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Earth Observations (EO) encompasses different types of sensors (e.g., SAR, LiDAR, Optical and multispectral) and platforms (e.g., satellites, aircraft, and Unmanned Aerial Vehicles) and enables us to monitor and model geohazards over regions at different scales in which ground observations may not be possible due to physical and/or political constraints. EO can provide high spatial, temporal and spectral resolution, stereo-mapping and all-weather-imaging capabilities, but not by a single satellite at a time. Improved satellite and sensor technologies, increased frequency of satellite measurements, and easier access and interpretation of EO information have all contributed to the increased demand for satellite EO data. EO, combined with complementary terrestrial observations and with physical models, have been widely used to monitor geohazards, revolutionizing our understanding of how the Earth system works.

LiDAR --- InSAR --- remote sensing --- earthquake --- UAV --- landslide --- land subsidence --- earth observation --- surface displacement --- geohazards --- deformation --- optical --- damage assessment

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The emerging massive density of human-held and machine-type nodes implies larger traffic deviatiolns in the future than we are facing today. In the future, the network will be characterized by a high degree of flexibility, allowing it to adapt smoothly, autonomously, and efficiently to the quickly changing traffic demands both in time and space. This flexibility cannot be achieved when the network’s infrastructure remains static. To this end, the topic of UAVs (unmanned aerial vehicles) have enabled wireless communications, and networking has received increased attention. As mentioned above, the network must serve a massive density of nodes that can be either human-held (user devices) or machine-type nodes (sensors). If we wish to properly serve these nodes and optimize their data, a proper wireless connection is fundamental. This can be achieved by using UAV-enabled communication and networks. This Special Issue addresses the many existing issues that still exist to allow UAV-enabled wireless communications and networking to be properly rolled out.

Technology: general issues --- History of engineering & technology --- unmanned aerial vehicle --- UAV positioning --- machine learning --- wireless communications --- drones --- network --- DTN --- mobility schedule --- routing algorithms --- data delivery --- Internet of drones --- communication --- security --- privacy --- UAV base station --- MIMO --- millimeter-wave band --- blind beamforming --- signal recovery --- UAV relay networks --- resource management --- transmit time allocation --- unmanned aerial vehicles --- dynamic spectrum access --- quality of service --- reinforcement learning --- multi-armed bandit --- aerial communication --- FANET --- not-spots --- stratospheric communication platform --- UAV --- UAV-assisted network --- 5G --- global positioning system --- GPS spoofing attacks --- detection techniques --- dynamic selection --- hyperparameter tuning --- IoT --- RF radio communication --- Wi-Fi direct --- D2D --- drone-based mobile secure zone --- friendly jamming --- mobility --- internet of things --- non-orthogonal multiple access --- resource allocation --- ultra reliable low latency communication --- uplink transmission --- Deep Q-learning (DQL) --- Double Deep Q-learning (DDQL) --- dynamic spectrum sharing --- High Altitude Platform Station (HAPS) --- cellular communications --- power control --- interference management --- cognitive UAV networks --- clustered two-stage-fusion cooperative spectrum sensing --- continuous hidden Markov model --- SNR estimation --- n/a

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This is an open access book. It offers comprehensive, self-contained knowledge on Mobile Edge Computing (MEC), which is a very promising technology for achieving intelligence in the next-generation wireless communications and computing networks. The book starts with the basic concepts, key techniques and network architectures of MEC. Then, we present the wide applications of MEC, including edge caching, 6G networks, Internet of Vehicles, and UAVs. In the last part, we present new opportunities when MEC meets blockchain, Artificial Intelligence, and distributed machine learning (e.g., federated learning). We also identify the emerging applications of MEC in pandemic, industrial Internet of Things and disaster management. The book allows an easy cross-reference owing to the broad coverage on both the principle and applications of MEC. The book is written for people interested in communications and computer networks at all levels. The primary audience includes senior undergraduates, postgraduates, educators, scientists, researchers, developers, engineers, innovators and research strategists.

