pubmed_data.csv

ResearchQuestion,PubMedQuery,PMID,Title,Source,Doi,Author_1,Author_2,Author_3,Author_4,Author_5,Author_6,Author_7,Author_8,Author_9,Author_10,Author_11,Author_12,Author_13,Author_14,Author_15,Author_16,Author_17,Author_18,Author_19,Author_20,Collective_Name,PubYear,PubMonth,PubDay,OriginalPubDate,Abstract,DOI,DOI_Link,PMC_ID,PMC_Link,MeSH_1,Keyword_1,MeSH_2,Keyword_2,MeSH_3,Keyword_3,MeSH_4,Keyword_4,MeSH_5,Keyword_5,MeSH_6,Keyword_6,MeSH_7,Keyword_7,MeSH_8,Keyword_8,MeSH_9,Keyword_9,MeSH_10,Keyword_10,MeSH_11,Keyword_11,MeSH_12,Keyword_12,MeSH_13,Keyword_13,MeSH_14,Keyword_14,MeSH_15,Keyword_15,MeSH_16,Keyword_16,MeSH_17,Keyword_17,MeSH_18,Keyword_18,MeSH_19,Keyword_19,MeSH_20,Keyword_20,MeSH_21,Keyword_21,MeSH_22,Keyword_22,MeSH_23,Keyword_23,MeSH_24,Keyword_24,MeSH_25,Keyword_25,MeSH_26,Keyword_26,MeSH_27,Keyword_27,MeSH_28,Keyword_28,MeSH_29,Keyword_29,MeSH_30,Keyword_30,geometryHeight,geometryScaleMode,pmid,includeArticle,Notes,Rating,Tags
how do drones work at sea?,drone sea measurement,26730457,Characterization of a Quadrotor Unmanned Aircraft System for Aerosol-Particle-Concentration Measurements.,Environ Sci Technol,,Brady JM,Stokes MD,Bonnardel J,Bertram TH,,,,,,,,,,,,,,,,,,2016,Feb,2,2016 Feb 2,"High-spatial-resolution, near-surface vertical profiling of atmospheric chemical composition is currently limited by the availability of experimental platforms that can sample in constrained environments. As a result, measurements of near-surface gradients in trace gas and aerosol particle concentrations have been limited to studies conducted from fixed location towers or tethered balloons. Here, we explore the utility of a quadrotor unmanned aircraft system (UAS) as a sampling platform to measure vertical and horizontal concentration gradients of trace gases and aerosol particles at high spatial resolution (1 m) within the mixed layer (0-100 m). A 3D Robotics Iris+ autonomous quadrotor UAS was outfitted with a sensor package consisting of a two-channel aerosol optical particle counter and a CO2 sensor. The UAS demonstrated high precision in both vertical (±0.5 m) and horizontal positions (±1 m), highlighting the potential utility of quadrotor UAS drones for aerosol- and trace-gas measurements within complex terrain, such as the urban environment, forest canopies, and above difficult-to-access areas such as breaking surf. Vertical profiles of aerosol particle number concentrations, acquired from flights conducted along the California coastline, were used to constrain sea-spray aerosol-emission rates from coastal wave breaking.",10.1021/acs.est.5b05320,https://doi.org/10.1021/acs.est.5b05320,,,Aerosols,,Air Pollutants,,Aircraft,,California,,Particle Size,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.8,none,26730457,true,,,
how do drones work at sea?,drone sea measurement,27589770,Combining Remote Temperature Sensing with in-Situ Sensing to Track Marine/Freshwater Mixing Dynamics.,Sensors (Basel),,McCaul M,Barland J,Cleary J,Cahalane C,McCarthy T,Diamond D,,,,,,,,,,,,,,,,2016,Aug,31,2016 Aug 31,"The ability to track the dynamics of processes in natural water bodies on a global scale, and at a resolution that enables highly localised behaviour to be visualized, is an ideal scenario for understanding how local events can influence the global environment. While advances in in-situ chem/bio-sensing continue to be reported, costs and reliability issues still inhibit the implementation of large-scale deployments. In contrast, physical parameters like surface temperature can be tracked on a global scale using satellite remote sensing, and locally at high resolution via flyovers and drones using multi-spectral imaging. In this study, we show how a much more complete picture of submarine and intertidal groundwater discharge patterns in Kinvara Bay, Galway can be achieved using a fusion of data collected from the Earth Observation satellite (Landsat 8), small aircraft and in-situ sensors. Over the course of the four-day field campaign, over 65,000 in-situ temperatures, salinity and nutrient measurements were collected in parallel with high-resolution thermal imaging from aircraft flyovers. The processed in-situ data show highly correlated patterns between temperature and salinity at the southern end of the bay where freshwater springs can be identified at low tide. Salinity values range from 1 to 2 ppt at the southern end of the bay to 30 ppt at the mouth of the bay, indicating the presence of a freshwater wedge. The data clearly show that temperature differences can be used to track the dynamics of freshwater and seawater mixing in the inner bay region. This outcome suggests that combining the tremendous spatial density and wide geographical reach of remote temperature sensing (using drones, flyovers and satellites) with ground-truthing via appropriately located in-situ sensors (temperature, salinity, chemical, and biological) can produce a much more complete and accurate picture of the water dynamics than each modality used in isolation.",10.3390/s16091402,https://doi.org/10.3390/s16091402,PMC5038680,https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5038680/,,groundwater,,in-situ sensing,,nutrients,,remote sensing,,salinity,,sea-surface temperature,,sensor networks,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.8,none,27589770,true,,,
how do drones work at sea?,drone sea measurement,29208716,Direct measurements of meltwater runoff on the Greenland ice sheet surface.,Proc Natl Acad Sci U S A,,Smith LC,Yang K,Pitcher LH,Overstreet BT,Chu VW,Rennermalm ÅK,Ryan JC,Cooper MG,Gleason CJ,Tedesco M,Jeyaratnam J,van As D,van den Broeke MR,van de Berg WJ,Noël B,Langen PL,Cullather RI,Zhao B,Willis MJ,Hubbard A,,2017,Dec,12,2017 Dec 12,"Meltwater runoff from the Greenland ice sheet surface influences surface mass balance (SMB), ice dynamics, and global sea level rise, but is estimated with climate models and thus difficult to validate. We present a way to measure ice surface runoff directly, from hourly in situ supraglacial river discharge measurements and simultaneous high-resolution satellite/drone remote sensing of upstream fluvial catchment area. A first 72-h trial for a 63.1-km2 moulin-terminating internally drained catchment (IDC) on Greenland's midelevation (1,207-1,381 m above sea level) ablation zone is compared with melt and runoff simulations from HIRHAM5, MAR3.6, RACMO2.3, MERRA-2, and SEB climate/SMB models. Current models cannot reproduce peak discharges or timing of runoff entering moulins but are improved using synthetic unit hydrograph (SUH) theory. Retroactive SUH applications to two older field studies reproduce their findings, signifying that remotely sensed IDC area, shape, and supraglacial river length are useful for predicting delays in peak runoff delivery to moulins. Applying SUH to HIRHAM5, MAR3.6, and RACMO2.3 gridded melt products for 799 surrounding IDCs suggests their terminal moulins receive lower peak discharges, less diurnal variability, and asynchronous runoff timing relative to climate/SMB model output alone. Conversely, large IDCs produce high moulin discharges, even at high elevations where melt rates are low. During this particular field experiment, models overestimated runoff by +21 to +58%, linked to overestimated surface ablation and possible meltwater retention in bare, porous, low-density ice. Direct measurements of ice surface runoff will improve climate/SMB models, and incorporating remotely sensed IDCs will aid coupling of SMB with ice dynamics and subglacial systems.",10.1073/pnas.1707743114,https://doi.org/10.1073/pnas.1707743114,PMC5740616,https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5740616/,,climate models,,fluvial catchment,,ice sheet meltwater runoff,,surface mass balance,,surface water hydrology,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.8,none,29208716,true,,,
