UAV or drones for remote sensing applications . Volume 2 / / edited by Felipe Gonzalez Toro, Antonios Tsourdos

• Pubblicazione: Basel, Switzerland : , : MDPI - Multidisciplinary Digital Publishing Institute, , [2018]; ©2018
• Descrizione fisica: 1 online resource (x, 332 pages) : illustrations
• Disciplina: 621.3678
• Soggetto topico: Remote sensing - Equipment and supplies
• Persona (resp. second.): ToroFelipe Gonzalez; TsourdosAntonios
• Nota di contenuto: About the Special Issue Editors -- Preface to "UAV or Drones for Remote Sensing Applications" -- Tomas Poblete, Samuel Ortega-Farías and Dongryeol Ryu / Automatic Coregistration Algorithm to Remove Canopy Shaded Pixels in UAV-Borne Thermal Images to Improve the Estimation of Crop Water Stress Index of a Drip-Irrigated Cabernet Sauvignon Vineyard, Reprinted from: Sensors 2018, 18, 397, doi: 10.3390/s18020397 -- Yufu Qu, Jianyu Huang and Xuan Zhang / Rapid 3D Reconstruction for Image Sequence Acquired from UAV Camera, Reprinted from: Sensors 2018, 18, 225, doi: 10.3390/s18010225 -- Krishna Ribeiro-Gomes, David Hernández-López, Jos é F. Ortega, Rocío Ballesteros, Tomás Poblete and Miguel A. Moreno / Uncooled Thermal Camera Calibration and Optimization of the Photogrammetry Process for UAV Applications in Agriculture, Reprinted from: Sensors 2017, 17, 2173, doi: 10.3390/s17102173 -- Elena Ridolfi, Giulia Buffi, Sara Venturi and Piergiorgio Manciola / Accuracy Analysis of a Dam Model from Drone Surveys, Reprinted from: Sensors 2017, 17, 1777, doi: 10.3390/s17081777 -- Monica Rivas Casado, Rocío Ballesteros González, José Fernando Ortega, Paul Leinster and Ros Wright / Towards a Transferable UAV-Based Framework for River Hydromorphological Characterization, Reprinted from: Sensors 2017, 17, 2210, doi: 10.3390/s17102210 -- Juan Sandino, Adam Wooler and Felipe Gonzalez / Towards the Automatic Detection of Pre-Existing Termite Mounds through UAS and Hyperspectral Imagery, Reprinted from: Sensors 2017, 17, 2196, doi: 10.3390/s17102196 -- Juan Sandino, Felipe Gonzalez, Kerrie Mengersen and Kevin J. Gaston / UAVs and Machine Learning Revolutionising Invasive Grass and Vegetation Surveys in Remote Arid Lands, Reprinted from: Sensors 2018, 18, 605, doi: 10.3390/s18020605 -- Juan Sandino, Geoff Pegg, Felipe Gonzalez and Grant Smith / Aerial Mapping of Forests Affected by Pathogens Using UAVs, Hyperspectral Sensors, and Artificial Intelligence, Reprinted from: Sensors 2018, 18, 944, doi: 10.3390/s18040944 -- Seung-Hyun Seo, Jung-In Choi and Jinseok Song / Secure Utilization of Beacons and UAVs in Emergency Response Systems for Building Fire Hazard, Reprinted from: Sensors 2017, 17, 2200, doi: 10.3390/s17102200 -- Jieliang Shen, Yan Su, Qing Liang and Xinhua Zhu / Calculation and Identification of the Aerodynamic Parameters for Small-Scaled Fixed-Wing UAVs, Reprinted from: Sensors 2018, 18, 206, doi: 10.3390/s18010206 -- Rafael R. Sola-Guirado, Francisco J. Castillo-Ruiz, Francisco Jiménez-Jim énez, Gregorio L. Blanco-Roldan, Sergio Castro-Garcia and Jesus A. Gil-Ribes / Olive Actual "on Year" Yield Forecast Tool Based on the Tree Canopy Geometry Using UAS Imagery, Reprinted from: Sensors 2017, 17, 1743, doi: 10.3390/s17081743 -- Alfonso Torres-Rua / Vicarious Calibration of sUAS Microbolometer Temperature Imagery for Estimation of Radiometric Land Surface Temperature, Reprinted from: Sensors 2017, 17, 1499, doi: 10.3390/s17071499 -- Mohammad Ammad