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100 results for “AVHRR”
LBA Regional Land Cover from AVHRR, 1-Degree, 1987 (Defries and Townshend)
This data set consists of a subset for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., longitude 85 deg to 30 deg W, latitude 25 deg S to 10 deg N) of the University of Maryland (UMD) 1-degree Global Land Cover product in ASCII GRID and binary image formats.The UMD 1-degree Global Land Cover product was produced by researchers at the Laboratory for Global Remote Sensing Studies (LGRSS) at UMD. The product is based on Advanced Very High Resolution Radiometer (AVHRR) maximum monthly composites for 1987 of Normalized Difference Vegetation Index (NDVI) values at approximately 8-km resolution, averaged to one-by-one degree resolution. This coarse- resolution data set was used as the basis for a supervised classification of eleven cover types that broadly represent the major biomes of the world. Because of missing values at high latitudes, the Pathfinder AVHRR data set for 1987 for summer monthly NDVI and red reflectance values were used to distinguish the following cover types: tundra, high latitude deciduous forest and woodland, coniferous evergreen forest and woodland.The 1-degree global land cover product is available for download from the Global Land Cover Facility (GLCF)[http://glcf.umiacs.umd.edu/data/landcover/index.shtml] web site. The data are available as a global coverage in both binary and ASCII format. Additional information and references on this data set can be found at the GLCF web site as well as at the LGRSS web site (link provided at the GLCF web site ) and in the readme file found along with the data [ ftp://daac.ornl.gov/data/lba/land_use_change/land_cover_data_1deg/comp/README].
SAFARI 2000 Land Cover from AVHRR, 1-km, 1992-1993 (Hansen et al.)
The data set consists of a southern African subset of the 1-km Global Land Cover Data Set Derived from AVHRR developed at the Laboratory for Global Remote Sensing Studies (LGRSS) at the University of Maryland. Both ASCII data and binary image files are available. Over the past several years, researchers have increasingly turned to remotely sensed data to improve the accuracy of data sets that describe the geographic distribution of land cover at regional and global scales. To develop improved methodologies for global land cover classifications as well as to provide global land cover products for immediate use in global change research, researchers at the Laboratory for Global Remote Sensing Studies (LGRSS) at the University of Maryland have employed the NASA/NOAA Pathfinder Land (PAL) data set with a spatial resolution of 1 km. This data set has a record length of 14 years (1981-1994), providing the ability to test the stability of classification algorithms. Furthermore, this data set includes red, infrared, and thermal bands in addition to the Normalized Difference Vegetation Index (NDVI). Inclusion of these additional bands improves discrimination between cover types. The project aim is to develop and validate global land cover data sets and to develop advanced methodologies for more realistically describing the vegetative land surface based on satellite data. The 1-km global land cover product was created from 1992-93 LAC AVHRR data. The full 1-km global land cover product is available for download from the Global Land Cover Facility (GLCF) web site. Forty-one (41) metrics were developed to describe global vegetation phenology, and these data were used to make the 1-km land cover map. The final product contains 13 land cover classes. More information can be found at: ftp://daac.ornl.gov/data/safari2k/vegetation_wetlands/land_cover_data-1km/comp/glcf1km_readme.pdf.
