pedro Marques, Luis Padua, Joaquim J. Sousa, Anabela Fernandes-Silva
Summary: Global warming poses a significant threat to agricultural systems, requiring increased irrigation to mitigate the impact of prolonged dry seasons. This study investigates the potential of unmanned aerial vehicles (UAVs) and aerial imagery to predict water stress indicators and pigment content in olive orchards. The results show that thermal and spectral vegetation indices can accurately estimate these indicators, highlighting the importance of UAV-based imagery in precision agriculture.
Article
Environmental Sciences
Juan S. Tamayo Duque, Antonio Miguel Ruiz-Armenteros, Guillermo E. Avila Alvarez, Gustavo Matiz, Joaquim J. Sousa
Summary: This study investigates the subsidence phenomenon in Bogota, Colombia, including both urban and rural areas. The analysis results indicate that the outer regions of the city experience the most significant subsidence, with velocities reaching approximately 5-6 cm/year.
Article
Environmental Sciences
Diogo Rodrigues, Andre Fonseca, Oiliam Stolarski, Teresa R. Freitas, Nathalie Guimaraes, Joao A. Santos, Helder Fraga
Summary: The increasing gap between water demands and availability poses a significant challenge for sustainable water management. In the Coa region of Portugal, agriculture is vital for the local economy but is also threatened by climate change. This study evaluates the potential impact of climate change on streamflow in the Coa River.
Review
Chemistry, Multidisciplinary
Dibet Garcia, Joao Carias, Telmo Adao, Rui Jesus, Antonio Cunha, Luis G. Magalhaes
Summary: This article provides a comprehensive and systematic review of object detection (OD) and active learning (AL) techniques. It analyzes articles from reputable databases published between 2010 and December 2022, and also examines the geographical distribution of OD researchers worldwide. The study identifies promising research opportunities to enhance the AL process, including the development of novel sampling strategies and their integration with different learning techniques.
APPLIED SCIENCES-BASEL
(2023)
Article
Remote Sensing
Joaquim J. Sousa, Jiahui Lin, Qun Wang, Guang Liu, Jinghui Fan, Shibiao Bai, Hongli Zhao, Hongyu Pan, Wenjing Wei, Vanessa Rittlinger, Peter Mayrhofer, Ruth Sonnenschein, Stefan Steger, Luis Paulo Reis
Summary: Remote sensing, particularly satellite-based, is important for monitoring geohazards. This study presents techniques and methods for utilizing Earth observation data in detecting mining subsidence, monitoring water conservancy and hydropower engineering, evaluating the potential of InSAR results for heritage preservation, and detecting landslides in mountainous regions. The use of Artificial Intelligence techniques in combination with InSAR data improves the accuracy and efficiency of hazard analysis and identification.
GEO-SPATIAL INFORMATION SCIENCE
(2023)
Article
Imaging Science & Photographic Technology
Telmo Adao, Joao Oliveira, Somayeh Shahrabadi, Hugo Jesus, Marco Fernandes, Angelo Costa, Vania Ferreira, Martinho Fradeira Goncalves, Miguel A. Guevara Lopez, Emanuel Peres, Luis Gonzaga Magalhaes
Summary: This paper proposes a non-invasive Portuguese Sign Language (LGP) interpretation system using skeletal posture sequence inference and dataset augmentation. It achieves continuous conversations and coherent sentence construction. Users report high intuitiveness and real-time feedback. Promising semantic correlation is observed in the generated sentences.
JOURNAL OF IMAGING
(2023)
Article
Remote Sensing
Luis Padua, Ana M. Antao-Geraldes, Joaquim J. Sousa, Manuel angelo Rodrigues, Veronica Oliveira, Daniela Santos, Maria Filomena P. Miguens, Joao Paulo Castro
Summary: Efficient detection and monitoring of invasive plant species in aquatic ecosystems is crucial. This study used multispectral data with different spatial resolutions to detect water hyacinth. The results showed that the random forest classifier achieved the highest overall accuracy. The high spatial resolution of UAV data allowed for the detection of small amounts of water hyacinth, while satellite data analysis enabled the identification of water hyacinth coverage.
