UAV Or Drones for Remote Sensing Applications in GPS/GNSS Enabled and GPS/GNSS Denied Environments

UAV Or Drones for Remote Sensing Applications in GPS/GNSS Enabled and GPS/GNSS Denied Environments
Author :
Publisher : Mdpi AG
Total Pages : 400
Release :
ISBN-10 : 3036515909
ISBN-13 : 9783036515908
Rating : 4/5 (908 Downloads)

Book Synopsis UAV Or Drones for Remote Sensing Applications in GPS/GNSS Enabled and GPS/GNSS Denied Environments by : Felipe Gonzalez Toro

Download or read book UAV Or Drones for Remote Sensing Applications in GPS/GNSS Enabled and GPS/GNSS Denied Environments written by Felipe Gonzalez Toro and published by Mdpi AG. This book was released on 2021-11-09 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: The design of novel UAV systems and the use of UAV platforms integrated with robotic sensing and imaging techniques, as well as the development of processing workflows and the capacity of ultra-high temporal and spatial resolution data, have enabled a rapid uptake of UAVs and drones across several industries and application domains. This book provides a forum for high-quality peer-reviewed papers that broaden awareness and understanding of single- and multiple-UAV developments for remote sensing applications, and associated developments in sensor technology, data processing and communications, and UAV system design and sensing capabilities in GPS-enabled and, more broadly, Global Navigation Satellite System (GNSS)-enabled and GPS/GNSS-denied environments. Contributions include: UAV-based photogrammetry, laser scanning, multispectral imaging, hyperspectral imaging, and thermal imaging; UAV sensor applications; spatial ecology; pest detection; reef; forestry; volcanology; precision agriculture wildlife species tracking; search and rescue; target tracking; atmosphere monitoring; chemical, biological, and natural disaster phenomena; fire prevention, flood prevention; volcanic monitoring; pollution monitoring; microclimates; and land use; Wildlife and target detection and recognition from UAV imagery using deep learning and machine learning techniques; UAV-based change detection.


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