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403 results for “satellite data”
Data from: Forecasting landslides using community detection on geophysical satellite data
<p>As a result of extreme weather conditions, such as heavy precipitation, natural hillslopes can fail dramatically; these slope failures can occur on a dry day due to time lags between rainfall and pore-water pressure change at depth, or even after days to years of slow-motion. While the pre-failure deformation is sometimes apparent in retrospect, it remains challenging to predict the sudden transition from gradual deformation (creep) to runaway failure. We use a network science method–multilayer modularity optimization–to investigate the spatiotemporal patterns of deformation in a region near the 2017 Mud Creek, California landslide. We transform satellite radar data from the study site into a spatially-embedded network in which the nodes are patches of ground and the edges connect the nearest neighbors, with a series of layers representing consecutive transits of the satellite. Each edge is weighted by the product of the local slope (susceptibility to failure) measured from a digital elevation model and ground surface deformation (current rheological state) from interferometric synthetic aperture radar (InSAR). We use multilayer modularity optimization to identify strongly-connected clusters of nodes (communities) and are able to identify both the location of Mud Creek and nearby creeping landslides which have not yet failed. We develop a metric, community persistence, to quantify patterns of ground deformation leading up to failure, and find that this metric increases from a baseline value in the weeks leading up to Mud Creek's failure. These methods promise as a technique for highlighting regions at risk of catastrophic failure.</p>
Validation of the satellite-estimated sedimentation rates in reservoirs using 10-m Sentinel-2 satellites and water level data
<p><strong>Overview</strong>: The database contains data used for the validation of satellite-based sedimentation rates in eight reservoirs across the central and western United States using 10-m Sentinel-2 imagery and in-situ level data. Additional validation of the results from combining Sentinel-2 imagery with simulated 27-day Sentinel-3 altimetry levels is also included.</p> <p> </p> <p><strong>This dataset includes</strong>:</p> <ol> <li>Satellite-derived area-level duplets</li> <li>Bathymetry curves from satellite-based estimates</li> <li>Bathymetry curves from survey data</li> <li>Validation</li> </ol>
Satellite images and road-reference data for AI-based road mapping in Equatorial Asia
<p><span>1. </span><span>INTRODUCTION</span></p> <p><span>For the purposes of training AI-based models to identify (map) road features in rural/remote tropical regions on the basis of true-colour satellite imagery, and subsequently testing the accuracy of these AI-derived road maps, we produced a dataset of 8904 satellite image 'tiles' and their corresponding known road features across Equatorial Asia (Indonesia, Malaysia, Papua New Guinea).</span><span> </span></p> <p><span>2. </span><span>FURTHER INFORMATION</span></p> <p><span>The following is a summary of our data. Fuller details on these data and their underlying methodology are given in the corresponding article, under consideration by the journal Remote Sensing as of September 2023: </span></p> <p><span>Sloan, S., Talkhani, R.R., Huang, T., Engert, J., Laurance, W.F. (2023) Mapping remote roads using artificial intelligence and satellite imagery. Under consideration by Remote Sensing.</span></p> <p><span>Correspondence regarding these data can be directed to:</span></p> <p><span>Sean Sloan</span></p> <p>Department of Geography, Vancouver Island University, Nanaimo, B.C, Canada</p> <p><span><a href="mailto:sean.sloan@viu.ca"><span>sean.sloan@viu.ca</span></a></span>; </p> <p><span>Tao (Kevin) Huang</span></p> <p>College of Science and Engineering, James Cook University, Cairns, Queensland 4878, Australia</p> <p><a href="mailto:tao.huang1@jcu.edu.au">tao.huang1@jcu.edu.au</a><span> </span></p>
Data from: In situ correlation between microplastic and suspended particulate matter concentrations in river-estuary systems support proxies for satellite-derived estimates of microplastic flux
<p>Data from Sullivan et al., (in press) In situ correlation between microplastic and suspended particulate matter concentrations in river-estuary systems support proxies for satellite-derived estimates of microplastic flux, <em>Marine Pollution Bulletin. </em></p> <p>It contains the summary of the in situ measurements of TSM and microplastic counts and concentrations for each site. For more detail on the methods, users are directed to the methods section 2.2 of the open access paper. </p>
Data from: Vegetation growth responses to climate change: A cross-scale analysis of biological memory and time-lags using tree ring and satellite data
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Data from: Forecasting landslides using community detection on geophysical satellite data
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Supporting data for assessing impacts of satellite GPS transmitters on survival, nesting propensity, and nest success of greater sage-grouse
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Crop performance, aerial, and satellite data from multistate maize yield trials
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Data for: Ensemble-based data assimilation of significant wave height from Sofar Spotters and satellite altimeters with a global operational wave model
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Satellite images and road-reference data for AI-based road mapping in Equatorial Asia
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Data from: STREAM-Sat: a novel near-realtime quasi-global satellite-only ensemble precipitation
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Satellite telemetry data for Egyptian Geese in southern Africa
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Data from: Assessing the impacts of satellite tagging on growth rates of immature hawksbill turtles
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Data from: multi-level determinants of land use land cover change in Tigray, Ethiopia: a mixed-effects approach using socioeconomic panel and satellite data
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Data for: Multi-LEO satellite stereo winds
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Data from: The value of satellite tracking across multiple years to identify key areas for conservation
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Satellite-derived trait data slightly improves tropical forest biomass, NPP, and GPP predictions
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Data from: Predicting photosynthesis-irradiance relationships from satellite remote-sensing observations
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Satellite data of the 2018 Sierra Negra eruption in the Galápagos islands
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Satellite telemetry data of Double-crested cormorant locations
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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)
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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.