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403 results for “satellite data”
Data from: When and where does mortality occur in migratory birds? Direct evidence from long-term satellite tracking of raptors
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Data from: Filling knowledge gaps in a threatened shorebird flyway through satellite tracking
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Data from: A daily global mesoscale ocean eddy dataset from satellite altimetry
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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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Data from: Satellite tracking reveals novel migratory patterns and the importance of seamounts for endangered South Pacific humpback whales
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Data from: Global energy sector methane emissions estimated by using facility-level satellite observations
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Data from: Computational research on mobile pastoralism using agent-based modeling and satellite imagery
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Data from: Modeling avian biodiversity using raw, unclassified satellite imagery
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Data from: Synergistic use of UAV surveys, satellite tracking data and mark-recapture to estimate abundance of elusive species
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Data from: Processing of acceleration and dive data on-board satellite relay tags to investigate diving and foraging behaviour in free-ranging marine predators
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PREFIRE Auxiliary Satellite Data for PREFIRE Satellite 1 R01
PREFIRE (Polar Radiant Energy in the Far InfraRed Experiment) Auxiliary Satellite Data for PREFIRE Satellite 2 contains data fields extracted from external satellite datasets for each coincident PREFIRE Thermal Infrared Spectrometer (TIRS-PREFIRE) field of view, which is then used to process PREFIRE Level 2 and 3 products. Dual CubeSats each carry a 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 models to predict future conditions more accurately.This collection contains surface-type information from VIIRS, Aqua, and NISE (SSMIS). Its primary purpose is to provide surface type information for the PREFIRE Level 2 spectral flux product (PREFIRE_SAT1_2B-FLX) and the Level 3 surface emissivity product (PREFIRE_SAT1_3-SFC-SORTED-ALLSKY), which is sorted by surface type. Science data retrieval started July 24, 2024 and is ongoing. Geographic coverage is global, with the greatest concentration of data in the polar regions. Within the orbital swath there are eight distinct tracks of data associated with the eight separate spatial scenes for each PREFIRE-TIRS. At the beginning of the mission, the approximate scene footprint sizes were 11.8 km x 34.8 km (cross-track x along-track), with gaps between each scene of approximately 24.2 km. The entire swath was ~264 km across. Note that the scene footprint and swath sizes quoted here are for the orbit altitude soon after launch. However, the footprint size will slowly become smaller as the orbit altitude decreases with time. This data has a temporal resolution of 0.707 seconds and is available in netCDF-4.The auxiliary satellite data for the sister instrument aboard PREFIRE-SAT2 can be found in the PREFIRE_SAT2_AUX-SAT collection.
PREFIRE Auxiliary Meteorology Data for PREFIRE Satellite 2 R01
Polar Radiant Energy in the Far InfraRed Experiment (PREFIRE) Auxiliary Meteorology Data for PREFIRE Satellite 2 (PREFIRE_SAT2_AUX-MET) contains GEOS-IT analyses and VIIRS satellite data that are subsets and interpolations corresponding to data collected by the PREFIRE Thermal Infrared Spectrometer (TIRS-PREFIRE) aboard PREFIRE-SAT2. Dual PREFIRE CubeSats each 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 models to predict future conditions more accurately.PREFIRE_SAT2_AUX-MET contains surface and skin temperatures, land fraction, sea ice concentration, snow cover, surface pressure, temperature profiles, pressure profiles, O3 profiles, wind velocity profiles, and surface type. Science data retrieval started June 29, 2024 and is ongoing. Geographic coverage is global, with the greatest concentration of data in the polar regions. Within the orbital swath there are eight distinct tracks of data associated with the eight separate spatial scenes for each PREFIRE-TIRS. At the beginning of the mission, the approximate scene footprint sizes were 11.8 km x 34.8 km (cross-track x along-track), with gaps between each scene of approximately 24.2 km. The entire swath was ~264 km across. Note that the scene footprint and swath sizes quoted here are for the orbit altitude soon after launch. However, the footprint size will slowly become smaller as the orbit altitude decreases with time. This data has a temporal resolution of 0.707 seconds and is available in netCDF-4.The auxiliary meteorology data for the sister instrument aboard PREFIRE-SAT1 can be found in the PREFIRE_SAT1_AUX-MET collection.