Mobile & handheld device programming / Apps programming --- WAP (wireless) technology --- Electrical engineering --- Computing & information technology --- Open Access --- mobile edge computing --- 5G beyond --- 6G --- edge caching --- Internet of Things --- UAV

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Unmanned aerial vehicles (UAV) have already become an affordable and cost-efficient tool to quickly map a targeted area for many emerging applications in the arena of ecological monitoring and biodiversity conservation. Managers, owners, companies, and scientists are using professional drones equipped with high-resolution visible, multispectral, or thermal cameras to assess the state of ecosystems, the effect of disturbances, or the dynamics and changes within biological communities inter alia. We are now at a tipping point on the use of drones for these type of applications over natural areas. UAV missions are increasing but most of them are testing applicability. It is time now to move to frequent revisiting missions, aiding in the retrieval of important biophysical parameters in ecosystems or mapping species distributions. This Special Issue shows UAV applications contributing to a better understanding of biodiversity and ecosystem status, threats, changes, and trends. It documents the enhancement of knowledge in ecological integrity parameters mapping, long-term ecological monitoring based on drones, mapping of alien species spread and distribution, upscaling ecological variables from drone to satellite images: methods and approaches, rapid risk and disturbance assessment using drones, mapping albedo with UAVs, wildlife tracking, bird colony and chimpanzee nest mapping, habitat mapping and monitoring, and a review on drones for conservation in protected areas.

Pinus nigra --- unmanned aerial vehicles (UAVs) --- biological conservation --- precision --- flight altitude --- accuracy --- multiscale approach --- low-cost UAV --- LTER --- small UAV --- ecological monitoring --- Sequoia --- long-term monitoring --- albedo --- image processing --- vegetation indices --- Tanzania --- ground-truth --- Sentinel-2 --- biodiversity threats --- field experiments --- effective management --- great apes --- drone --- ecological integrity --- multispectral --- rice crops --- conservation --- protected areas --- survey --- response surface --- aerial survey --- bird censuses --- multispectral mapping --- drones --- UAS --- hyperspectral --- UAV --- random forest --- Pinus sylvestris --- NDVI --- UAVs --- Parrot Sequoia --- supervised classification --- drone mapping --- RPAS --- greenness index --- image resolution --- Plegadis falcinellus --- Motus --- biodiversity --- Landsat 8 --- Sentinel --- boreal forest --- phenology --- LTSER --- western swamphen --- Parrot SEQUOIA --- native grassland --- forêt Montmorency --- drought --- forest regeneration --- radio-tracking

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This book is the first literature collection focused on the development and implementation of unmanned aircraft systems (UAS) and their integration with sensors for atmospheric measurements on Earth. The research covered in the book combines chemical, physical, and meteorological measurements performed in field campaigns, as well as conceptual and laboratory work. Useful examples for the development of platforms and autonomous systems for environmental studies are provided, which demonstrate how careful the operation of sensors aboard UAS must be to gather information for remote sensing in the atmosphere. The work serves as a key collection of articles to introduce the topic to new researchers interested in the field, guide future studies, and motivate measurements to improve our understanding of the Earth’s complex atmosphere.

Research & information: general --- unmanned aerial vehicles (UAV) --- drones --- geostatistics --- atmospheric physics --- meteorology --- spatial sampling --- unmanned aerial vehicles --- unmanned aerial systems, turbulence --- atmospheric boundary layer --- TK-1G sounding rocket --- near space --- data analysis --- remote sensing --- unmanned aerial systems --- atmospheric composition --- sensors --- UAS --- RPAS --- ALADINA --- airborne turbulence --- radiation measurements --- aerosol measurements --- field experiments --- validation methods --- unmanned aircraft --- meteorological observation --- stable atmospheric boundary layer --- turbulence --- remotely piloted aircraft systems (RPAS) --- ground-based in-situ observations --- boundary layer remote sensing --- Arctic --- polar --- sea ice --- n/a --- source estimation --- methane emissions --- natural gas --- leak surveys --- inverse emissions --- MONITOR --- UAV --- LDAR --- air pollution --- unmanned aerial vehicle (UAV) --- PM2.5 --- meteorological condition --- long-distance transport --- satellite data --- RMLD-UAV --- methane --- mass flux --- leak rate quantification --- wind speed and direction estimation algorithms --- flow probes --- airspeed measurement --- small unmanned aircraft systems (sUAS)