GHRSST Level 2P Global Sea Surface Temperature v2.0 from the AVHRR on the MetOp-C satellite produced by NAVO
A global Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P data set containing multi-channel Sea Surface Temperature (SST) retrievals derived in real-time from the Advanced Very High Resolution Radiometer (AVHRR) level-1B data from the Meteorological Operational-C (MetOp-C) satellite. The SST data in this data set are used operationally in oceanographic analyses and forecasts by the US Naval Oceanographic Office (NAVO). The MetOp satellite program is a European multi-satellite program to provide weather data services for monitoring climate and improving weather forecasts. MetOp-A, MetOp-B and Metop-C were respectively launched on 19 Oct 2006, 17 September 2012 and 7 November 2018. The program was jointly established by the European Space Agency (ESA) and the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) with the US National Oceanic and Atmospheric Administration (NOAA) contributing the AVHRR sensor. AVHRR instruments measure the radiance of the Earth in 5 (or 6) relatively wide spectral bands. The first two are centered around the red (0.6 micron) and near-infrared (0.9 micron) regions, the third one is located around 4 (3.6) micron, and the last two sample the emitted thermal radiation, around 11 and 12 micron, respectively. The legacy 5 band instrument is known as AVHRR/2 while the more recent version, the AVHRR/3 (first carried on the NOAA-15 platform), acquires data in a 6th channel located at 1.6 micron. Typically, the 11 and 12 micron channels are used to derive SST sometimes in combination with the 3.5 micron channel. The swath of the AVHRR sensor is a relatively large 2400 km. All MetOp platforms are sun synchronous and generally view the same earth location twice a day (latitude dependent). The ground native resolution of the AVHRR instruments is approximately 1.1 km at nadir and degrades off nadir. This particular data set is produced from legacy Global Area Coverage (GAC) data that are derived from a sample averaging of the full resolution global AVHRR data. Four out of every five samples along the scan line are used to compute on average value and the data from only every third scan line are processed, yielding an effective 4 km spatial resolution at nadir. The v2.0 is the updated version from current v1.0 with extensive algorithm improvements and upgrades. The major improvements include: 1) Significant changes in contaminant/cloud detection; 2) Increased the spatial resolution from 9 km to 4 km; 3) Updated compliance with GDS2, ACDD 1.3, and CF 1.6; and 4) Removed the dependency on the High-resolution Infrared Radiation Sounder (HIRS) sensor (only available to MetOp-A/B), thus allowing for the consistent inter-calibration and the processing of MetOp-A/B/C data
LBA Regional Tree Cover from AVHRR, 1-km, 1992-1993 (DeFries et al.)
The data set consists of a subset for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., longitude 85 deg to 30 deg W, latitude 25 deg S to 10 deg N) of the 1km Global Tree Cover Data Set developed at the Laboratory for Global Remote Sensing Studies (LGRSS) at the University of Maryland. Data are available in both ASCII GRID and binary image files formats.Characterization of terrestrial vegetation from the Advanced Very High Resolution Radiometer (AVHRR) on the global to regional scale has traditionally been accomplished using classification schemes with discrete numbers of vegetation classes. Representation of vegetation into a limited number of homogeneous classes does not account for the variability within land cover, nor does the portrayal recognize transition zones between adjacent cover types. An alternative paradigm to describing land cover as discrete classes is to represent land cover as continuous fields of vegetation characteristics using a linear mixture model approach. This prototype data set, created by researchers at the Laboratory for Global Remote Sensing Studies (LGRSS) at the University of Maryland, contains 1-km cells estimating: 1) Percent tree cover; 2) Percentage cover for two layers representing leaf longevity (evergreen and deciduous); and 3) Percentage cover for two layers estimating leaf type (broadleaf and needleleaf).Data acquired in 1992-93 from NOAA's AVHRR at a 1-km spatial resolution and processed under the guidance of the International Geosphere Biosphere Programme (IGBP) were used to derive the tree cover, leaf type and leaf longevity maps. Each pixel in the layers has a value between 10 and 80 percent. These layers can be directly used as parameters in models or aggregated into more conventional land cover maps. For the latter, the product offers the flexibility to derive land cover maps based on user's requirements for a particular application. The product is intended for use in terrestrial carbon cycle models, in conjunction with other spatial data sets such as climate and soil type, to obtain more consistent and reliable estimates of carbon stocks.
