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338 results for “gps”
Eight Mile Lake Research Watershed, Carbon in Permafrost Experimental Heating and Drying Research (DryPEHR): GPS Plot Locations
This drying and warming experiment addresses the following questions: 1) Does ecosystem drying, warming and permafrost thaw cause a net release or uptake of C from the ecosystem to the atmosphere?, 2) Does the decomposition of old C that comprises the bulk of the soil C pool influence ecosystem C loss? 3) How do drying and warming affect plant communities and ecosystem properties? We are answering these questions using a combined warming and drying experiment (DryPEHR), which is situated with the Carbon in Permafrost Experimental Heating Research (CiPEHR) project and located in an upland tundra field site near Healy, Alaska in the foothills of the Alaska Range. Warming treatment here refers to growing season air temperature warming (~1C) using open top chambers (OTC) combined with soil 'warming' using snow fences during the snow covered months. Drying is achieved using an automated pumping system that lowers the water table in the dry plots. Soil warming began in 2008; OTCs and drying in 2011. This dataset contains plot locations made using a differential GPS with real time kinematic correction in early August of 2017.
Eight Mile Lake Research Watershed, Thaw Gradient: GPS Plot Locations
In this larger study, we are asking the question: Is old carbon that comprises the bulk of the soil organic matter pool released in response to thawing of permafrost? We are answering this question by using a combination of field and laboratory experiments to measure radiocarbon isotope ratios in soil organic matter, soil respiration, and dissolved organic carbon, in tundra ecosystems. The objective of these proposed measurements is to develop a mechanistic understanding of the SOM sources contributing to C losses following permafrost thawing. We are making these measurements at an established tundra field site near Healy, Alaska in the foothills of the Alaska Range. Field measurements center on a natural experiment where permafrost has been observed to warm and thaw over the past several decades. This area represents a gradient of sites each with a different degree of change due to permafrost thawing. As such, this area is unique for addressing questions at the time and spatial scales relevant for change in arctic ecosystems. This dataset contains plot locations made using a differential GPS with real time kinematic correction in early August of 2017.
Topographic GPS profiles of Hog and Metompkin Island Cross-shore Transects of the Virginia Coast Reserve 2010
For complete information regarding sampling and analytical methods, and for contextualization of the data and variables, please see C. Wolner's 2011 thesis, available on the VCR LTER website.
Test data for Sonic Kayaks particulate matter sensor, temperature and GPS
<p>These data sets are the first trials for adding a particulate matter sensor to the Sonic Kayak project https://fo.am/activities/kayaks/</p> <p>There are three data files - gps.csv is the GPS co-ordinates, pm.csv is the particulate matter data (using a PMS7003), and temp.csv is the temperature data (two separate but identical digital thermometer sensors). Time is included in all datasets and can be used to align them. Together the data can be used to make a fine scale heat line map of particulate matter and temperature.</p>
Very high rate GPS observables at San Pedro Martir, Mexico (SPIG) continously operating station: dataset for the case study. Part 4.