how do drones work at sea?,drone sea measurement,29561901,"Measuring behavioral responses of sea turtles, saltwater crocodiles, and crested terns to drone disturbance to define ethical operating thresholds.",PLoS One,,Bevan E,Whiting S,Tucker T,Guinea M,Raith A,Douglas R,,,,,,,,,,,,,,,,2018,,,2018,"Drones are being increasingly used in innovative ways to enhance environmental research and conservation. Despite their widespread use for wildlife studies, there are few scientifically justified guidelines that provide minimum distances at which wildlife can be approached to minimize visual and auditory disturbance. These distances are essential to ensure that behavioral and survey data have no observer bias and form the basis of requirements for animal ethics and scientific permit approvals. In the present study, we documented the behaviors of three species of sea turtle (green turtles, Chelonia mydas, flatback turtles, Natator depressus, hawksbill turtles, Eretmochelys imbricata), saltwater crocodiles (Crocodylus porosus), and crested terns (Thalasseus bergii) in response to a small commercially available (1.4 kg) multirotor drone flown in Northern Territory and Western Australia. Sea turtles in nearshore waters off nesting beaches or in foraging habitats exhibited no evasive behaviors (e.g. rapid diving) in response to the drone at or above 20-30 m altitude, and at or above 10 m altitude for juvenile green and hawksbill turtles foraging on shallow, algae-covered reefs. Adult female flatback sea turtles were not deterred by drones flying forward or stationary at 10 m altitude when crawling up the beach to nest or digging a body pit or egg chamber. In contrast, flyovers elicited a range of behaviors from crocodiles, including minor, lateral head movements, fleeing, or complete submergence when a drone was present below 50 m altitude. Similarly, a colony of crested terns resting on a sand-bank displayed disturbance behaviors (e.g. flight response) when a drone was flown below 60 m altitude. The current study demonstrates a variety of behavioral disturbance thresholds for diverse species and should be considered when establishing operating conditions for drones in behavioral and conservation studies.",10.1371/journal.pone.0194460,https://doi.org/10.1371/journal.pone.0194460,PMC5862495,https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5862495/,Alligators and Crocodiles,,Animals,,Australia,,"Behavior, Animal",,Turtles,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.8,none,29561901,true,,,
how do drones work at sea?,drone sea measurement,29653153,Unmanned aerial vehicles (drones) to prevent drowning.,Resuscitation,,Seguin C,Blaquière G,Loundou A,Michelet P,Markarian T,,,,,,,,,,,,,,,,,2018,Jun,,2018 Jun,"BACKGROUND: Drowning literature have highlighted the submersion time as the most powerful predictor in assessing the prognosis. Reducing the time taken to provide a flotation device and prevent submersion appears of paramount importance. Unmanned aerial vehicles (UAVs) can provide the location of the swimmer and a flotation device. OBJECTIVE: The objective of this simulation study was to evaluate the efficiency of a UAV in providing a flotation device in different sea conditions, and to compare the times taken by rescue operations with and without a UAV (standard vs UAV intervention). Several comparisons were made using professional lifeguards acting as simulated victims. A specifically-shaped UAV was used to allow us to drop an inflatable life buoy into the water. RESULTS: During the summer of 2017, 28 tests were performed. UAV use was associated with a reduction of time it took to provide a flotation device to the simulated victim compared with standard rescue operations (p < 0.001 for all measurements) and the time was reduced even further in moderate (81 ± 39 vs 179 ± 78 s; p < 0.001) and rough sea conditions (99 ± 34 vs 198 ± 130 s; p < 0.001). The times taken for UAV to locate the simulated victim, identify them and drop the life buoy were not altered by the weather conditions. CONCLUSION: UAV can deliver a flotation device to a swimmer safely and quickly. The addition of a UAV in rescue operations could improve the quality and speed of first aid while keeping lifeguards away from dangerous sea conditions.",10.1016/j.resuscitation.2018.04.005,https://doi.org/10.1016/j.resuscitation.2018.04.005,,,Aircraft,Drone,Drowning,Drowning,Humans,Lifeguards,Patient Simulation,Rescue,Prospective Studies,Simulation,Rescue Work,Unmanned aerial vehicles,Time Factors,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.8,none,29653153,true,,,
how do drones work at sea?,drone sea measurement,31558588,Scaling of swimming performance in baleen whales.,J Exp Biol,,Gough WT,Segre PS,Bierlich KC,Cade DE,Potvin J,Fish FE,Dale J,di Clemente J,Friedlaender AS,Johnston DW,Kahane-Rapport SR,Kennedy J,Long JH,Oudejans M,Penry G,Savoca MS,Simon M,Videsen SKA,Visser F,Wiley DN,,2019,Oct,23,2019 Oct 23,"The scale dependence of locomotor factors has long been studied in comparative biomechanics, but remains poorly understood for animals at the upper extremes of body size. Rorqual baleen whales include the largest animals, but we lack basic kinematic data about their movements and behavior below the ocean surface. Here, we combined morphometrics from aerial drone photogrammetry, whale-borne inertial sensing tag data and hydrodynamic modeling to study the locomotion of five rorqual species. We quantified changes in tail oscillatory frequency and cruising speed for individual whales spanning a threefold variation in body length, corresponding to an order of magnitude variation in estimated body mass. Our results showed that oscillatory frequency decreases with body length (∝length-0.53) while cruising speed remains roughly invariant (∝length0.08) at 2 m s-1 We compared these measured results for oscillatory frequency against simplified models of an oscillating cantilever beam (∝length-1) and an optimized oscillating Strouhal vortex generator (∝length-1). The difference between our length-scaling exponent and the simplified models suggests that animals are often swimming non-optimally in order to feed or perform other routine behaviors. Cruising speed aligned more closely with an estimate of the optimal speed required to minimize the energetic cost of swimming (∝length0.07). Our results are among the first to elucidate the relationships between both oscillatory frequency and cruising speed and body size for free-swimming animals at the largest scale.",10.1242/jeb.204172,https://doi.org/10.1242/jeb.204172,,,Animals,Frequency,Regression Analysis,Hydrodynamic modeling,Species Specificity,Locomotion,Swimming,Morphometrics,Whales,Speed,,Unoccupied aerial systems,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.8,none,31558588,true,,,
how do drones work at sea?,drone sea measurement,33203050,Dimensioning Method of Floating Offshore Objects by Means of Quasi-Similarity Transformation with Reduced Tolerance Errors.,Sensors (Basel),,Stępień G,Tomczak A,Loosaar M,Ziębka T,,,,,,,,,,,,,,,,,,2020,Nov,13,2020 Nov 13,"The human activities in the offshore oil and gas, renewable energy and construction industry require reliable data acquired by different types of hydrographic sensors: DGNSS (Differential Global Navigation Satellite System) positioning, attitude sensors, multibeam sonars, lidars or total stations installed on the offshore vessel, drones or platforms. Each component or sensor that produces information, unique to its position, will have a point that is considered as the reference point of that sensor. The accurate measurement of the offsets is vital to establish the mathematical relation between sensor and vessel common reference point in order to achieve sufficient accuracy of the survey data. If possible, the vessel will be put on a hard stand so that it can be very accurately measured using the standard land survey technique. However, due to the complex environment and sensors being mobilized when the vessel is in service, this may not be possible, and the offsets will have to be measured in sea dynamic conditions by means of a total station from a floating platform. This article presents the method of transformation by similarity with elements of affine transformation, called Q-ST (Quasi-Similarity Transformation). The Q-ST has been designed for measurements on such unstable substrates when it is not possible to level the total station (when the number of adjustment points is small (4-6 points)). Such situation occurs, among others, when measuring before the offshore duties or during the jack up or semi-submersible rig move. The