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533 results for “Aerial”
Craters in Historical Aerial Images (CHAI) Dataset
<p>This dataset contains 99 aerial images from Austria and Germany from 1943 - 1945. There are three versions of the dataset: <strong>CHAI-raw</strong>, <strong>CHAI-full</strong>, and <strong>CHAI-light</strong>. The CHAI-raw contains the original 99 historical aerial images with a Region of Interest (ROI) mask as well as the crater annotations. CHAI-full and CHAI-light are the derived datasets that were used for the evaluation of the paper <strong>"CHAI: Craters in Historical Aerial Images"</strong> presented at <a href="https://wacv2024.thecvf.com/">WACV2024</a>. For both datasets we extracted 960×960 patches with an overlap of 20%, both come with the images in .png format and the train, val, and test as .json files in the COCO style. The difference between the CHAI-full and CHAI-light datasets is that for the light version, all patches without any annotations have been removed, which results in the same amount of annotations, but fewer patches.</p><h2>Technical Details</h2><p>CHAI-raw contains all images unnormalized, additionally, the -info.csv contains the GSD in m, the -mask.png contains the region of interest (only in which craters were annotated), as well as the craters.csv and craters-manual-adapted.csv, which contain the craters and the manually refined craters, details can be found in the original publication. For ease of use, please consider using the derived datasets, which were used for the evaluation of our paper:<br><br>Will be linked once published.</p><p>Please cite the WACV paper when publishing results on these datasets.</p><h2>Access</h2><p>If you would like to request access to these files, please fill out the form below.</p><p>You need to satisfy these conditions in order for this request to be accepted:</p><p>The dataset is freely available for non-commercial research use. In order to get access to the dataset you have to fill in and sign the <a href="https://cvl.tuwien.ac.at/wp-content/uploads/2023/12/Form-Agreement-for-Usage-of-CHAI-Dataset.pdf">usage agreement form</a> and send it to <a href="https://cvl.tuwien.ac.at/staff/marvin-burges/">Marvin Burges</a><a href="mailto:sebastian.zambanini@tuwien.ac.at">.</a></p>
Figure 1 from: Marinov T, Kokanova-Nedialkova Z, Nedialkov P (2024) UHPLC-HRMS-based profiling and simultaneous quantification of the hydrophilic phenolic compounds from the aerial parts of Hypericum aucheri Jaub. & Spach (Hypericaceae). Pharmacia 71: 1-11. https://doi.org/10.3897/pharmacia.71.e122436
Figure 1 Chromatographic separation of the standards chlorogenic acid, mangiferin, and hyperoside under the optimized conditions.
Data set for combined influence of food availability and agricultural intensification on a declining aerial insectivore
<p>Aerial insectivores show worldwide population declines coinciding with shifts in agricultural practices. Increasing reliance on certain agricultural practices is thought to have led to an overall reduction in insect abundance that negatively affects aerial insectivore fitness. The relationship between prey availability and the fitness of insectivores may thus vary with the extent of agricultural intensity. It is therefore imperative to quantify the strength and direction of these associations. Here we used data from an 11-year study monitoring the breeding of Tree Swallows (<em>Tachycineta bicolor</em>) and the availability of Diptera (their main prey) across a gradient of agricultural intensification in southern Québec, Canada. This gradient was characterized by a shift in agricultural production, whereby landscapes composed of forage and pastures represented less agro-intensive landscapes and those focusing on large-scale arable row crop monocultures, such as corn (<em>Zea mays</em>) or soybean (<em>Glycine max</em>) that are innately associated with significant mechanization and agro-chemical inputs, represented more agro-intensive landscapes. We evaluated the landscape characteristics affecting prey availability, and how this relationship influences the fledging success, duration of the nestling period, fledgling body mass, and wing length as these variables are known to influence the population dynamics of this species. Diptera availability was greatest within predominately forested landscapes, while within landscapes dominated by agriculture, it was marginally greater in less agro-intensive areas. Of the measured fitness and body condition proxies, both fledging success and nestling body mass were positively related to prey availability. The impact of prey availability varied across the agricultural gradient as fledging success improved with increasing prey levels within forage landscapes yet declined in more agro-intensive landscapes. Finally, after accounting for prey availability, fledging success was lowest, nestling periods were the longest, and wing length of fledglings were shortest within more agro-intensive landscapes. Our results highlight the interacting roles that aerial insect availability and agricultural intensification have on the fitness of aerial insectivores, and by extension how food availability may interact with other aspects of breeding habitats to influence the population dynamics of predators.</p>