<p>Archived data is on a Trimble raw T02 format from a Trimble NetR9 receiver. Complete metadata for the station can be obtained at the TLALOCNet archive at <strong>http://tlalocnet.udg.mx</strong>.</p> <p>This dataset is a high rate (50hz) version of the SPIG continous GPS station observables that is otherwise available as a 15 sec recording on the TLALOCNet archive (<strong>http://tlalocnet.udg.mx</strong>).</p> <p>Any use of this dataset or parts of it must give the proper acknowledgement, including the Zenodo assigned DOI (10.5281/zenodo.4002090) as follows:</p> <p>This material is partly based on GPS data provided by the SSN-Trans-boundary, Land and Atmosphere Long-term Observational and Collaborative Network (TLALOCNet; Cabral-Cano et al., 2018 and Pérez-Campos et al., 2018) jointly operated by Servicio de Geodesia Satelital (SGS) and Servicio Sismológico Nacional (SSN) at the Instituto de Geofísica-Universidad Nacional Autónoma de México in collaboration with UNAVCO, Inc. We gratefully acknowledge all the personnel from SGS, SSN and UNAVCO for station installation, maintenance, data acquisition, permanent IT support and data distribution. TLALOCNet and related GPS operations at SGS are supported by the Consejo Nacional de Ciencia y Tecnología (CONACyT) projects 253760 and 2017-01-5955, by the National Science Foundation grant EAR-1338091 and supplemental support from UNAM-Instituto de Geofísica.<br> <br> <strong>References</strong>.</p> <p>E. Cabral-Cano, X. Pérez-Campos, B. Márquez-Azúa, M. A. Sergeevaa, L. Salazar-Tlaczani, C. DeMets, D. Adams, J. Galetzka, K. Feaux, Y. L. Serra, G. S. Mattioli, and M. Miller, 2018. TLALOCNet: A Continuous GPS-Met Backbone in Mexico for Seismotectonic, and Atmospheric Research. Seismological Research Letters, v. 89, n. 2ª, p. 373-381. https://doi.org/10.1785/0220170190.</p> <p>X. Pérez‐Campos, V.H. Espíndola, J. Pérez, J. A. Estrada C. Cárdenas Monroy, D. Bello, Adriana González‐López, Daniel González Ávila, Moisés Gerardo Contreras Ruiz Esparza, Rafael Maldonado, Yi Tan, Iván Rodríguez Rasilla, Miguel Ángel Vela Rosas, José Luis Cruz, Arturo Cárdenas, Fernando Navarro Estrada, Alejandro Hurtado, Antonio de Jesús Mendoza Carvajal, Edgar Montoya‐Quintanar, Miguel A. Pérez‐Velázquez, 2018. The Mexican National Seismological Service: An Overview. Seismological Research Letters, v. 89, n. 2ª, p.318-323. https://doi.org/10.1785/0220170186.</p>
Very high rate GPS observables at Coeneo, Mexico (UCOE) continously operating station: dataset for the case study. Part 3.
<p>Archived data is on a Trimble raw T02 format from a Trimble NetR9 receiver. Complete metadata for the station can be obtained at the TLALOCNet archive at <strong>http://tlalocnet.udg.mx</strong>.</p> <p>This dataset is a high rate (50hz) version of the UCOE continous GPS station observables that is otherwise available as a 15 sec recording on the TLALOCNet archive (<strong>http://tlalocnet.udg.mx</strong>).</p> <p>Any use of this dataset or parts of it must give the proper acknowledgement, including the Zenodo assigned DOI (10.5281/zenodo.4002072) as follows:</p> <p>This material is partly based on GPS data provided by the Trans-boundary, Land and Atmosphere Long-term Observational and Collaborative Network (TLALOCNet; Cabral-Cano et al., 2018) jointly operated by Servicio de Geodesia Satelital (SGS) at the Instituto de Geofísica-Universidad Nacional Autónoma de México in collaboration with UNAVCO, Inc. We gratefully acknowledge Armando Carrillo-Vargas and all the personnel from SGS and UNAVCO at for station installation, maintenance, data acquisition, permanent IT support and data distribution. TLALOCNet and related GPS operations at SGS are supported by the Consejo Nacional de Ciencia y Tecnología (CONACyT) projects 253760 and 2017-01-5955, by the National Science Foundation grant EAR-1338091 and supplemental support from UNAM-Instituto de Geofísica.<br> <br> <strong>References</strong>.</p> <p>E. Cabral-Cano, X. Pérez-Campos, B. Márquez-Azúa, M. A. Sergeevaa, L. Salazar-Tlaczani, C. DeMets, D. Adams, J. Galetzka, K. Feaux, Y. L. Serra, G. S. Mattioli, and M. Miller, 2018. TLALOCNet: A Continuous GPS-Met Backbone in Mexico for Seismotectonic, and Atmospheric Research. Seismological Research Letters, v. 89, n. 2ª, p. 373-381. https://doi.org/10.1785/0220170190.</p>
GPS velocity field in the Pamir region in the Eurasian-fixed frame complied from our own results and previous studies