GHRSST Level 2P Global 1m Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the MetOp-A satellite produced by NAVO
A global Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on multi-channel sea surface temperature (SST) retrievals generated in real-time from the Advanced Very High Resolution Radiometer (AVHRR) on the European Meteorological Operational-A (MetOp-A; launched 19 Oct 2006) ) satellite produced and used operationally in oceanographic analyses and forecasts by the US Naval Oceanographic Office (NAVO). The MetOp satellite program is a European undertaking providing weather data services for monitoring climate and improving weather forecasts. It was jointly established by the European Space Agency (ESA) and the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) with a contribution by the US National Oceanic and Atmospheric Administration (NOAA) of an AVHRR sensor identical to those flying on the family of Polar Orbiting Environmental Satellites (POES). AVHRR instruments measure the radiance of the Earth in 5 (or 6) relatively wide spectral bands. The first two are centered around the red (0.6 micrometer) and near-infrared (0.9 micrometer) regions, the third one is located around 3.5 micrometer, and the last two sample the emitted thermal radiation, around 11 and 12 micrometers, respectively. The legacy 5 band instrument is known as AVHRR/2 while the more recent version, the AVHRR/3 (first carried on the NOAA-15 platform), acquires data in a 6th channel located at 1.6 micrometer. Typically the 11 and 12 micron channels are used to derive SST sometimes in combination with the 3.5 micron channel. The MetOp-A platform is sun synchronous generally viewing the same earth location twice a day (latitude dependent) due to the relatively large AVHRR swath of approximately 2400 km. The highest ground resolution that can be obtained from the current AVHRR instruments is 1.1 km at nadir. This particular dataset is produced from Global Area Coverage (GAC) data that are derived from an on-board sample averaging of the full resolution global AVHRR data. Four out of every five samples along the scan line are used to compute on average value and the data from only every third scan line are processed, yielding an effective 4 km resolution at nadir. Further binning and averaging of these pixels results in a final dataset resolution of 8.8 km.
GHRSST Level 4 AVHRR_OI Global Blended Sea Surface Temperature Analysis (GDS version 2) from NCEI
A Group for High Resolution Sea Surface Temperature (GHRSST) global Level 4 sea surface temperature analysis produced daily on a 0.25 degree grid at the NOAA National Centers for Environmental Information. This product uses optimal interpolation (OI) by interpolating and extrapolating SST observations from different sources, resulting in a smoothed complete field. The sources of data are satellite (AVHRR) and in situ platforms (i.e., ships and buoys), and the specific datasets employed may change over. At the marginal ice zone, sea ice concentrations are used to generate proxy SSTs. A preliminary version of this file is produced in near-real time (1-day latency), and then replaced with a final version after 2 weeks. Note that this is the AVHRR-ONLY (AVHRR-OI), available from September 1, 1981, but there is a companion SST product that includes microwave satellite data, available from June 2002.
RLC AVHRR-Derived Land Cover, Former Soviet Union, Far East, 1-km, 1990
This data set is a 1-kilometer resolution land cover map for the land area of the Primor'ye and Southern Khabarovsk Regions, in the Russian Far East, based on 1990 NOAA AVHRR data. Labeling of land cover classes depended upon the Russian 1990 Forest Cover Map (Garsia, 1990), the analyst's experience with AVHRR data, and Russian data sources. There are eight classes distinguished in this dataset, of which 5 are forest cover classes.The objective of this work was to create a 1-km resolution land cover map of the region of the Far Eastern Siberia based on NOAA AVHRR data which might be used by World Wildlife Fund researchers to aid in the definition of remaining habitats and range for threatened animal species (Stone and Schlesinger, 1996).
GHRSST Level 2P sub-skin Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on Metop satellites (currently Metop-B) (GDS V2) produced by OSI SAF
A global 1 km Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on multi-channel sea surface temperature (SST) retrievals generated in real-time from the Advanced Very High Resolution Radiometer (AVHRR) on the European Meteorological Operational-B (MetOp-B) satellite (launched 17 Sep 2012). The European Organization for the Exploitation of Meteorological Satellites (EUMETSAT),Ocean and Sea Ice Satellite Application Facility (OSI SAF) is producing SST products in near realtime from Metop/AVHRR. Global AVHRR level 1b data are acquired at Meteo-France/Centre deMeteorologie Spatiale (CMS) through the EUMETSAT/EUMETCAST system. SST is retrievedfrom the AVHRR infrared channels (3.7, 10.8 and 12.0 micrometer) using a multispectral algorithm.Atmospheric profiles of water vapor and temperature from a numerical weather prediction model,together with a radiatiave transfer model, are used to correct the multispectral algorithm forregional and seasonal biases due to changing atmospheric conditions. This product is delivered atfull resolution in satellite projection as metagranule corresponding to 3 minutes of acquisition. Theproduct format is compliant with the GHRSST Data Specification (GDS) version 2.