Data sets for Interacting effects of cold snaps, rain, and agriculture on the fledging success of a declining aerial insectivore
<p>Climate change predicts the increased frequency, duration, and intensity of inclement weather periods, such as unseasonably low temperatures (i.e., cold snaps) and prolonged precipitation. Many migratory species have advanced the phenology of important life history stages, and as a result will likely be exposed to these periods of inclement spring weather more often, thus risking reduced fitness and population growth. For declining avian species, including aerial insectivores, anthropogenic landscape changes such as agricultural intensification are another driver of population declines. These landscape changes may affect the foraging ability of food provisioning parents, and reduce the survival of nestlings exposed to inclement weather, through for example pesticide exposure impairing thermoregulation and punctual anorexia. Breeding in agro-intensive landscapes may thus exacerbate the negative effects of inclement weather under climate change. We observed that a significant reduction in the availability of insect prey occurred when daily maximum temperatures fell below 18.3°C, and thereby defined any day where the maximum temperature fell below this value as a day witnessing a cold snap. We then combined daily information on the occurrence of cold snaps and measures of precipitation to assess their impact on the fledging success of Tree Swallows (<em>Tachycineta bicolor</em>) occupying a nest box system placed across a gradient of agricultural intensification. Estimated fledging success of this declining aerial insectivore was 36.2% lower for broods experiencing four cold snap days during the 12 days post hatching period versus broods experiencing none, and this relationship was worsened when facing more precipitation. We further found that the overall negative effects of a brood experiencing periods of inclement weather was exacerbated in more agro-intensive landscapes. Our results indicate that two of the primary hypothesized drivers of many avian population declines may interact to further increase the rate of declines in certain landscape contexts.</p>
Terrestrial and aerial photos, GCPs and derived point clouds of a sinkhole in Northern Thuringia
<p>Aiming at comparing the results of using either terrestrial or aerial photos for structure from motion photogrammetry of a sinkhole in Northern Thuringia we took these photos in 2017, 2018 and 2019 and surveyed ground control points. Therefore, the data allows both, the comparison of the results of using terrestrial or aerial photos for the 3D reconstruction, and the mulit-year monitoring of geomorphic changes within the sinkhole.</p>
Data for: Negative effects of agricultural intensification on the food provisioning rate of a declining aerial insectivore
<p>The historical rise of intensive agricultural practices is hypothesized to be related to declines of grassland and aerial insectivorous birds. Drivers of declines may also influence the overall abundance and spatial distribution of insects within agricultural landscapes. Subsequently, the food provisioning rate of birds breeding within more agro-intensive landscapes may be impacted. Lower provisioning rates in agro-intensive landscapes may lead to reduced growth rate, body condition or fledging success of nestlings but also to diminished body condition of food provisioning adults. Results from a previous study supported this hypothesis as the fledging success and proxies of nestling body condition were lowest for an aerial insectivore breeding in more agro intensive landscapes. Of the multiple hypotheses put forward to explain these correlations, one mechanism may act through variation in food provisioning rates. In this study, we expounded on this hypothesis using data derived from the aforementioned study system and assessed if provisioning rates to nestlings and food provisioning behavior of adults varied across a gradient of agricultural intensification in a declining aerial insectivore, the Tree Swallow (<em>Tachycineta bicolor)</em>. We found that the hourly provisioning rate was lower in agro-intensive landscapes, and yet travel distances were longest within less agro-intensive landscapes. Our results highlight that, in order to maximize long term average gain rates, Tree Swallows breeding within agro-intensive landscapes must forage with greater intensity, perhaps at a cost to themselves, or else costs will transfer to growing broods. Our work provides further evidence that agricultural intensification on the breeding grounds can contribute to the declines of aerial insectivores in part through a trophic pathway.</p>
Aerial metabolic rates of the Asian shore crab Hemigrapsus sanguineus