<p>The data file includes the GPS velocities with respect to the Eurasian frame in the Pamir, Tien Shan region.</p>
Analysis of migration patterns of western marsh harriers using GPS tracking data
<p>This repository contains analysis code for Vansteelant et al. (2020, <a href="https://doi.org/10.1007/s10336-020-01785-6">https://doi.org/10.1007/s10336-020-01785-6</a>). See the <code>README.md</code> for more information.</p>
Proximity-sensors on GPS collars reveal fine-scale predator-prey behavior during a predation event: A case study from Scandinavia
<p>Although the advent of high-resolution GPS tracking technology has helped increase our understanding of individual and multi-species behavior in wildlife systems, detecting and recording direct interactions between free-ranging animals remains difficult. In 2023, we deployed GPS collars equipped with proximity sensors (GPS proximity collars) on brown bears (<em>Ursus</em> <em>arctos</em>) and moose (<em>Alces</em> <em>alces</em>) as part of a multi-species interaction study in central Sweden. On 6 June, 2023, a collar on an adult female moose and a collar on an adult male bear triggered on each other's UHF signal and started collecting fine-scale GPS positioning data. The moose collar collected positions every 2 minutes for 89 minutes and the bear collar collected positions every 1 minute for 41 minutes. On 8 June, field personnel visited the site and found a female neonate moose carcass with clear indications of bear bite marks on the head and neck. During the predation event, the bear remained at the carcass while the moose moved back and forth, moving towards the carcass site about 5 times. The moose was observed via drone with 2 calves on 24 May and with only one remaining calf on 9 June. This case study describes, to the best of our knowledge, the first instance of a predation event between two free-ranging, wild species recorded by GPS proximity collars. Both collars successfully triggered and switched to finer-scaled GPS fix rates when the individuals were in close proximity producing detailed movement data for both predator and prey during and after a predation event. We suggest that, combined with standard field methodology, GPS proximity collars placed on free-ranging animals offer the ability for researchers to observe direct interactions between multiple individuals and species in the wild without the need for direct visual observation.</p>
GPS RINEX data and position solutions (BUK1 and ARO2)
<p>*.zip => RINEX data</p><p>*.txt => position solutions in IGS20 reference frame</p><p>anal.m => analysis and plotting script in Matlab</p>
Supporting data for assessing impacts of satellite GPS transmitters on survival, nesting propensity, and nest success of greater sage-grouse
<p>Telemetry technology and data are commonly used to study behavior and demography of wildlife. Satellite-based, global positioning system (GPS) telemetry allows researchers to remotely collect a high volume of fine-resolution animal location data but may also come with hidden costs. For example, recent studies suggested GPS transmitters attached via backpacks may reduce survival of greater sage-grouse (<em>Centrocercus urophasianus</em>) relative to very high frequency (VHF) telemetry transmitters attached via collars. While some evidence suggests GPS backpacks can reduce survival, no studies examined their effects on sage-grouse breeding behavior and success. We compared survival, breeding behavior, and nest success for sage-grouse hens marked with either VHF collars or GPS backpack transmitters in central Idaho, USA. GPS backpacks reduced spring-summer survival relative to VHF collars, yet GPS backpacks did not consistently affect nest success or the likelihood or timing of nest initiation relative to VHF collars. Daily nest survival varied annually and with timing of nest initiation and nest age, but marginal effects of transmitter type were statistically insignificant, and interactions between transmitter type and study year were inconsistent. These results demonstrate the effect of GPS backpacks on sage-grouse survival but also suggest GPS backpacks do not appear to affect components of fecundity. </p>
Monitoring mobility in older adults using a global positioning system (GPS) smartwatch and accelerometer: A validation study
