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423 results for “spatial use”
OCO-2 Level 2 spatially ordered geolocated retrievals screened using the IMAP-DOAS Preprocessor (IDP), Retrospective Processing V10r (OCO2_L2_IMAPDOAS) at GES DISC
Version 10r is the current version of the data set. Older versions will no longer be available and are superseded by Version 10r.In early 2021, the OCO Team identified an issue with OCO-2 level 2 products processed since January 28, 2020. The Ancillary Geometric Product (AGAP) file, a static file used in OCO-2 Geolocation processing, was inadvertently replaced with an obsolete version. This AGAP file included a ~300 m pointing error. As a result, all OCO-2 Level 2, version 10r, data files for the period January 28 - December 31, 2020, were corrected and replaced. The replacement process was completed by the end of June, 2021. The significance of this error has been described in Kiel et al. (2019; doi:10.5194/amt-12-2241-2019).The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. This collection encompass the output from the IMAP-DOAS preprocessor, which is used for both screening of the official XCO2 product as well as for the retrieval of Solar-Induced Fluorescence from the 0.76 micrometer O2 A-band. The IMAP-DOAS preprocessor, just as the ABO2 cloud screen, is implemented in the operational OCO-2 processing pipeline.This is the retrospective processing where the calibration data is estimated from the full timeseries of data (before, during, and after the measurements), and is expected to be of slightly higher quality.
OCO-3 Level 2 spatially ordered geolocated retrievals screened using the A-band Preprocessor, Retrospective Processing V11r (OCO3_L2_ABand) at GES DISC
Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data with further analysis performed on OCO-2 simulations.The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.
OCO-2 Level 2 spatially ordered geolocated retrievals screened using the A-band Preprocessor Retrospective Processing V11.2r (OCO2_L2_ABand) at GES DISC
Version 11.2r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11.2r.The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers.
OCO-3 Level 2 spatially ordered geolocated retrievals screened using the IMAP-DOAS Preprocessor (IDP), Retrospective Processing V10r (OCO3_L2_IMAPDOAS) at GES DISC
Version 10r is the current version of the data set. Older versions will no longer be available and are superseded by Version 10r.The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data with further analysis performed on OCO-2 simulations.The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.
OCO-3 Level 2 spatially ordered geolocated retrievals screened using the A-band Preprocessor, Retrospective Processing V10r (OCO3_L2_ABand) at GES DISC
Version 10r is the current version of the data set. Older versions will no longer be available and are superseded by Version 10r.The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data with further analysis performed on OCO-2 simulations.The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.
Characterization of immune cell populations in the tumor microenvironment of colorectal cancer using high definition spatial profiling [VisiumHD]
GEO Series GSE280315. Homo sapiens. 5 samples. Type: Other.
High resolution mapping of the tumor microenvironment using integrated single-cell, spatial and in situ analysis
GEO Series GSE243280. Homo sapiens. 7 samples. Type: Other; Expression profiling by high throughput sequencing.
Comparison of imaging based single-cell resolution spatial transcriptomics profiling platforms using formalin-fixed paraffin-embedded tumor samples [CosMx]
GEO Series GSE299786. Homo sapiens. 4 samples. Type: Other.
Characterization of immune cell populations in the tumor microenvironment of colorectal cancer using high definition spatial profiling [Flex]
GEO Series GSE280311. Homo sapiens. 12 samples. Type: Expression profiling by high throughput sequencing.
Cell-Type Profiling of the Sympathetic Nervous System Using Spatial Transcriptomics and Spatial Mapping of mRNA [Slide-seq]
GEO Series GSE230776. Gallus gallus. 1 samples. Type: Expression profiling by high throughput sequencing.
Determination of the spatial organization of the FXN gene locus by using Chromosome Conformation Capture technique coupled with High-throughtput sequencing (3C-seq).
GEO Series GSE42961. Homo sapiens. 5 samples. Type: Other.
Characterization of immune cell populations in the tumor microenvironment of colorectal cancer using high definition spatial profiling
GEO Series GSE280318. Homo sapiens. 39 samples. Type: Expression profiling by high throughput sequencing; Other.
Comparison of imaging based single-cell resolution spatial transcriptomics profiling platforms using formalin-fixed paraffin-embedded tumor samples [Xenium]
GEO Series GSE300007. Homo sapiens. 6 samples. Type: Other.
Spatially resolved whole transcriptome profiling in human and mouse tissue using Digital Spatial Profiling [human tonsil]
GEO Series GSE188451. Homo sapiens. 49 samples. Type: Expression profiling by high throughput sequencing; Other.
Comprehensive identification and spatial mapping of habenular neuronal types using single cell RNAseq
GEO Series GSE105115. Danio rerio. 1143 samples. Type: Expression profiling by high throughput sequencing.
Unraveling the Cellular Landscape of Abdominal Aortic Aneurysm Using High-Resolution Spatial Transcriptomics:
GEO Series GSE229500. Mus musculus; synthetic construct. 3 samples. Type: Expression profiling by high throughput sequencing.
Probing pathways by which rhynchophylline modifies sleep using spatial transcriptomics
GEO Series GSE217058. Mus musculus. 8 samples. Type: Expression profiling by high throughput sequencing; Other.
GENE EXPRESSION WITHIN A HUMAN CHOROIDAL NEOVASCULAR MEMBRANE USING SPATIAL TRANSCRIPTOMICS
GEO Series GSE234047. Homo sapiens. 5 samples. Type: Expression profiling by high throughput sequencing.
Characterization of immune cell populations in the tumor microenvironment of colorectal cancer using high definition spatial profiling [VisiumV2]
GEO Series GSE280313. Homo sapiens. 3 samples. Type: Other.
Defining Cellular Diversity at the Swine Maternal-Fetal Interface Using Spatial Transcriptomics and Organoids
GEO Series GSE301436. Sus scrofa. 2 samples. Type: Expression profiling by high throughput sequencing.
ScienceDex guides
Understand access before you commit
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.