<p>Rapid warming in the Gulf of Maine may influence the success or invasiveness of the Asian shore crab, <em>Hemigrapsus sanguineus</em>. To better predict the effects of climate change on this invasive species, it is necessary to measure its energy dynamics under a range of conditions. However, previous research has only focused on the metabolism of this intertidal species in water. We sampled adult crabs from three different sites and measured their metabolic rates in air. We show that metabolic rate increases with body mass and the number of missing limbs, but decreases with the number of regenerating limbs, possibly reflecting the timing of energy allocation to limb regeneration. Importantly, metabolic rates measured here in air are ~4× higher than metabolic rates previously measured for this species in water. Our results provide baseline measurements of aerial metabolic rates across body sizes, which may be affected by climate change. With a better understanding of respiration in <em>H. sanguineus</em>, we can make more informed predictions about the combined effects of climate change and invasive species on the northeast coasts of North America.</p>
Autonomous Self-burying Seed Carriers for Aerial Seeding
<p>The datasets </p>
A Two-time-level Model for Mission and Flight Planning of an Inhomogeneous Fleet of Unmanned Aerial Vehicles
<p>We consider the mission and flight planning problem for an inhomogeneous fleet of unmanned aerial vehicles (UAVs). Therein, the mission planning problem of assigning targets to a fleet of UAVs and the flight planning problem of finding optimal flight trajectories between a given set of waypoints are combined into one model and solved simultaneously. Thus, trajectories of an inhomogeneous fleet of UAVs have to be specified such that the sum of waypoint-related scores is maximized, considering technical and environmental constraints. Several aspects of an existing basic model are expanded to achieve a more detailed solution. A two-level time grid approach is presented to smooth the computed trajectories. The three-dimensional mission area can contain convex-shaped restricted airspaces and convex subareas where wind affects the flight trajectories. Furthermore, the flight dynamics are related to the mass change, due to fuel consumption, and the operating range of every UAV is altitude-dependent. A class of benchmark instances for collision avoidance is adapted and expanded to fit our model and we prove an upper bound on its objective value. Finally, the presented features and results are tested and discussed on several test instances using GUROBI as a state-of-the-art numerical solver.</p>
Autonomous Aerial Inspection using Visual-Inertial Robust Localization and Mapping
<p>This video illustrates the content of the paper referenced below.<br> <br> <strong>Reference:</strong><br> Lucas Teixeira, Ignacio Alzugaray and Margarita Chli, "Autonomous Aerial Inspection using Visual-Inertial Robust Localization and Mapping", in Proceedings of the International Conference on Field and Service Robotics (FSR), 2017.</p> <p><strong>Abstract:</strong></p> <p>With recent technological breakthroughs bringing fully autonomous inspection using small Unmanned Aerial Vehicles (UAVs) closer to reality, the community of Robotics has actively been developing the real-time perception capabilities able to run onboard such constraint platforms. Despite good progress, realistic deployment of autonomous UAVs in GPS-denied environments is still rudimentary. In this work, we propose a novel system to generate a collision-free path towards a user-specified inspection direction for a small UAV using monocular-inertial sensing only and performing all computation onboard. Estimating both the previously unknown scene and the UAV’s trajectory on the fly, this system is evaluated on real experiments outdoors in the presence of wind and poorly structured environments. Our analysis reveals the shortcomings of using sparse feature maps for planning, highlighting the importance of robust dense scene estimation proposed here.</p>
A Geometric Pulling Force Controller for Aerial Robotic Workers
<p> This video presents a geometric, pulling force control scheme in order to enable the concept of Aerial Robotic Workers (ARWs), where the capabilities of the Unmanned Aerial Vehicles (UAVs) are enhanced by aerial manipulators in order to exert known pulling forces on the environment, with characteristic applications such as levers actuation, debris removal and safety assessments. The proposed novel approach consists of interfacing a cascaded position control scheme with a manipulation framework in such a way that the UAV, together with the manipulator are being controlled in a complete system.</p>
Aerial View Swiss International Flight LX35 Approaching Zurich International Airport
<p>December 3, 2016</p> <p>Return from MRS Fall Meeting 2016 in Boston</p>
Enhancing Regional Quasi-Geoid Refinement Precision: An Analytical Approach Employing ADS80 Tri-linear Array Stereoscopic Imagery for Aerial Triangulation Densification and GNSS Gravity-Potential Leveling
Open the record for dataset details and reuse information.