Uddin, Ali Mansour, Denis Le Jeune, Mohammad Ayaz and el-Hadi M. Aggoune / UAV-Assisted Dynamic Clustering of Wireless Sensor Networks for Crop Health Monitoring, Reprinted from: Sensors 2018, 18, 555, doi: 10.3390/s18020555 -- Fernando Vanegas, Dmitry Bratanov, Kevin Powell, John Weiss and Felipe Gonzalez / A Novel Methodology for Improving Plant Pest Surveillance in Vineyards and Crops Using UAV-Based Hyperspectral and Spatial Data, Reprinted from: Sensors 2018, 18, 260, doi: 10.3390/s18010260 -- Xiaoliang Wang, Peng Jiang, Deshi Li and Tao Sun / Curvature Continuous and Bounded Path Planning for Fixed-Wing UAVs, Reprinted from: Sensors 2017, 17, 2155, doi: 10.3390/s17092155 -- Yi Zhao, Jiale Ma, Xiaohui Li and Jie Zhang / Saliency Detection and Deep Learning-Based Wildfire Identification in UAV Imagery, Reprinted from: Sensors 2018, 18, 712, doi: 10.3390/s18030712 -- Haijing Zheng, Tingzhu Bai, Quanxi Wang, Fengmei Cao, Long Shao and Zhaotian Sun / Experimental Study of Multispectral Characteristics of an Unmanned Aerial Vehicle at Different Observation Angles, Reprinted from: Sensors 2018, 18, 428, doi: 10.3390/s18020428 -- Jiandan Zhong, Tao Lei and Guangle Yao / Robust Vehicle Detection in Aerial Images Based on Cascaded Convolutional Neural Networks, Reprinted from: Sensors 2017, 17, 2720, doi: 10.3390/s17122720.
• Sommario/riassunto: The rapid development and growth of unmanned aerial vehicles (UAVs) as a remote sensing platform, as well as advances in the miniaturization of instrumentation and data systems, have resulted in an increasing uptake of this technology in the environmental and remote sensing science communities. Although tough regulations across the globe may still limit the broader use of UAVs, their use in precision agriculture, ecology, atmospheric research, disaster response biosecurity, ecological and reef monitoring, forestry, fire monitoring, quick response measurements for emergency disaster, Earth science research, volcanic gas sampling, monitoring of gas pipelines, mining plumes, humanitarian observations and biological/chemo-sensing tasks continues to increase. This book provides a forum for high-quality peer-reviewed papers that broaden the awareness and understanding of UAV developments, applications of UAVs for remote sensing, and associated developments in sensor technology, data processing and communications, and UAV system design and sensing capabilities. The book covers the following topics: • improvements in UAV sensor technology; • UAV sensor design; • descriptions of processing algorithms applied to UAV-based imagery datasets; • the use of optical, multi-spectral, hyperspectral, laser, and optical SAR technologies onboard UAVs; • Artificial intelligence and data mining-based strategies from UAV-acquired datasets; • UAV onboard data storage, transmission, and retrieval; • multiple platform UAV, AUV, and ground robot networks; • UAV sensor applications including: precision agriculture, construction, mining, pest detection, forestry, wildlife tracking, atmosphere, wildfire monitoring and prevention, reef monitoring, Earth science research pollution monitoring, micro-climates, land use precision agriculture, ecology, atmospheric research, quick response measurements for emergency disaster.
• Titolo autorizzato: UAV or drones for remote sensing applications
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910598170103321
• Lo trovi qui: Univ. Federico II