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13 results for “satellite telemetry”
OPSSAT-AD - anomaly detection dataset for satellite telemetry
<p>This is the AI-ready benchmark dataset (OPSSAT-AD) containing the telemetry data acquired on board OPS-SAT---a CubeSat mission that has been operated by the European Space Agency.</p> <p>It is accompanied by the paper with baseline results obtained using 30 supervised and unsupervised classic and deep machine learning algorithms for anomaly detection. They were trained and validated using the training-test dataset split introduced in this work, and we present a suggested set of quality metrics that should always be calculated to confront the new algorithms for anomaly detection while exploiting OPSSAT-AD. We believe that this work may become an important step toward building a fair, reproducible, and objective validation procedure that can be used to quantify the capabilities of the emerging anomaly detection techniques in an unbiased and fully transparent way.</p> <p>The included files are:</p> <ul> <li><code>segments.csv</code> with the acquired telemetry signals from ESA OPS-SAT aircraft,</li> <li><code>dataset.csv</code> with the extracted, synthetic features are computed for each manually split and labeled telemetry segment.</li> <li>code files for data processing and example modeliing (<code>dataset_generator.ipynb</code> for data processing, <code>modeling_examples.ipynb</code> with simple examples, <code>requirements.txt</code>- with details on Python configuration, and the <code>LICENSE</code> file)</li> </ul> <p> </p> <p>Please have a look at our two papers commenting on this dataset:</p> <ul> <li>The benchmark paper with results of 30 supervised and unsupervised anomaly detection models for this collection:<br>Ruszczak, B., Kotowski. K., Nalepa, J., Evans, D.:<strong> The OPS-SAT benchmark for detecting anomalies in satellite telemetry, 2024</strong>, <a href="https://arxiv.org/abs/2407.04730" target="_blank" rel="noopener">preprint arxiv: 2407.04730</a>,</li> <li>the conference paper in which we presented some preliminary results for this dataset:<br>Ruszczak, B., Kotowski. K., Andrzejewski, J., et al.: (2023). Machine Learning Detects Anomalies in OPS-SAT Telemetry. Computational Science – ICCS 2023. LNCS, vol 14073. Springer, Cham, <a href="https://doi.org/10.1007/978-3-031-35995-8_21">DOI:10.1007/978-3-031-35995-8_21</a>.</li> </ul>
Comparing distribution of harbour porpoises (Phocoena phocoena) derived from satellite telemetry and passive acoustic monitoring
<p>Data used for publication in Plos One. Two excel files. The satellite_filtered_data is the filtered satellite positions used for MaxEnt modelling in R. The CPOD_data_PPH is the raw C-POD data expressed here as porpoises positive hours (PPH) and can easily be converted to porpoise positive days (PPD).</p>
Satellite telemetry data for Egyptian Geese in southern Africa
<p>This archive contains all currently available satellite GPS telemetry data for Egyptian Geese in southern Africa over the period from 2008 to 2016. The data were collected with two primary aims: (1) to understand the movement ecology of this species; (2) to better evaluate the potential role of Egyptian Geese in spreading avian influenza in southern Africa. Data colelction was undertaken in several phases. The first phase focused on just three sites (Manyame, Barberspan, Strandfontein) and occurred at the same time as a series of extensive bird counts and captures. Birds captured during this period were tested for avian influenza. We also undertook an extensive colour-ringing exercise on Egyptian Geese during the first phase. The second phase of the program involved extending our activities to some new locations (Voelvlei, Jozini) to test specific hypotheses about movement and the timing of moult, and to improve the generality of our findings. The third phase involved a translocation experiment in which six birds were moved from Barberspan to Strandfontein. The data have been analysed and published in a number of different venues and publications, as listed in the associated metadata.</p>
Satellite telemetry data of Double-crested cormorant locations
<p>Avian migrants are challenged by seasonal adverse climatic conditions and energetic costs of long-distance flying. Migratory birds may track or switch seasonal climatic niche between the breeding and non-breeding grounds. Satellite tracking enables avian ecologists to investigate seasonal climatic niche and circannual movement patterns of migratory birds. The Double-crested Cormorant (<em>Nannopterum auritum</em>, hereafter cormorant) wintering in the Gulf of Mexico (GOM) migrate to the Northern Great Plains and Great Lakes and is of economic importance because of its impacts on aquaculture. We tested the climatic niche switching hypothesis that cormorants would switch climatic niche between summer and winter because of substantial differences in climate between the non-breeding grounds in the subtropical region and breeding grounds in northern temperate region. The ordination analysis of climatic niche overlap indicated that cormorants had separate seasonal climatic niche consisting of seasonal mean monthly minimum and maximum temperature, seasonal mean monthly precipitation, and seasonal mean wind speed. Despite non-overlapping summer and winter climatic niches, cormorants appeared to be subjected to similar wind speed between winter and summer habitats and were consistent with similar hourly flying speed between winter and summer. Therefore, substantial differences in temperature and precipitation may lead to the climatic niche switching of fish-eating cormorants, a dietary specialist, between the breeding and non-breeding grounds. </p>
Satellite telemetry data for Egyptian Geese in southern Africa
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Satellite telemetry data of Double-crested cormorant locations
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Data from: Satellite telemetry reveals higher fishing mortality rates than previously estimated, suggesting overfishing of an apex marine predator
Overfishing is a primary cause of population declines for many shark species of conservation concern. However, means of obtaining information on fishery interactions and mortality, necessary for the development of successful conservation strategies, are often fisheries-dependent and of questionable quality for many species of commercially exploited pelagic sharks. We used satellite telemetry as a fisheries-independent tool to document fisheries interactions, and quantify fishing mortality of the highly migratory shortfin mako shark (Isurus oxyrinchus) in the western North Atlantic Ocean. Forty satellite-tagged shortfin mako sharks tracked over 3 years entered the Exclusive Economic Zones of 19 countries and were harvested in fisheries of five countries, with 30% of tagged sharks harvested. Our tagging-derived estimates of instantaneous fishing mortality rates (F = 0.19–0.56) were 10-fold higher than previous estimates from fisheries-dependent data (approx. 0.015–0.024), suggesting data used in stock assessments may considerably underestimate fishing mortality. Additionally, our estimates of F were greater than those associated with maximum sustainable yield, suggesting a state of overfishing. This information has direct application to evaluations of stock status and for effective management of populations, and thus satellite tagging studies have potential to provide more accurate estimates of fishing mortality and survival than traditional fisheries-dependent methodology.