PREFIRE Auxiliary Meteorology Data for PREFIRE Satellite 1 version R01
Polar Radiant Energy in the Far InfraRed Experiment (PREFIRE) Auxiliary Meteorology Data for PREFIRE Satellite 1 (PREFIRE_SAT1_AUX-MET) contains GEOS-IT analyses and VIIRS satellite data that are subsets and interpolations corresponding to data collected by the PREFIRE Thermal Infrared Spectrometer (TIRS-PREFIRE) aboard PREFIRE-SAT1. Dual PREFIRE CubeSats each 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 models to predict future conditions more accurately.PREFIRE_SAT1_AUX-MET contains surface and skin temperatures, land fraction, sea ice concentration, snow cover, surface pressure, temperature profiles, pressure profiles, O3 profiles, wind velocity profiles, and surface type. Science data retrieval started July 24, 2024 and is ongoing. Geographic coverage is global, with the greatest concentration of data in the polar regions. Within the orbital swath there are eight distinct tracks of data associated with the eight separate spatial scenes for each PREFIRE-TIRS. At the beginning of the mission, the approximate scene footprint sizes were 11.8 km x 34.8 km (cross-track x along-track), with gaps between each scene of approximately 24.2 km. The entire swath was ~264 km across. Note that the scene footprint and swath sizes quoted here are for the orbit altitude soon after launch. However, the footprint size will slowly become smaller as the orbit altitude decreases with time. This data has a temporal resolution of 0.707 seconds and is available in netCDF-4.The auxiliary meteorology data for the sister instrument aboard PREFIRE-SAT2 can be found in the PREFIRE_SAT2_AUX-MET collection.
PREFIRE Auxiliary Satellite Data for PREFIRE Satellite 2 R01
PREFIRE (Polar Radiant Energy in the Far InfraRed Experiment) Auxiliary Satellite Data for PREFIRE Satellite 2 contains data fields extracted from external satellite datasets for each coincident PREFIRE Thermal Infrared Spectrometer (TIRS-PREFIRE) field of view, which is then used to process PREFIRE Level 2 and 3 products. Dual CubeSats each carry a 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 models to predict future conditions more accurately.This collection contains surface-type information from VIIRS, Aqua, and NISE (SSMIS). Its primary purpose is to provide surface type information for the PREFIRE Level 2 spectral flux product (PREFIRE_SAT2_2B-FLX) and the Level 3 surface emissivity product (PREFIRE_SAT2_3-SFC-SORTED-ALLSKY), which is sorted by surface type. Science data retrieval started June 29, 2024 and is ongoing. Geographic coverage is global, with the greatest concentration of data in the polar regions. Within the orbital swath there are eight distinct tracks of data associated with the eight separate spatial scenes for each PREFIRE-TIRS. At the beginning of the mission, the approximate scene footprint sizes were 11.8 km x 34.8 km (cross-track x along-track), with gaps between each scene of approximately 24.2 km. The entire swath was ~264 km across. Note that the scene footprint and swath sizes quoted here are for the orbit altitude soon after launch. However, the footprint size will slowly become smaller as the orbit altitude decreases with time. This data has a temporal resolution of 0.707 seconds and is available in netCDF-4.The auxiliary satellite data for the sister instrument aboard PREFIRE-SAT1 can be found in the PREFIRE_SAT1_AUX-SAT collection.
Data repository from Boudewijn van Lieshout' thesis A comparison between Normalized Difference Vegetation Indices calculated from Sentinel 2A satellite data and high-resolution UAV imagery in Tanzania
<p>Monitoring vegetation is imperative for policy design and efficiency measurements. Frequent data collection, easy and inexpensive accessibility of images and the possibility of large area analysis, makes it still valuable to use satellite imagery. This study aims to examine how a Normalized Difference Vegetation Index (NDVI) measured with Sentinel-2A satellite data relates to an NDVI from Unmanned Aerial Vehicles (UAV henceforth) in study areas Chamwino Mlimwa and Chemba Waida, Tanzania.</p>
Data from: Centromere satellite repeats have undergone rapid changes in polyploid wheat subgenomes
Centromeres mediate the pairing of homologous chromosomes during meiosis; this pairing is particularly challenging for polyploid plants such as hexaploid wheat (Triticum aestivum), as their meiotic machinery must differentiate homologs from similar homoeologs. However, the sequence compositions (especially functional centromeric satellites) and evolutionary history of wheat centromeres are largely unknown. Here, we mapped T. aestivum centromeres by chromatin immunoprecipitation sequencing using antibodies to the centromeric-specific histone CENH3; this identified two types of functional centromeric satellites that are abundant in two of the three subgenomes. These centromeric satellites had unit sizes over 500 bp and contained specific sites with highly phased binding to CENH3 nucleosomes. Phylogenetic analysis revealed that the satellites have diverged in the three T. aestivum subgenomes, and the more homogeneous satellite arrays are associated with CENH3. Satellite signals decreased and the degree of satellites variation increased from diploid to hexaploid wheat. Moreover, several T. aestivum centromeres lack satellite repeats. Rearrangements, including local expansion and satellite variations, inversions, and changes in gene expression, occurred during the evolution from diploid to tetraploid and hexaploid wheat. These results reveal the asymmetry in centromere organization among the wheat subgenomes, which may play a role in proper homolog pairing during meiosis.