presented calculation model is characterized by zero deviations at the adjustment points (at four common points). The transformation concerns the conversion of points between two orthogonal and inclined reference frames. The method enables the independent calculation of the scale factor, rotation matrix and system translation. Scaling is performed first in real space, and then both systems are shifted to the centroid, which is the center of gravity. The center of gravity is determined for the fit points that meet the criterion of stability of the orthogonal transformation. Then, the rotation matrix is computed, and a translation is performed from the computational (centroid) to real space. In the applied approach, the transformation parameters, scaling, rotation and translation, are determined independently, and the least squares method is applied independently at each stage of the calculations. The method has been verified in laboratory conditions as well as in real conditions. The results were compared to other known methods of coordinate transformation. The proposed approach is a development of the idea of transformation by similarity based on centroids.",10.3390/s20226497,https://doi.org/10.3390/s20226497,PMC7709043,https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7709043/,,affine transformation,,close range photogrammetry,,dimensional control,,offshore surveying,,orthogonal coordinate system,,rotation matrix,,similarity transformation,,total station,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.8,none,33203050,true,,,
how do drones work at sea?,drone sea measurement,33486249,Automatic detection and quantification of floating marine macro-litter in aerial images: Introducing a novel deep learning approach connected to a web application in R.,Environ Pollut,,Garcia-Garin O,Monleón-Getino T,López-Brosa P,Borrell A,Aguilar A,Borja-Robalino R,Cardona L,Vighi M,,,,,,,,,,,,,,2021,Mar,15,2021 Mar 15,"The threats posed by floating marine macro-litter (FMML) of anthropogenic origin to the marine fauna, and marine ecosystems in general, are universally recognized. Dedicated monitoring programmes and mitigation measures are in place to address this issue worldwide, with the increasing support of new technologies and the automation of analytical processes. In the current study, we developed algorithms capable of detecting and quantifying FMML in aerial images, and a web-oriented application that allows users to identify FMML within images of the sea surface. The proposed algorithm is based on a deep learning approach that uses convolutional neural networks (CNNs) capable of learning from unstructured or unlabelled data. The CNN-based deep learning model was trained and tested using 3723 aerial images (50% containing FMML, 50% without FMML) taken by drones and aircraft over the waters of the NW Mediterranean Sea. The accuracies of image classification (performed using all the images for training and testing the model) and cross-validation (performed using 90% of images for training and 10% for testing) were 0.85 and 0.81, respectively. The Shiny package of R was then used to develop a user-friendly application to identify and quantify FMML within the aerial images. The implementation of this, and similar algorithms, allows streamlining substantially the detection and quantification of FMML, providing support to the monitoring and assessment of this environmental threat. However, the automated monitoring of FMML in the open sea still represents a technological challenge, and further research is needed to improve the accuracy of current algorithms.",10.1016/j.envpol.2021.116490,https://doi.org/10.1016/j.envpol.2021.116490,,,,Convolutional neural network,,Machine learning,,Marine litter,,Remote sensing,,Unmanned aerial vehicles,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.8,none,33486249,true,,,
how do drones work at sea?,drone sea measurement,33617554,Accuracy and precision of citizen scientist animal counts from drone imagery.,PLoS One,,Wood SA,Robinson PW,Costa DP,Beltran RS,,,,,,,,,,,,,,,,,,2021,,,2021,"Repeated counts of animal abundance can reveal changes in local ecosystem health and inform conservation strategies. Unmanned aircraft systems (UAS), also known as drones, are commonly used to photograph animals in remote locations; however, counting animals in images is a laborious task. Crowd-sourcing can reduce the time required to conduct these censuses considerably, but must first be validated against expert counts to measure sources of error. Our objectives were to assess the accuracy and precision of citizen science counts and make recommendations for future citizen science projects. We uploaded drone imagery from Año Nuevo Island (California, USA) to a curated Zooniverse website that instructed citizen scientists to count seals and sea lions. Across 212 days, over 1,500 volunteers counted animals in 90,000 photographs. We quantified the error associated with several descriptive statistics to extract a single citizen science count per photograph from the 15 repeat counts and then compared the resulting citizen science counts to expert counts. Although proportional error was relatively low (9% for sea lions and 5% for seals during the breeding seasons) and improved with repeat sampling, the 12+ volunteers required to reduce error was prohibitively slow, taking on average 6 weeks to estimate animals from a single drone flight covering 25 acres, despite strong public outreach efforts. The single best algorithm was 'Median without the lowest two values', demonstrating that citizen scientists tended to under-estimate the number of animals present. Citizen scientists accurately counted adult seals, but accuracy was lower when sea lions were present during the summer and could be confused for seals. We underscore the importance of validation efforts and careful project design for researchers hoping to combine citizen science with imagery from drones, occupied aircraft, and/or remote cameras.",10.1371/journal.pone.0244040,https://doi.org/10.1371/journal.pone.0244040,PMC7899343,https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7899343/,Aircraft,,Animals,,Citizen Science,,Ecosystem,,Fur Seals,,Humans,,Population Dynamics,,Sea Lions,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.8,none,33617554,true,,,
how do drones work at sea?,drone sea measurement,34640826,Bi-Spectral Infrared Algorithm for Cloud Coverage over Oceans by the JEM-EUSO Mission Program.,Sensors (Basel),,Santalices D,Briz S,de Castro AJ,López F,,,,,,,,,,,,,,,,,,2021,Sep,29,2021 Sep 29,"The need to monitor specific areas for different applications requires high spatial and temporal resolution. This need has led to the proliferation of ad hoc systems on board nanosatellites, drones, etc. These systems require low cost, low power consumption, and low weight. The work we present follows this trend. Specifically, this article evaluates a method to determine the cloud map from the images provided by a simple bi-spectral infrared camera within the framework of JEM-EUSO (The Joint Experiment Missions-Extrem Universe Space Observatory). This program involves different experiments whose aim is determining properties of Ultra-High Energy Cosmic Ray (UHECR) via the detection of atmospheric fluorescence light. Since some of those projects use UV instruments on board space platforms, they require knowledge of the cloudiness state in the FoV of the instrument. For that reason, some systems will include an infrared (IR) camera. This study presents a test to generate a binary cloudiness mask (CM) over the ocean, employing bi-spectral IR data. The database is created from Moderate-Resolution Imaging Spectroradiometer (MODIS) data (bands 31 and 32). The CM is based on a split-window algorithm. It uses an estimation of the brightness temperature calculated from a statistical study of an IR images database along with an ancillary sea surface temperature. This statistical procedure to obtain the estimate of the brightness temperature is one of the novel contributions of this work. The difference between the measured and estimation of the brightness temperature determines whether a pixel is cover or clear. That classification requires defining several thresholds which depend on the scenarios. The procedure for determining those thresholds is also novel. Then, the results of the algorithm are compared with the MODIS CM. The agreement is above 90%. The performance of the proposed CM is similar to that of other studies. The validation also shows that cloud edges concentrate the vast majority of discrepancies with the MODIS CM. The relatively high accuracy of the algorithm is a relevant result for the JEM-EUSO program. Further work will combine the proposed algorithm with complementary studies in the framework of JEM-EUSO to reinforce the CM above the cloud edges.",10.3390/s21196506,https://doi.org/10.3390/s21196506,PMC8512583,https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8512583/,,JEM-EUSO,,cloud coverage,,infrared camera,,remote sensing,,split-window algorithm,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.8,none,34640826,true,,,