<p><strong>Background</strong></p> <p>There is interest in identifying the most reliable method for detecting early mobility limitations. Accelerometry and Global Positioning System (GPS) could provide insight into declines in mobility, but few studies have used this multi-sensor approach to monitor mobility in older adults. </p> <p><strong>Methods</strong></p> <p>Thirty-two volunteers (66.2±6.3 years) agreed to participate in our validation study. We conducted two experiments to determine the validity of the TicWatch S2 and Pro 3 Ultra GPS models against the Qstarz receiver in measuring life-space mobility, trip frequency, duration, and mode. We also assessed the accuracy of the TicWatch in measuring step count and agreement with the ActiGraph wGT3X-BT for activity counts and sedentary behavior. Participants wore devices simultaneously for three consecutive days and recorded activity and trip information.</p> <p><strong><span>Results</span></strong></p> <p>The TicWatch Pro 3 Ultra GPS performed better than the S2 model and was similar to the Qstarz in all tested trip-related measures, and it was able to estimate both passive and active trip modes. Both models showed similar results to the Qstarz in life-space-related measures. The TicWatch S2 demonstrated good to excellent overall agreement with the ActiGraph algorithms for the time spent in sedentary and non-sedentary activities, with 84% and 87% agreement rates, respectively. Under supervised conditions, the TicWatch Pro 3 Ultra GPS measured step count consistently with the gold standard observer, with a bias of 0.4 steps. The thigh-worn ActiGraph algorithm accurately classified sitting and lying postures (97%) and standing postures (90%).</p> <p><strong>Conclusion</strong></p> <p>Our multi-sensor approach to monitoring mobility has the potential to capture both accelerometer-derived movement data and trip/life-space data only available through GPS. In this study, we found that the TicWatch models are valid devices for capturing GPS and raw accelerometer data, making them useful tools for assessing real-world mobility in older adults and advancing our knowledge of early mobility decline.</p>
Raw GPS data of wild and farmed mallards in southern Sweden
<p>Releasing farmed mallards into the wild is a common practice in wildlife management worldwide, involving millions of birds annually, and is mainly carried out to increase hunting opportunities. Ringing and previous research show that released mallards have low survival also outside the hunting season, and that survivors may compromise migration habits, morphology, and adaptations of the wild population. Detailed local movements of released mallards have not been studied before, despite the importance of spatiotemporal patterns for understanding the impact of releases and their utility for hunting. We studied local movements in August-October of 11 wild and 44 released mallards caught in the same wetland in southern Sweden and provided with GPS tags. Wild mallards moved longer distances than farmed, over the whole diel cycle as well as during three out of four separate periods of the day (dawn, day, and dusk). Mallards of both origins moved the longest distances during dusk and dawn, and the shortest during night. Males and females did not differ significantly in distance moved, regardless of origin (wild <em>versus</em> farmed). Our study demonstrates large differences in spatiotemporal movement patterns between wild and farmed mallards. The typical day of wild mallards included movements between wetlands in the landscape, likely to foraging sites known from previous experience. However, wild mallards frequently returned to the study wetland, probably attracted by supplementary bait. On the other hand, farmed mallards seldom left the study wetland, despite the possibility of accompanying wild birds to other sites. The sedentary behavior of farmed mallards and the fact that wild birds come to join them are both beneficial for hunting purposes. Limited movements of farmed mallards together with their low survival could also be positive as they limit hybridization between wild and farmed mallards, as well as dispersal of nutrients.</p>
The upper crustal deformation field of Greece inferred from GPS data and its correlation with earthquake occurrence
<p>These are Tables S1 and S2 which accompany the Article "The upper crustal deformation field of Greece inferred from GPS data and its correlation with earthquake occurrence" by Konstantinos Chousianitis, Sotirios Sboras, Vasiliki Mouslopoulou, Gerasimos Chouliaras, and Dionissios T. Hristopulos.</p>
GPS trajectories of tourists on Torsö and Brommö 2021 from INCULTUM Sweden Pilot