Figure 4 in Quantitative assessment of species identification in aerial transect surveys for ice-associated seals
Figure 4. Observed species, age class, and confidence level probabilities for four species of ice-associated seals in the Bering Sea. True species and age classes include spotted seal pup (SDP), spotted seal nonpup (SDN), ribbon seal pup (RNP), ribbon seal nonpup (RNN), bearded seal pup (BDP), bearded seal nonpup (BDN), ringed seal pup (RDP), and ringed seal nonpup (RDN). Observed species classifications include spotted seal (red), ribbon seal (green), bearded seal (yellow), ringed seal (blue), and unknown seal (white). Observed age classes include pup, nonpup, and unknown. For observed species classifications, darker shades indicate greater confidence (e.g., light red = spotted seal guess, red = spotted seal likely, and dark red = spotted seal positive). For observed age classes, the relative density of hash lines indicate greater confidence (e.g., low density = guess, medium density = likely, high density = positive). Solid colors with no hashing indicate unknown age classification. Top panel (a) includes results from an analysis with no observer effects on model parameters. Bottom four panels (b) correspond to four different observers from an analysis including observer effects.
Figure 5 in Quantitative assessment of species identification in aerial transect surveys for ice-associated seals
Figure 5. Frequencies of observed characteristics from images identified as pups (a) and nonpups (b) of four ice-associated seal species in the Bering Sea. Bars are stacked according to the frequencies of nine observed species and age class confidence categories. For pups, only those traits with at least one observation are included for each species. For nonpups, only traits with ≥ 5 observations are included. Trait definitions are provided in Table 1.
Glacial sediment-rich meltwater plume investigation using a high-resolution multispectral sensor embedded in an Unmanned Aerial Vehicle
<p>Methodology video</p>
Dataset used in "Unmanned Aerial System (UAS) observations of water surface elevation in a small stream: comparison of radar altimetry, LIDAR and photogrammetry techniques"
<p>Dataset for research paper "Unmanned Aerial System (UAS) observations of water surface elevation in a small stream: comparison of radar altimetry, LIDAR and photogrammetry techniques", published in Remote Sensing of Environment 2019, Elsevier Journal.</p> <p>Dataset includes:</p> <p>-MATLAB_codes.rar: zip file that contains MATLAB codes. MAIN.m is the main code, it refers to external functions that are included in the zip file. MAIN.m plots the figures of the paper in which we compare radar, LIDAR and photogrammetry and computes statistics of table 3 (table of the paper)</p> <p>-zip file WL_observations_Aomose.zip contains LIDAR, radar, and photogrammetry observations to be loaded by MATLAB code MAIN.m</p> <p>-the LIDAR Digital Surface Model (DSM_final.tif) retrieved in the stream Amose Å</p> <p>-the photogrammetry Digital Elevation Model (DEM_nov.tif) and orthomosaic (orthomosaic_nov.tif) </p> <p> </p>
Figure 3 in Aquatic insects in the forest canopy: a new genus of moth flies (Diptera: Psychodidae) developing in slime on aerial roots
Figure 3. Habitus of Mucomyia emersa male, head and abdomen removed.
Figure 2 in Aquatic insects in the forest canopy: a new genus of moth flies (Diptera: Psychodidae) developing in slime on aerial roots
Figure 2. Habitus of Mucomyia emersa larvae in plant mucilage.
Figure 2 from: Kokanova-Nedialkova Z, Nedialkov P (2021) Validated UHPLC-HRMS method for simultaneous quantification of flavonoid contents in the aerial parts of Chenopodium bonus-henricus L. (wild spinach). Pharmacia 68(3): 597-601. https://doi.org/10.3897/pharmacia.68.e69781
Figure 2 Flavonoids in the MeOH extract from the aerial parts of C. bonus-henricus L. and detected glycosides of patuletin (A), spinacetin (B), 6-methoxykaempferol, and isorhamnetin (C).
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.