how do drones work at sea?,drone sea measurement,35454194,Unmanned Aircraft Systems as a Powerful Tool to Detect Fine-Scale Spatial Positioning and Interactions between Waterbirds at High-Tide Roosts.,Animals (Basel),,Castenschiold JHF,Bregnballe T,Bruhn D,Pertoldi C,,,,,,,,,,,,,,,,,,2022,Apr,7,2022 Apr 7,"The surveillance of behavioral interactions between individuals in bird populations is important to understand social dynamics and explain distribution patterns caused by competition for food and space. For waterbirds, little is known about interactions between individuals at high-tide roosts. In the present study, we used surveying with unmanned aircraft systems (UASs) to provide enhanced information on previously hidden aspects of the highly dynamic communities of roosting waterbirds in the non-breeding season. Fine-scale density estimations, derived from aerial photos obtained with UASs, were used as a measure to explain intra- and inter-species interactions for 10 selected waterbird species on a major roost site in the Danish Wadden Sea. Uniquely defined density distributions were detected, which, to some degree, were dependent on species and species size, with smaller waders exhibiting densely packed flocks (e.g., dunlin Calidris alpina and golden plover Pluvialis apricaria), whereas larger species, such as ducks and geese (Anatidae) exhibited lower densities. Multi-species flocks were observed to occur frequently (31.9%) and generally resulted in lower densities than single-species flocks for each of the species involved. Furthermore, it has been demonstrated that UAS aerial photos can be used both to assess positions for roosting waterbirds and to classify habitats (i.e., mudflats, vegetated areas, waterline, and flooded areas) during high-tide. This facilitated the collection of precise data for temporal habitat choices for individual species when using the studied roost site. Our study highlights UAS surveys as an effective tool to gather hitherto unobtainable data for individual occurrences of roosting waterbirds on a spatiotemporal scale.",10.3390/ani12080947,https://doi.org/10.3390/ani12080947,PMC9030221,https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9030221/,,choice of roosting habitat,,competitive behavior,,density distributions,,drone,,ducks,,flock structure,,geese,,inter-species interactions,,spatiotemporal positioning,,waders,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.8,none,35454194,true,,,
how do drones work at sea?,drone sea measurement,35561617,Can we quantify the aquatic environmental plastic load from aquaculture?,Water Res,,Tian Y,Yang Z,Yu X,Jia Z,Rosso M,Dedman S,Zhu J,Xia Y,Zhang G,Yang J,Wang J,,,,,,,,,,,2022,Jul,1,2022 Jul 1,"Aquaculture provides livelihoods for hundreds of millions of people, but it also forms a significant source of plastic litter that poses a serious hazard to aquatic ecosystems. How to assess and subsequently manage plastic loads from aquaculture is a pending and pressing issue for aquaculture sustainability, and an important concern for water environment monitoring and management. In this study, we developed the first framework for estimating plastic litter from aquaculture by combining data from satellite remote sensing, drones, questionnaires, and in situ measurements. By acquiring multidimensional (human and nature) and multiscale (centimeter to basin scale) data, this framework helped us understand the aquaculture farming patterns and its spatial and temporal evolution, and thus estimate the plastic load it generates and suggest effective management approaches. Applying this framework, we assessed the marine plastic load from oyster floating raft farming in the Maowei Sea, a typical mariculture bay in China, with an increasing farming area. Approximately 3840 tons of plastic waste is expected to be discharged into the sea in the next four years (the average service life of a floating raft) without improvements in aquaculture waste management. Strengthening governance, timely plastic removal, innovative replacement, and transforming farmers' behavior patterns are recommended as the subsequent measures for plastic management. This framework can be extended to other regions and other aquaculture patterns, and is applicable to local, regional, and global aquaculture plastic litter assessments. It is a source-based method for evaluating plastic pollution that is more conducive to subsequent plastic management than traditional post-contamination environmental monitoring. In the context of the global expansion of mariculture and the global commitment to action to combat plastic pollution, this approach could play a critical role in the investigation and management of plastic waste in aquatic environments.",10.1016/j.watres.2022.118551,https://doi.org/10.1016/j.watres.2022.118551,,,Aquaculture,Aquaculture,Ecosystem,Plastic load,Environmental Monitoring,Satellite remote sensing,Environmental Pollution,Source of microplastics,Humans,UAV,Plastics,,"Water Pollutants, Chemical",,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.8,none,35561617,true,,,
how do drones work at sea?,drone sea measurement,36088931,Observation of anomalous spectral downshifting of waves in the Okhotsk Sea Marginal Ice Zone.,Philos Trans A Math Phys Eng Sci,,Waseda T,Alberello A,Nose T,Toyota T,Kodaira T,Fujiwara Y,,,,,,,,,,,,,,,,2022,Oct,31,2022 Oct 31,"Waves in the Marginal Ice Zone in the Okhotsk Sea are less studied compared to the Antarctic and Arctic. In February 2020, wave observations were conducted for the first time in the Okhotsk Sea, during the observational program by Patrol Vessel Soya. A wave buoy was deployed on the ice, and in situ wave observations were made by a ship-borne stereo imaging system and Inertial Measurement Unit. Sea ice was observed visually and by aerial photographs by drone, while satellite synthetic aperture radar provided basin-wide spatial distribution. On 12 February, a swell system propagating from east northeast was detected by both the stereo imaging system and the buoy-on-ice. The wave system attenuated from 0.34 m significant wave height to 0.25 m in about 90 km, while the wave period increased from 10 s to 15-17 s. This anomalous spectral downshifting was not reproduced by numerical hindcast and by applying conventional frequency-dependent exponential attenuation to the incoming frequency spectrum. The estimated rate of spectral downshifting, defined as a ratio of momentum and energy losses, was close to that of uni-directional wave evolution accompanied by breaking dissipation: this indicates that dissipation-driven nonlinear downshifting may be at work for waves propagating in ice. This article is part of the theme issue 'Theory, modelling and observations of marginal ice zone dynamics: multidisciplinary perspectives and outlooks'.",10.1098/rsta.2021.0256,https://doi.org/10.1098/rsta.2021.0256,,,,Marginal Ice Zone,,nonlinear wave interaction,,ocean waves,,spectral downshifting,,wave attenuation,,wave modelling,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.8,none,36088931,true,,,