Manuscript code & data: Foster et al. (2020) "Satellite-based monitoring of irrigation water use: assessing measurement errors and their implications for agricultural water management policy"
<p>Data to reproduce results presented in Foster, T., Mieno, T. and Brozovic, N. (2020). <em>Satellite-based monitoring of irrigation water use: assessing measurement errors and their implications for agricultural water management policy.</em> Water Resources Research. In Review. Files provide include:</p> <ul> <li>"ReviewMetadata_FosterWRR_2020.xlsx" - data needed to reproduce meta-analysis presented in the paper</li> <li>"MeasurementErrorCode_FosterWRR_2020.m" and "Foster2018_ProductionFunction.mat" - Matlab code and data needed to reproduce welfare loss analysis presented in the paper.</li> </ul>
Assimilation of Satellite Radiance Data with the POD-4DEnVar Method for the Forecasting of Binary Typhoons
<p>The data and codes for ploting the figures in our manuscript are provided here.</p>
Data from: The organization and evolution of the Responder satellite in species of the Drosophila melanogaster group: dynamic evolution of a target of meiotic drive
Background: Satellite DNA can make up a substantial fraction of eukaryotic genomes and has roles in genome structure and chromosome segregation. The rapid evolution of satellite DNA can contribute to genomic instability and genetic incompatibilities between species. Despite its ubiquity and its contribution to genome evolution, we currently know little about the dynamics of satellite DNA evolution. The Responder (Rsp) satellite DNA family is found in the pericentric heterochromatin of chromosome 2 of Drosophila melanogaster. Rsp is well-known for being the target of Segregation Distorter (SD) an autosomal meiotic drive system in D. melanogaster. I present an evolutionary genetic analysis of the Rsp family of repeats in D. melanogaster and its closely-related species in the melanogaster group (D. simulans, D. sechellia, D. mauritiana, D. erecta, and D. yakuba) using a combination of available BAC sequences, whole genome shotgun Sanger reads, Illumina short read deep sequencing, and fluorescence in situ hybridization. Results: I show that Rsp repeats have euchromatic locations throughout the D. melanogaster genome, that Rsp arrays show evidence for concerted evolution, and that Rsp repeats exist outside of D. melanogaster, in the melanogaster group. The repeats in these species are considerably diverged at the sequence level compared to D. melanogaster, and have a strikingly different genomic distribution, even between closely-related sister taxa. Conclusions: The genomic organization of the Rsp repeat in the D. melanogaster genome is complex--it exists of large blocks of tandem repeats in the heterochromatin and small blocks of tandem repeats in the euchromatin. My discovery of heterochromatic Rsp-like sequences outside of D. melanogaster suggests that SD evolved after its target satellite and that the evolution of the Rsp satellite family is highly dynamic over a short evolutionary time scale (<240,000 years).
Data from: Critical analysis of forest degradation in the southern Eastern Ghats of India: comparison of satellite imagery and soil quality index
India has one of the largest assemblages of tropical biodiversity, with its unique floristic composition of endemic species. However, current forest cover assessment is performed via satellite-based forest surveys, which have many limitations. The present study, which was performed in the Eastern Ghats, analysed the satellite-based inventory provided by forest surveys and inferred from the results that this process no longer provides adequate information for quantifying forest degradation in an empirical manner. The study analysed 21 soil properties and generated a forest soil quality index of the Eastern Ghats, using principal component analysis. Using matrix modules and geospatial technology, we compared the forest degradation status calculated from satellite-based forest surveys with the degradation status calculated from the forest soil quality index. The Forest Survey of India classified about 1.8% of the Eastern Ghats' total area as degraded forests and the remainder (98.2%) as open, dense, and very dense forests, whereas the soil quality index results found that about 42.4% of the total area is degraded, with the remainder (57.6%) being non-degraded. Our ground truth verification analyses indicate that the forest soil quality index along with the forest cover density data from the Forest Survey of India are ideal tools for evaluating forest degradation.
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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.