ISLSCP II NOAA 5-year Average Monthly Snow-free Albedo from AVHRR
The objective of this work was to produce a monthly climatology of broadband surface albedos for use in global numerical weather prediction models at the National Centers for Environmental Prediction (NCEP). Monthly means of clear-sky, surface, broadband, snow-free albedos for overhead sun illumination angle were determined using data from a five-year period from April 1985-December 1987 and January 1989-March 1991. The data set is compatible in temporal coverage and spatial resolution with a monthly climatology of green vegetation fraction (Gutman and Ignatov, 1998) delivered earlier and currently in use at NCEP. Files showing the differences between the original data set and the Land/water mask used in the International Satellite land Surface Climatology Project (ISLSCP) Initiative II are also provided.
GHRSST NOAA/STAR Metop-A AVHRR FRAC ACSPO v2.80 1km L2P Dataset (GDS v2)
The MetOp First Generation (FG) is a European multi-satellite program jointly established by ESA and EUMETSAT, comprising three satellites, MetOp-A, -B and -C. The primary sensor onboard MetOp-FG, the Advanced Very High Resolution Radiometer/3 (AVHRR/3) contributed by NOAA, measures Earth emissions and reflectances in 5 out of 6 available bands (centered at 0.63, 0.83, 1.61, 3.7, 11 and 12 microns), in a swath of 2,600km from an 817km altitude. These data are collected in a Full Resolution Area Coverage (FRAC) mode, with pixel size of 1.1km at nadir. MetOp-A launched on 19 October 2006 is the first in the MetOp-FG series. The NOAA Advanced Clear-Sky Processor for Ocean (ACSPO) Level 2 Preprocessed (L2P) SST product is derived at the full AVHRR FRAC resolution and reported in 10 minute granules in NetCDF4 format, compliant with the GHRSST Data Specification version 2 (GDS2). Subskin SSTs are derived using the regression Nonlinear SST (NLSST) algorithm, which employs three bands (3.7, 11 and 12 microns) at night and two bands (11 and 12 microns) during the day. The ACSPO AVHRR FRAC L2P product is monitored and validated against quality controlled in situ data, provided by the NOAA in situ SST Quality Monitor system (iQuam; Xu and Ignatov, 2014, https://doi.org/10.1175/JTECH-D-13-00121.1 ), in another NOAA system, SST Quality Monitor (SQUAM; Dash et al, 2010, https://doi.org/10.1175/2010JTECHO756.1 ). SST imagery and clear-sky masking are continuously evaluated, and checked for consistency with other sensors and platforms, in the ACSPO Regional Monitor for SST (ARMS) system. MetOp-A orbital characteristics and AVHRR/3 sensor performance are tracked in the NOAA 3S system (He et al., 2016, https://doi.org/10.3390/rs8040346 ).The L2P Near Real Time (NRT) SST files are archived at PO.DAAC with 3-6 hours latency, and then replaced by the Re-ANalysis (RAN) SST after about 2 months later with identical file names. Two features can be used to identify them: different file name time stamps and netCDF global attribute metadata source=NOAA-NCEP-GFS for NRT and source=MERRA-2 for RAN. A reduced size (0.45GB/day), equal-angle gridded (0.02-deg resolution) ACSPO L3U product is available at https://doi.org/10.5067/GHMTA-3US28
RLC AVHRR-Derived Land Cover, Former Soviet Union, 15-km, 1984-1993
This dataset is a 15-kilometer resolution land cover map for the land area of the Former Soviet Union. There are sixty land cover classes distinguished in this dataset, of which 38 are forest cover classes. The data set is useful for stratification of the FSU into general sub-regions of land cover for subsequent study using higher resolution satellite data.