how do drones work at sea?,drone sea measurement,36616890,The Use of Green Laser in LiDAR Bathymetry: State of the Art and Recent Advancements.,Sensors (Basel),,Szafarczyk A,Toś C,,,,,,,,,,,,,,,,,,,,2022,Dec,27,2022 Dec 27,"Bathymetric LiDAR technology is a technology used for simultaneous data acquisition regarding the morphology of the bottom of water reservoirs and the surrounding coastal zone, realized from the air, e.g., by plane or drone. Contrary to the air topographic LiDAR, which uses an infrared wavelength of 1064 nm, bathymetric LiDAR systems additionally use a green wavelength of 532 nm. The green laser can penetrate the water, which makes it possible to measure the depth of shallow water reservoirs, rivers, and coastal sea waters within three Secchi depths. This article presents the theoretical basis for the construction of a green laser. Against the background of other methods of measuring the bottom of water reservoirs, the technology using waves from the visible light range is presented in detail in the assessment of the bottom morphology of shallow water reservoirs. The possibilities of using green laser in lidar bathymetry implemented in particular in non-navigable regions are shown. The results of the researchers' work on river processes (erosion, sedimentation), design of stream restoration, determination of morphometric parameters of the riverbed, as well as assessment of the topography of the marine coastal bottom zones are summarized. The development direction of lidar bathymetry is discussed.",10.3390/s23010292,https://doi.org/10.3390/s23010292,PMC9824562,https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9824562/,,LiDAR bathymetry,,Secchi depth,,abrasion,,bottom surface morphology,,coastal zones,,fluvial processes,,green laser,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.8,none,36616890,true,,,
how do drones work at sea?,drone sea measurement,36623360,Quantifying seaweed and seagrass beach deposits using high-resolution UAV imagery.,J Environ Manage,,Li Y,Gundersen H,Poulsen RN,Xie L,Ge Z,Hancke K,,,,,,,,,,,,,,,,2023,Apr,1,2023 Apr 1,"Macroalgae and seagrass wash ashore by tidal waters and episodic events and create an ocean-to-land transport of carbon and nutrients. On land, these deposits (beach wrack) are consumed by macrofauna, remineralized by microorganisms, or washed back to the sea, during which recycling of carbon and nitrogen affect the biochemical cycles in coastal zones. Manual quantification of beach wracks is time-consuming and often difficult due to complex topography and remote locations. Here, we present a novel method using Unoccupied Aerial Vehicle (UAV) photogrammetry combined with in situ measurements of carbon and nitrogen contents of wrack to quantify marine carbon and nutrient deposits in beach zones. The UAV method was tested against placed cubes ranging from 125 to 88,218 cm3 and demonstrated a high accuracy (R2 > 0.99) for volume acquisition when compared to manual measurements. Also, the UAV-based assessments of the cross-sectional area of beach deposits demonstrated a high accuracy when compared to manual and high-precision GNSS (Global Navigation Satellite System) measurements without significant differences between the methods. This demonstrated that UAVs can provide detailed spatial maps, three-dimensional (3D) surface models, and accurate volumetric assessments of beach wrack deposits. In three case studies, combined with carbon and nitrogen measures, total organic carbon and nitrogen deposits in beach wracks were quantified ranging from 4.3 to 9.7 and from 0.3 to 0.5 kg per meter coastline, respectively. In conclusion, this UAV method demonstrated an effective tool to quantify ecosystem carbon and nitrogen deposits relevant to ecosystem assessments and quantification of blue carbon stocks. The method is optimal when the terrain below beach wrack deposits is known, as in the case with before-and-after or repeated surveys. Further, UAVs display strong time- and cost-effective advantages over manual methods which is amplified with increasing project scale. We propose it as a valuable method for multiple scientific and commercial applications related to environmental monitoring and management, including marine resource exploration and exploitation.",10.1016/j.jenvman.2022.117171,https://doi.org/10.1016/j.jenvman.2022.117171,,,Ecosystem,Beach deposits,Seaweed,Carbon,Environmental Monitoring,Drones,Carbon,Macroalgae,Nitrogen,Seagrass,,UAV photogrammetry,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.8,none,36623360,true,,,
how do drones work at sea?,drone sea measurement,37299725,Channel Characterization and Modeling for 6G UAV-Assisted Emergency Communications in Complicated Mountainous Scenarios.,Sensors (Basel),,Zhang Z,Liu Y,Huang J,Zhang J,Li J,He R,,,,,,,,,,,,,,,,2023,May,23,2023 May 23,"Regarding the new demands and challenges of sixth-generation (6G) mobile communications, wireless networks are undergoing a significant shift from traditional terrestrial networks to space-air-ground-sea-integrated networks. Unmanned aerial vehicle (UAV) communications in complicated mountainous scenarios are typical applications and have practical implications, especially in emergency communications. In this paper, the ray-tracing (RT) method was applied to reconstruct the propagation scenario and then acquire the wireless channel data. Channel measurements are also conducted in real mountainous scenarios for verification. By setting different flight positions, trajectories, and altitudes, channel data in the millimeter wave (mmWave) band was obtained. Important statistical properties, such as the power delay profile (PDP), Rician K-factor, path loss (PL), root mean square (RMS) delay spread (DS), RMS angular spreads (ASs), and channel capacity were compared and analyzed. The effects of different frequency bands on channel characteristics at 3.5 GHz, 4.9 GHz, 28 GHz, and 38 GHz bands in mountainous scenarios were considered. Furthermore, the effects of extreme weather, especially different precipitation, on the channel characteristics were analyzed. The related results can provide fundamental support for the design and performance evaluation of future 6G UAV-assisted sensor networks in complicated mountainous scenarios.",10.3390/s23114998,https://doi.org/10.3390/s23114998,PMC10255449,https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10255449/,Unmanned Aerial Devices,6G,Communication,UAV-assisted emergency communications,Altitude,channel characteristics,Reproduction,millimeter wave,,mountainous scenarios,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.8,none,37299725,true,,,
how do drones work at sea?,drone sea measurement,37529684,Compact and modular autonomous surface vehicle for water research: The Naval Operating Research Drone Assessing Climate Change (NORDACC).,HardwareX,,Carlson DF,Akbulut S,Rasmussen JF,Hestbech CS,Andersen MH,Melvad C,,,,,,,,,,,,,,,,2023,Sep,,2023 Sep,"Research, monitoring, and management of marine and aquatic ecosystems often require surface water samples to measure biogeochemical and optical parameters. Traditional sampling with a boat and several personnel onboard can be labor-intensive and safety requirements limit sampling activities in high-risk environments. This paper describes the Naval Operating Research Drone Assessing Climate Change (NORDACC). NORDACC is an open source, light-weight, and portable autonomous surface vehicle that can acquire surface water samples while also measuring sea surface temperature and salinity for the duration of its deployment. NORDACC is ideal for operations in remote areas where resources and personnel are limited. Two sample bottles, each one liter in volume, can be filled, either at pre-programmed sampling stations or manually, using the remote control. A trimaran design provides buoyancy and stability, with hulls constructed of vacuum-formed acrylonitrile butadiene styrene (ABS) plastic. NORDACC can navigate autonomously between waypoints and features first person view capabilities for enhanced situational awareness. NORDACC's performance was validated in Aarhus Bay, Denmark, collecting multiple surface water samples in winds in excess of 8 ms-1 and steep, choppy waves.",10.1016/j.ohx.2023.e00453,https://doi.org/10.1016/j.ohx.2023.e00453,PMC10387611,https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10387611/,,Autonomous surface vehicle,,Surface water sample,,Water quality,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.8,none,37529684,true,,,