<div>This dataset is part of ongoing work about tourist behaviour changes on Torsö and Brommö. It was collected using GPS trackers. </div> <div> <div> <p> </p> </div> </div>
GPS tracking data for: Male mating season range expansion results from an increase in scale of daily movements for a polygynous-promiscuous bird
<p>Males of species with promiscuous mating systems are commonly observed to use larger ranges during the mating season relative to non-mating seasons, which is often attributed to a change in movements related to reproductive activities. However, few studies link seasonal range sizes to variations in daily space use patterns to provide insight into the behavioral mechanisms underlying mating season range expansion. We studied 20 GPS-tagged male wild turkeys (<em>Meleagris gallopavo</em>), a large upland gamebird, during the mating and summer non-mating seasons to test the hypothesis that larger mating season ranges resulted from male wild turkeys expanding the scale of daily movement activities to locate and court females. We delineated mating and non-mating seasons based on the intensity of gobbling, a vocalization tied to courtship behavior, recorded by autonomous recording units distributed across the study area. Mating season ranges were significantly larger than non-mating season ranges. Daily ranges were larger in the mating season, as were distances between roost sites used on consecutive nights. Variance in daily range size was greater in the mating season, but low temporal autocorrelation suggested considerable daily variability in both seasons. We found no evidence that male wild turkeys changed how they distributed daily movements within seasonal ranges, or differences in habitat use, suggesting larger mating season ranges result from male wild turkeys increasing the scale of their daily movements, rather than a systematic shift to a nomadic movement strategy. Likely, the distribution of females is more dynamic and ephemeral compared to other resources, prompting males to traverse larger daily ranges during the mating season to locate and court females. Our work illustrates the utility of using daily movement to understand the behavioral process underlying larger space use patterns.</p>
Post-50 Ma evolution of India-Asia collision zone from paleomagnetic and GPS data: Greater India indentation to eastward Tibet flow
<p>Review of paleomagnetic data from Tibet and N Indochina, supporting the paper "Post-50 Ma evolution of India-Asia collision zone from paleomagnetic and GPS data: Greater India indentation to eastward Tibet flow".</p>
GPS Time Series Kamchatka 2013
<p>GPS time series presented in the article: "Transient slab plunge prior to the Mw 8.3 2013 Okhotsk deep-focus earthquake"</p> <p>The columns of the files correspond to </p> <p>Year ; Month ; Day ; Hour ; Minute ; Second ; East position (mm) ; North position (mm) ; Up position (mm) ; East uncertainty (mm) ; North uncertainty (mm) ; Up uncertainty (mm) ;</p>
Ocean surface wind estimation from waves based on small GPS buoy observations in a bay and the open ocean
<p>This is dataset of ocean surface wave and wind used in the paper "Ocean surface wind estimation from waves based on small GPS buoy observations in a bay and the open ocean" by Shimura et al. (2022, JGR-Oceans, <a href="https://doi.org/10.1029/2022JC018786">https://doi.org/10.1029/2022JC018786</a> ).</p> <p>"data_bayObservation.nc" contains the observed wind, estimated wind, and observed wave spectral data during the bay observations.</p> <p>"data_openOceanObservation.nc" contains the reanalysis wind, estimated wind, and observed wave spectral data during the open ocean observations.</p> <p> </p>
Realistic GPS and IMU data
<p>Recordings of both gps and imu during a Seafar vessel navigation.</p> <p>The following values come from the gnss unit:</p> <pre><code> "heading_degrees": 154.453, "rot_degrees_min": 19.9, "lat_degrees": 51.212967072, "lon_degrees": 2.995510899, "sog_kph": 3.37,</code></pre> <p>All the other values come from the IMU eg. </p> <pre><code class="language-json"> "roll_degrees": 2.78, "pitch_degrees": 0.57, "yaw_degrees": 158.5, "roll_rate_rad_min": 0.0, "pitch_rate_rad_min": 0.0, "yaw_rate_rad_min": 0.51, "accel_x_ms2": -0.00137, "accel_y_ms2": 0.00784, "accel_z_ms2": -0.00171, "yaw_rate_degrees_min": 29.2208475517</code></pre> <p>All acceleration values are gravity-compensated.</p>
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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.