SAFARI 2000 AVHRR Daily Site (1.5 km) and 15-Day Regional (1.5- and 6-km) Imagery
The Global Inventory Mapping and Modeling (GIMMS) group at NASA/GSFC provided SAFARI 2000 with remotely sensed satellite data products at the site and regional level. These AVHRR data contain two main sets of data: site extracts of SAFARI core sites (Mongu, Etosha, Kasungu, Maun, Skukuza, and Tshane), and regional 15-day composites from sets of single-day images. These AVHRR data contain four main sets of data:1.5 km daily site extracts of SAFARI core sites (2000)1.5 km 15-day composites of SAFARI core sites (1998-2000)1.5 km 15-day composites of the southern African region (Mar, Sept 2000)6 km 15-day composites of the southern African region (1998-2000)The primary data layers for site extracts and regional composites are fire pixel counts and maximum NDVI. The fire product is different for the daily and for the composited products (see readme file) and a fire product is not included in the 1.5 km regional data set. NDVI composite-associated data layers for the regional data sets include land surface temperature, reflectance, solar zenith angle, view zenith angle, and relative azimuth angle. NDVI composite-associated data layers for the site extracts include these same variables as well as brightness temperature, fire mask composite, latitude, and longitude. The data are stored in binary image format files. There is a metadata file for each site and date/compositing period, in ASCII format.
GHRSST Level 4 AVHRR_OI Global Blended Sea Surface Temperature Analysis (GDS2) from NCEI
A Group for High Resolution Sea Surface Temperature (GHRSST) global Level 4 sea surface temperature dataset is produced daily on a 0.25 degree grid at the NOAA National Centers for Environmental Information. This product uses optimal interpolation (OI) by interpolating and extrapolating SST observations from different sources, resulting in a smoothed complete field. The sources of data are satellite (AVHRR) and in situ platforms (i.e., ships, buoys, and Argo floats above 5m depth), and the specific datasets employed may change over time. In the regions with sea-ice concentration higher than 30%, freezing points of seawater are used to generate proxy SSTs. A preliminary version of this dataset is produced in near-real time (1-day latency), and then replaced with a final version after 2 weeks. The v2.1 (Huang et al. 2021) is updated from the previous AVHRR_OI-NCEI-L4-GLOB-v2.0 data. Major improvements include: 1) In-situ ship and buoy data changed from the NCEP Traditional Alphanumeric Codes (TAC) to the NCEI merged TAC + Binary Universal Form for the Representation (BUFR) data, with large increases of buoy data included to correct satellite SST biases; 2) Addition of Argo float observed SST data as well, for further correction of satellite SST biases; 3) Satellite input from the METOP-A and NOAA-19 to METOP-A and METOP-B, removing degraded satellite data; 4) Revised ship-buoy SST corrections for improved accuracy; and 5) Revised sea-ice-concentration to SST conversion to remove warm biases in the Arctic region. These updates only apply to data after January 1st, 2016. The data pre 2016 are still the same as v2.0 except for metadata upgrades. NCEI has panned to update the entire dataset from 1982 to fix the In-Situ data ingest and bias correction which exist prior 2016.
CLPX-Satellite: AVHRR/HRPT Brightness Temperatures and Reflectances, Version 1
This data set includes AVHRR/HRPT (Advanced Very High Resolution Radiometer/High Resolution Picture Transmission) brightness temperatures and reflectances over the NASA Cold Land Processes Field Experiment (CLPX) Large Regional Study Area (LRSA).