how do drones work at sea?,drone sea measurement,39009747,"Integrated monitoring and prediction of thermal discharge from nuclear power plants using satellite, UAV, and numerical simulation.",Environ Monit Assess,,Wang L,Li G,Shi H,Zhu J,Zhan C,Zhang X,Wang Q,,,,,,,,,,,,,,,2024,Jul,15,2024 Jul 15,"Global nuclear power is surging ahead in its quest for global carbon neutrality, eyeing an anticipated installed capacity of 436 GW for coastal nuclear power plants by 2040. As these plants operate, they emit substantial amounts of warm water into the ocean, known as thermal discharge, to regulate the temperature of their nuclear reactors. This discharge has the potential to elevate the temperature of the surrounding seawater, potentially influencing the marine ecosystem in the discharge vicinity. Therefore, our study area is on the Qinshan and Jinqimen Nuclear Power Plants in China, employing a blend of Landsat 8/9, and unmanned aerial vehicle (UAV) imagery to gather sea surface temperature (SST) data. In situ measurements validate the temperature data procured through remote sensing. Leveraging these SST observations alongside hydrodynamic and meteorological data from field measurements, we input them into the MIKE 3 model to prognosticate the three-dimensional (3D) spatial distribution and temperature elevation resulting from thermal discharge. The findings reveal that (1) satellite remote sensing can instantly acquire the horizontal distribution of thermal discharge, but with a spatial resolution much lower than that of UAV. The spatial resolution of UAV is higher, but the imaging efficiency of UAV is only 1/40,000 of that of satellite remote sensing. (2) Numerical simulation models can predict the 3D spatial distribution of thermal discharge. Although UAV and satellite remote sensing cannot directly obtain the 3D spatial distribution of thermal discharge, using remotely sensed SST as the temperature field input for the MIKE 3 model can reduce the quantity of measured temperature data and lower the cost of numerical simulation. (3) In the process of monitoring and predicting the thermal discharge of nuclear power plants, achieving an effective balance between monitoring accuracy and cost can be realized by comprehensively considering the advantages and costs of satellite, UAV, and numerical simulation technologies.",10.1007/s10661-024-12890-x,https://doi.org/10.1007/s10661-024-12890-x,,,Nuclear Power Plants,UAV,Environmental Monitoring,numerical simulation,China,remote sensing monitoring,Remote Sensing Technology,thermal discharge monitoring,Unmanned Aerial Devices,thermal discharge prediction,Temperature,,Seawater,,Satellite Imagery,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.8,none,39009747,true,,,
how do drones work at sea?,drone sea measurement,39445093,Behavioural responses of common dolphins to naval sonar.,R Soc Open Sci,,Southall BL,Durban JW,Calambokidis J,Casey C,Fahlbusch JA,Fearnbach H,Flynn KR,Fregosi S,Friedlaender AS,Leander SGM,Visser F,,,,,,,,,,,2024,Oct,,2024 Oct,"Despite strong interest in how noise affects marine mammals, little is known for the most abundant and commonly exposed taxa. Social delphinids occur in groups of hundreds of individuals that travel quickly, change behaviour ephemerally and are not amenable to conventional tagging methods, posing challenges in quantifying noise impacts. We integrated drone-based photogrammetry, strategically placed acoustic recorders and broad-scale visual observations to provide complementary measurements of different aspects of behaviour for short- and long-beaked common dolphins. We measured behavioural responses during controlled exposure experiments (CEEs) of military mid-frequency (3-4 kHz) active sonar (MFAS) using simulated and actual Navy sonar sources. We used latent-state Bayesian models to evaluate response probability and persistence in exposure and post-exposure phases. Changes in subgroup movement and aggregation parameters were commonly detected during different phases of MFAS CEEs but not control CEEs. Responses were more evident in short-beaked common dolphins (n = 14 CEEs), and a direct relationship between response probability and received level was observed. Long-beaked common dolphins (n = 20) showed less consistent responses, although contextual differences may have limited which movement responses could be detected. These are the first experimental behavioural response data for these abundant dolphins to directly inform impact assessments for military sonars.",10.1098/rsos.240650,https://doi.org/10.1098/rsos.240650,PMC11495955,https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11495955/,,Delphinus,,cetaceans,,controlled exposure experiment,,mid-frequency sonar,,noise,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.8,none,39445093,true,,,
how do drones work at sea?,drone sea measurement,40020902,Effects of nocturnal boundary layer subsidence and long-distance transports on PM(2.5) vertical profiles in the Yangtze River Delta of China measured by PM sensor on unmanned aerial vehicle and PM Lidar.,Environ Pollut,,Chen L,Xu H,Huang R,Pang X,Wang B,Wu Z,Yu S,,,,,,,,,,,,,,,2025,Apr,15,2025 Apr 15,"Atmospheric boundary layer structures and long-distance transports significantly affect fine particulate matter (PM2.5) vertical profiles. In this study, the PM2.5 vertical profiles in the Yangtze River Delta (YRD) of China were measured by PM sensor on unmanned aerial vehicle (UAV) and PM Lidar in 2022 (April, June, October) and 2023 (February). The results showed that the PM2.5 vertical profiles appeared obvious stratification on the top of nocturnal boundary layer (NBL). The NBL subsidence stabilized the boundary layer structure and inhibited the vertical diffusion of PM2.5, increasing the ground PM2.5 concentrations. However, when there was an active turbulent motion during the NBL subsidence, the PM2.5 from the surface might be transported upward. The PM2.5 vertical mean concentrations (0-500 m) in the YRD decreased by 58-95% within 3 h, which might be caused by the rapid shift of long-distance transport sources from the North China Plain to the Yellow Sea with higher wind speeds according to backward trajectory. When the ambient PM2.5 concentrations were high (>20 μg m-3) and the weather was clear, the PM Lidar could also observe the diurnal variations of PM2.5 vertical profiles (200-500 m) like the PM sensor on UAV. However, there were differences in the PM2.5 vertical concentrations, and the differences of PM2.5 vertical mean concentrations (200-500 m) measured by the two methods in different seasons were 2.2-13.6 μg m-3. When the PM2.5 concentrations were lower than 17 μg m-3, the measurement performance of PM Lidar was significantly lower than those of the PM sensor on UAV.",10.1016/j.envpol.2025.125935,https://doi.org/10.1016/j.envpol.2025.125935,,,Particulate Matter,Long-distance transports,China,Nocturnal boundary layer,Environmental Monitoring,PM Lidar,Air Pollutants,PM(2.5) vertical profiles,Rivers,Unmanned aerial vehicles,Unmanned Aerial Devices,,Remote Sensing Technology,,Air Pollution,,Particle Size,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.8,none,40020902,true,,,