Data from: Assessing the spatial ecology and resource use of a mobile and endangered species in an urbanized landscape using satellite telemetry and DNA faecal metabarcoding
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Data from: Satellite telemetry reveals higher fishing mortality rates than previously estimated, suggesting overfishing of an apex marine predator
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Polar Radiant Energy in the Far InfraRed Experiment (PREFIRE) Satellite 2 telemetry R01
Polar Radiant Energy in the Far InfraRed Experiment (PREFIRE) Satellite 2 Telemetry (PREFIRE_SAT2_0-BUS-TLM) contains positioning and pointing information for one of two PREFIRE polar orbiting CubeSats. Both CubeSats carry a PREFIRE Thermal Infrared Spectrometer (TIRS-PREFIRE), a push broom spectrometer with 63 channels measuring mid- and far-infrared (FIR) radiation from approximately 5 to 53 µm. Most polar emissions are in the FIR but have not been measured on a large scale. PREFIRE aims to fill knowledge gaps in the global energy budget by more accurately characterizing polar emissions. This information will then be assimilated into global circulation and other climate models to predict future climates more accurately.This collection contains the time, beta angle, orbit position and velocity, and the quaternion of PREFIRE Satellite 2 (PREFIRE-SAT2). Combined with a Digital Elevation Map, these telemeters geolocate PREFIRE data on the Earth’s surface. Data retrieval started June 29, 2024 and is ongoing. Geographic coverage is global, with the greatest concentration of data in the polar regions. This data is retrieved at a frequency of 1Hz and is available in CSV format. Positioning and pointing information for the sister satellite, PREFIRE-SAT1, can be found in the PREFIRE_SAT1_0-BUS-TLM collection.
Polar Radiant Energy in the Far InfraRed Experiment (PREFIRE) Satellite 1 telemetry R01
Polar Radiant Energy in the Far InfraRed Experiment (PREFIRE) Satellite 1 Telemetry (PREFIRE_SAT1_0-BUS-TLM) contains positioning and pointing information for one of two PREFIRE polar orbiting CubeSats. Both CubeSats carry a PREFIRE Thermal Infrared Spectrometer (TIRS-PREFIRE), a push broom spectrometer with 63 channels measuring mid- and far-infrared (FIR) radiation from approximately 5 to 53 µm. Most polar emissions are in the FIR but have not been measured on a large scale. PREFIRE aims to fill knowledge gaps in the global energy budget by more accurately characterizing polar emissions. This information will then be assimilated into global circulation and other climate models to predict future climates more accurately. This collection contains the time, beta angle, orbit position and velocity, and the quaternion of PREFIRE Satellite 1 (PREFIRE-SAT1). Combined with a Digital Elevation Map, these telemeters geolocate PREFIRE data on the Earth’s surface.Data retrieval started June 29, 2024 and is ongoing. Geographic coverage is global, with the greatest concentration of data in the polar regions. This data is retrieved at a frequency of 1Hz and is available in CSV format.Positioning and pointing information for the sister satellite, PREFIRE-SAT2, can be found in the PREFIRE_SAT2_0-BUS-TLM collection.
When natal dispersal ends: using satellite telemetry to quantify territory settlement in a long-lived raptor
<p>Breeding territory settlement, as the end point of natal (juvenile) dispersal, is a key juncture in the life history and population dynamics of long-lived raptors. It spatially identifies natal dispersal distance and temporally identifies first recruitment to a breeding population. Its determination can be confused by similar temporary settlement behaviour during dispersal or by post-occupation territorial birds' excursions. Satellite telemetry provides potentially for a method to ascertain location and date of territory settlement without field observer limitations. Prior field-observer estimates are likely biased towards older ages. Telemetry has previously ascertained first territory settlement, but not via a quantified repeatable measure based solely on telemetric records. Our primary goal was to derive analytical rules, via an algorithm based on satellite telemetric data to determine when a dispersing Golden Eagle <i>Aquila chrysaetos </i>had settled on (occupied) a prospective breeding territory, using 83 birds tagged as nestlings in Scotland. Our algorithm derived median record locations during a night, also compared median values over a longer time span, and processed records to confirm the spatial and temporal stability that was expected when a territory was occupied. All 17 birds deemed as algorithmically settled were confirmed by visual plot checks. Field work further validated territory occupation in all 14 of the 17 territories where field observations were possible; confirming egg-laying and chick-rearing in some instances. Many tagged birds were not deemed algorithmically to have settled on a territory, despite comparable or greater age. As a research tool, any current telemetric method is skewed away from older settlement ages due to technological lifespans which will hopefully improve.</p> <p><span>These files provide 16 example datasets as shapefiles: eight for birds deemed to have settled on a territory and eight deemed not to have settled on a territory. Due to required confidentiality on locations of nest sites actual coordinates have been geometrically processed to mask their true locations but the scaling is unaffected.</span></p>
When natal dispersal ends: using satellite telemetry to quantify territory settlement in a long-lived raptor
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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.