GHRSST NOAA/STAR Metop-C AVHRR FRAC ACSPO v2.80 0.02 L3U Dataset (GDS v2)
This L3U (Level 3 Uncollated) dataset contains global daily Sea Surface Temperature (SST) on a 0.02 degree grid resolution. It is produced by the National Oceanic and Atmospheric Administration (NOAA) Advanced Clear Sky Processor for Ocean (ACSPO) using L2P (Level 2 Preprocessed) product acquired from the Meteorological Operational satellite C (Metop-C) Advanced Very High Resolution Radiometer 3 (AVHRR/3) (https://podaac.jpl.nasa.gov/dataset/AVHRRF_MC-STAR-L2P-v2.80 ) in Full Resolution Area Coverage (FRAC) mode as input. It is distributed as 10-minute granules in netCDF-4 format, compliant with the Group for High Resolution Sea Surface Temperature (GHRSST) Data Specification version 2 (GDS2). There are 144 granules per 24-hour interval. Fill values are reported in all invalid pixels, including land pixels with >5 km inland. For each valid water pixel (defined as ocean, sea, lake or river), and up to 5 km inland, the following major layers are reported: SSTs and ACSPO clear-sky mask (ACSM; provided in each grid as part of l2p_flags, which also includes day/night, land, ice, twilight, and glint flags). Only input L2P SSTs with QL=5 were gridded, so all valid SSTs are recommended for the users. Per GDS2 specifications, two additional Sensor-Specific Error Statistics layers (SSES bias and standard deviation) are reported in each pixel with valid SST. Ancillary layers include wind speed and ACSPO minus reference Canadian Meteorological Centre (CMC) Level 4 (L4) SST. The ACSPO Metop-C AVHRR FRAC L3U product is monitored and validated against iQuam in situ data (Xu and Ignatov, 2014) in the NOAA SST Quality Monitor (SQUAM) system (Dash et al, 2010). SST imagery and clear-sky mask are evaluated, and checked for consistency with L2P and other satellites/sensors SST products, in the NOAA ACSPO Regional Monitor for SST (ARMS) system. More information about the dataset is found at AVHRRF_MC-STAR-L2P-v2.80 and in (Pryamitsyn et al., 2021).
BOREAS AFM-12 1-km AVHRR Seasonal Land Cover Classification
This regional land cover classification is based on the use of multitemporal 1-km Advanced Very High Resolution Radiometer (AVHRR) National Oceanic and Atmospheric Administration (NOAA 11) data that were analyzed in combination with selected Landsat Thematic Mapper (TM) and extensive field observations within a 619-km by 821-km subset of the 1,000-km by 1,000-km BOReal Ecosystem-Atmosphere Study (BOREAS) region (Steyaert et al., 1997). Following the approach developed by Loveland et al. (1991) for 1-km AVHRR land cover mapping in the conterminous United States, monthly Normalized Difference Vegetation Index (NDVI) image composites (April-September 1992) of this subset in the BOREAS region were used in an unsupervised image cluster analysis algorithm to develop an initial set of seasonal land cover classes. Extensive ground data with Global Positioning System (GPS) georeferencing, observations from low-level aerial flights over remote areas, and selected Landsat image composites for the study areas were analyzed to split, aggregate, and label the spectral-temporal clusters throughout the BOREAS region. Landsat TM image composites (bands 5, 4, and 3) were available for the 100-km by 100-km Northern Study Area (NSA) and Southern Study Area (SSA). This AVHRR land cover product was compared with Landsat TM land cover classifications for the BOREAS study areas (Steyaert et al., 1997). Companion files include example thumbnail images that may be viewed and the image data files downloaded using a convenient viewer utility.
Satellite AVHRR Extracted Data (FIFE)
The Advanced Very High Resolution Radiometer (AVHRR) is a four- or five-channel scanning radiometer capable of providing global daytime and nighttime sea-surface temperature and information about ice, snow, and clouds. The sensor measures emitted and reflected radiation in five channels (bands) of the electromagnetic spectrum. The Site Average Reflectances Extracted from AVHRR-LAC Imagery Data Set consists of averages of pixel extracts from AVHRR-LAC (1 km resolution) scenes that overlay the FIFE site. Average radiances for dates are available for the five sensor wavebands and average reflectance and exoatmospheric reflectances are available for wavebands 1 and 2. Site averages are clustered in 1987 and during the summer of 1989. Some data are also available for early 1988. The AVHRR is capable of operating in both real-time or recorded modes. Direct readout data were transmitted to ground stations of the automatic picture transmission (APT) class at low-resolution (4x4 km) and to ground stations of the high-resolution picture transmission (HRPT) class at high resolution (1x1 km). Data recorded on board were available for processing in the NOAA Central Computer Facility. They included local area coverage (LAC) data which were from selected portions of each orbit with a 1x1 km resolution. The precision of satellite remote sensing estimates of surface reflectance (Hall et al., 1992), calibrated and corrected for atmospheric effects, was no worse than about 1 percent absolute.