how do drones work at sea?,drone sea measurement,40120362,Estimating windage coefficient of floating marine green tide of Ulva prolifera using UAV optical images.,Mar Pollut Bull,,Zheng X,Li J,Hou Y,Jiang S,Xing Q,,,,,,,,,,,,,,,,,2025,Jun,,2025 Jun,"Ulva prolifera green tides have emerged every year since 2007 in the Yellow Sea, China. Accurate prediction of trajectories of green tide is very important for early warning and prevention. Surface current and wind are major drivers for drift of green tides. Windage coefficient of α is often used to represent the role of wind in the drift velocity of Ulva masses. However, due to the lack of measured ambient current, the windage coefficient estimate is still highly uncertain. This study presented a novel method which makes it possible for measuring drift velocity and ambient current simultaneously. Using measured drift velocity of Ulva, ambient surface current and wind, the study found that, drift velocity of Ulva is significantly different from ambient current, and the velocity difference between them is well consistent with wind direction. The study established current-depth dependent windage coefficient α (0.41 ± 0.09 % at 2.5 cm depth and 0.74 ± 0.16 % at 10 cm depth). The estimated α in this study is much smaller than previously derived or used, probably because the depth of measured ambient surface current is very close to depth of floating Ulva. The study found that windage coefficient of Ulva is dependent on the depth of the given surface current; windage coefficient increases with increase of surface current depth, implying the necessity to use very-near-surface current to improve model skill of green tides' trajectory simulation. These findings are helpful in understanding the dynamics of drift of green tides and improving accuracy of green tides modeling.",10.1016/j.marpolbul.2025.117834,https://doi.org/10.1016/j.marpolbul.2025.117834,,,Ulva,Ambient surface current,Environmental Monitoring,Drift velocity,China,Green tide of Ulva prolifera,Wind,The Yellow Sea,Remote Sensing Technology,UAV,Unmanned Aerial Devices,Windage coefficient,Water Movements,,Edible Seaweeds,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.8,none,40120362,true,,,
how do drones work at sea?,drone sea measurement,40425720,Sediment accumulation by coastal biogenic structures sustains intertidal flats facing sea level rise in the German Wadden sea.,Sci Rep,,Hoffmann TK,Pfennings K,Hitzegrad J,Paul M,Wehrmann A,Goseberg N,Schlurmann T,,,,,,,,,,,,,,,2025,May,27,2025 May 27,"Biogenic structures such as oyster reefs and mussel beds can enhance sedimentation and promote the expansion of intertidal flats in the German Wadden Sea. This study presents large-scale measurements of sedimentation at biogenic structures that depend on biological activities, the hydrodynamic environment and surface roughness. As the surface roughness of intertidal flats has changed with the bioinvasion of the Pacific oyster and the resulting transformation of mussel beds into oyster reefs, we hypothesised that sedimentation rates vary between these structures. To quantify the extent of sedimentation over time, we surveyed bivalve-covered intertidal flats in 2020 and 2022 and generated digital models of the structures and surrounding terrain. The sediment accumulation rates for the mussel bed and oyster reefs reached 3.9 cm³/(cm²*y), with higher rates observed within the mussel bed than within the oyster reefs. Generally, biogenic structures at lower elevations experienced higher sediment accumulation rates. All accumulation rates exceeded previously reported rates for intertidal flats and the current rate of sea level rise in the Wadden Sea. Our findings suggest that oyster reefs and mussel beds have comparable effects on sediment accumulation, supporting the persistence of intertidal flats and thus helping to stabilise the Wadden Sea.",10.1038/s41598-025-03326-8,https://doi.org/10.1038/s41598-025-03326-8,PMC12117113,https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12117113/,Geologic Sediments,Magallana gigas,Animals,Mytilus edulis,Germany,Biogenic structures,Sea Level Rise,Biogeomorphology,Bivalvia,Drone mapping,Ecosystem,Ecosystem engineer,Oceans and Seas,,Coral Reefs,,Ostreidae,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.8,none,40425720,true,,,
how do drones work at sea?,drone sea measurement,41189606,Field data on sea ice restoration by artificial flooding in subarctic Canada.,Data Brief,,Owen CC,Afzali S,Schellingerhout W,Meijeraan T,Ypma F,,,,,,,,,,,,,,,,,2025,Dec,,2025 Dec,"A field campaign in the Milan Arm of Pistolet Bay in Newfoundland, Canada was conducted to gather data on sea ice restoration by artificial flooding between February and May of 2025. Sea ice thickening was initiated by pumping sea water from below the first-year sea ice onto the surface without significantly modifying the overall snow cover beforehand. Pumping consisted of 84 discrete events, for which GPS location, pumping start time and duration, and local snow and ice thicknesses were recorded. Remote data collection and monitoring were executed by three thermistor chains, three radiation sensors, and one anemometer. All remote measurement systems remained in the field until recovery of the floating systems following ice breakup in late spring. Additionally, coring systems were used to extract 10 ice cores for analysis of temperature and bulk salinity profiles through the ice depth to assess the effect of artificial flooding on sea ice formation and ablation. Two of the ice cores were used and three seawater samples were collected for analysis of the biological content of phytoplankton. Transects of surface composition across select flooded sites were assessed for the formation and solidification of ice and slush layers. Snow thickness and density data were sampled for a representative region of the entire site to assess spatial variability. All these data were complemented by timelapse camera imaging from each monitoring station and aerial drone imaging, including thermal imaging, of the entire region. The dataset can be used to investigate the physical processes involved in sea ice growth before, during, and after flooding. The dataset can be used, in a limited manner, to understand the formation, growth, and ablation of snow ice. The radiation data can be used to analyze the surface radiation fluxes of the parent, flooded, and melting ice. The data gathered during the melting season can be used to investigate the melting of thickened sea ice in comparison to that of natural sea ice. The data on bulk salinity can be used to investigate short-term brine migration. The data on phytoplankton content can be used to assess its change due to the impact of flooding. Combining the various data, thermodynamic ice growth and melt models of sea ice, including snow, slush, and snow ice, can be validated. The understanding of rain and meltwater drainage events could be improved and flow models for simulation of artificial flooding of snow-covered first-year sea ice could be further developed using the data. Aerial imagery obtained by drone provides insights into the flooding behavior of water over snow-covered ice, allowing for the detection and temporal tracking of both visibly impacted and visually concealed areas that may not be apparent to the naked eye.",10.1016/j.dib.2025.112147,https://doi.org/10.1016/j.dib.2025.112147,PMC12581626,https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12581626/,,Ablation,,Albedo,,Desalination processes,,Earth cooling approach,,Insolation,,Melting,,Snow,,Snow ice,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.8,none,41189606,true,,,
how do drones work at sea?,drone sea measurement,41312177,Estimating Total Body Lipid Store of Free-Ranging Whales In Vivo Using Drone Photogrammetry and Biologging Tags.,Ecol Evol,,Burslem A,Isojunno S,Prieto R,Silva MA,Miller PJO,,,,,,,,,,,,,,,,,2025,Dec,,2025 Dec,"Lipid reserve mass is a key indicator of individual fitness and population health in wild animal populations, but no method currently exists to measure it in large aquatic species for which capture is impractical. Here, we develop and employ a new method for quantifying lipid stores in a free-ranging cetacean, the sperm whale (Physeter macrocephalus). This method combines UAV (drone) photogrammetry-based estimates of body volume with tag-derived tissue density to estimate lipid store mass to within an estimated 18% on average. Statistical analysis cross validating volume and density-based condition indicators confirmed the predicted relationships between body volume, tissue density and body composition. On average, for a whale 12 m in length, an increment in volume of 1 m3 was predicted to be accompanied by a 6.3% increase in total body lipid content, while a decrease of 1 kg m-3 in tissue density was predicted to reflect a 5.1% increase in total body lipid content. These results support the effectiveness and encourage continued use of densitometric and morphometric methods for quantifying body condition in cetaceans and highlight the value of simultaneously employing both approaches to directly estimate lipid reserve mass. We anticipate that this method could be extended to other aquatic taxa allowing, for example, major life history events or exposure to stressors to be tied to absolute measures of lipid energy store.",10.1002/ece3.72472,https://doi.org/10.1002/ece3.72472,PMC12657101,https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12657101/,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.8,none,41312177,true,,,
how do drones work at sea?,drone sea measurement,41609332,"Validation of aerial photogrammetry methods to measure body size, condition and mass in small cetaceans.",J Physiol,,Cicciarella R,Willems EP,Markham B,Bizzozzero MR,Phillips W,Allen SJ,Krützen M,Christiansen F,,,,,,,,,,,,,,2026,Mar,,2026 Mar,"Accurate morphometric measurements are essential for estimating body size and condition in animals. These characteristics are, in turn, key to eco-physiological studies, wildlife management and conservation. For free-ranging cetaceans, however, collecting non-invasive morphometric data is challenging. Unoccupied aerial vehicle (UAV) photogrammetry offers a promising solution but requires ground-truthing to assess accuracy and precision. Similarly, morphometric-based indices of body condition must be validated against the animals' true body condition. Here we validated UAV-derived estimates of body size and condition in bottlenose dolphins (Tursiops spp.) under human care by comparing photogrammetry-based measurements of body length, width, height and girth from both stationary and swimming individuals with manual measurements. The two methods showed negligible differences, with UAV-based data yielding lower variability, confirming both high measurement accuracy and precision. Using UAV-derived measurements we calculated a volume-based body condition index (BCI) and compared it with a mass-based BCI, a standard metric in ecological research. The two indices showed a near-perfect fit, demonstrating that volume-based metrics reliably reflect true body condition in small cetaceans. Body density decreased with increasing body condition, consistent with higher fat-to-muscle ratios. By combining UAV-derived body volume with predicted density, based on their body condition, we accurately estimated individual body mass (mean error = 6.4%). This study provides a comprehensive validation of UAV-based photogrammetry to estimate body size, condition and mass in small cetaceans, highlighting its value as a non-invasive and cost-effective tool for ecological and conservation research. KEY POINTS: Measuring body size and condition in free-ranging dolphins is difficult, yet essential to understand their physiology, energy reserves and health. We used unoccupied aerial vehicles (UAV) to obtain accurate, non-invasive body measurements of bottlenose dolphins and compared them with direct manual measurements. UAV-based photogrammetry produced highly precise and accurate estimates of body length, girth and overall body volume, even for freely swimming animals. A UAV-derived, volume-based body condition index matched traditional mass-based indices and enabled accurate estimation of body mass. These results validate UAV photogrammetry as a reliable, ethical and cost-effective method for assessing body size, condition and mass in small cetaceans, thereby advancing ecological and physiological research in the wild.",10.1113/JP290419,https://doi.org/10.1113/JP290419,PMC12953016,https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12953016/,Animals,body condition,Photogrammetry,body mass,Body Size,bottlenose dolphins,Bottle-Nosed Dolphin,drone photogrammetry,Male,non‐invasive morphometrics,Female,validation,Body Weight,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.8,none,41609332,true,,,
how do drones work at sea?,drone sea measurement,41671702,Assessing seagrass ecological health in Zanzibar using an integrated index of drone and in situ indicators.,Mar Pollut Bull,,Hamad IY,Sheikh M,Staehr PAU,,,,,,,,,,,,,,,,,,,2026,May,,2026 May,"Seagrasses respond sensitively to both natural and anthropogenic pressures, making them effective indicators for assessing pressure-driven changes in marine ecosystem health. This study developed and validated a novel multimetric Seagrass Ecological Health Index (SEHI) by integrating drone-derived and in situ ecological metrics to assess nearshore seagrass condition in Unguja, Zanzibar. The index combines multiple parameters, including measures of abundance, taxonomic composition, eutrophication, leaf condition, and seascape fragmentation. Relationships between SEHI and key natural pressures-tidal desiccation (TEI) and wave exposure (REID)-as well as anthropogenic pressures such as hotel density, fishing intensity, seaweed farming, sea urchin density, and water quality, were evaluated. SEHI exhibited significant negative correlations with tidal desiccation (r = -0.70, p < 0.05), while wave exposure showed a negative but non-significant trend (r = -0.49), and sea urchin density (r = -0.70, p < 0.05), and responded strongly to phosphate, chlorophyll-a, and seaweed farming intensity. Among the component indicators, epiphytic cover showed the highest sensitivity to human pressures. Based on SEHI classification, five of the nine study sites were in moderate ecological condition, while two were in poor condition. The results demonstrate the robustness of the SEHI framework as an integrative, drone-based and field assessment tool capable of detecting seagrass ecosystem responses to multiple stressors. SEHI provides a scalable approach for monitoring and managing seagrass health in Zanzibar and other tropical, data-limited regions, improving the assessment and communication of seagrass ecological condition to managers and stakeholders involved in coastal and marine conservation.",10.1016/j.marpolbul.2026.119348,https://doi.org/10.1016/j.marpolbul.2026.119348,,,Environmental Monitoring,Drone remote sensing,Ecosystem,Ecological indicators,Tanzania,Human pressures,Eutrophication,Seagrass ecological health,Alismatales,Zanzibar,Animals,,Sea Urchins,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.8,none,41671702,true,,,
how do drones work at sea?,drone sea measurement,41783355,Effects of Recreational Boats on Harbour Porpoise Swimming Speed and Surfacing Interval Investigated by Two Synchronised UAVs.,Ecol Evol,,Till J,Palmqvist V,Wilk EN,Carlsson P,Stedt J,,,,,,,,,,,,,,,,,2026,Mar,,2026 Mar,"Cetaceans are negatively affected by anthropogenic activities, including acoustic and physical disturbance from boat traffic. Behavioural responses to such disturbances are context-dependent, and site-specific insights are needed for effective local management plans. In this study, the impact of speed and proximity of recreational boats on the swimming speed and surfacing interval of one of the most common coastal cetacean species, the harbour porpoise (Phocoena phocoena), is investigated using data collected by unmanned aerial vehicles (UAVs) within a key habitat for the vulnerable Belt Sea population. In August 2024, two UAVs were flown simultaneously on predefined routes within the area. One UAV searched for and followed detected porpoises, while the other monitored recreational boats. All data was captured as UAV video and used to determine surfacing intervals of individual porpoises, measure speed of porpoises and boats and calculate the closest distance between porpoises and boats for each simultaneous sighting. A total of 91 synchronous flights were conducted, resulting in 28 porpoise observational events. GLM analyses showed that an interaction between mean boat speed and distance to the boat influenced the mean speed of the porpoises. In the presence of boats with high mean speeds, porpoises at close range reduced their swimming speed, while porpoises at greater distances instead increased their swimming speed. Also, porpoise surfacing intervals decreased (i.e., porpoises surfaced more frequently) with decreasing distance to boats. This study demonstrates that recreational boats influence the behaviour of porpoises, which could lead to potential negative individual- and population-level effects.",10.1002/ece3.73165,https://doi.org/10.1002/ece3.73165,PMC12952998,https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12952998/,,Cetacea,,Phocoena phocoena,,anthropogenic impact,,behavioural effect,,drone,,noise,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,0.8,none,41783355,true,,,