SAFARI 2000 AVHRR-derived Land Surface Temperature Maps, Africa, 1995-2000
Land Surface Temperature (LST) is a key indicator of land surface states, and can provide information on surface-atmosphere heat and mass fluxes, vegetation water stress, and soil moisture. A daily, day and night, LST data set for continental Africa, including Madagascar, was derived from Advanced Very High Resolution Radiometer (AVHRR) Global Area Coverage (GAC; 4 km resolution) data for the 6-year lifetime of the NOAA-14 satellite (from 1995 to 2000) using a modified version of the Global Inventory Mapping and Monitoring System (GIMMS) (Tucker et al., 1994). The data were projected into Albers Equal Area and aggregated to 8 km spatial resolution. The data were cloud-filtered with CLAVR-1 algorithm (Stowe et al., 1999). The LST values were estimated with a split-window technique (Ulivieri et al., 1994) that takes advantage of differential absorption of the thermal infrared signal in bands 4 and 5. The emissivity of the surface was generated using a land cover classification map (Hansen et al., 2000) combined with the FAO soil map of Africa (FAO-UNESCO, 1977) and additional maps of tree, herbaceous, and bare soil percent cover (DeFries et al., 2000). Collateral products include cloud mask, time-of-scan, latitude and longitude, and land/water mask files.The data are in flat binary files. Each data file contains 1152 columns and 1152 rows, in signed integer format (2 bytes), with 8 km by 8 km spatial resolution. A unique map exists for each day and each night of the 6-year NOAA-14 lifetime. The data are best used to infer broad temporal and spatial trends rather than pixel-by-pixel values.
GHRSST Level 2P sub-skin Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on Metop satellites (currently Metop-A) (GDS V2) produced by OSI SAF
A global 1 km Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on multi-channel sea surface temperature (SST) retrievals generated in real-time from the Advanced Very High Resolution Radiometer (AVHRR) on the European Meteorological Operational-A (MetOp-A)satellite (launched 19 Oct 2006). The European Organization for the Exploitation of Meteorological Satellites (EUMETSAT),Ocean and Sea Ice Satellite Application Facility (OSI SAF) is producing SST products in near realtime from Metop/AVHRR. Global AVHRR level 1b data are acquired at Meteo-France/Centre deMeteorologie Spatiale (CMS) through the EUMETSAT/EUMETCAST system. SST is retrievedfrom the AVHRR infrared channels (3.7, 10.8 and 12.0 micrometer) using a multispectral algorithm.Atmospheric profiles of water vapor and temperature from a numerical weather prediction model,together with a radiatiave transfer model, are used to correct the multispectral algorithm forregional and seasonal biases due to changing atmospheric conditions. This product is delivered atfull resolution in satellite projection as metagranule corresponding to 3 minutes of acquisition. Theproduct format is compliant with the GHRSST Data Specification (GDS) version 2.
GHRSST NOAA/STAR Metop-B AVHRR FRAC ACSPO v2.80 1km L2P Dataset (GDS v2)
The MetOp First Generation (FG) is a European multi-satellite program jointly established by ESA and EUMETSAT, comprising three satellites, MetOp-A, -B and -C. The primary sensor onboard MetOp-FG, the Advanced Very High Resolution Radiometer/3 (AVHRR/3) contributed by NOAA, measures Earth emissions and reflectances in 5 out of 6 available bands (centered at 0.63, 0.83, 1.61, 3.7, 11 and 12 microns), in a swath of 2,600km from an 817km altitude. These data are collected in a Full Resolution Area Coverage (FRAC) mode, with pixel size of 1.1km at nadir. Metop-B launched on 17 September 2012 is the second in the MetOp-FG series. The NOAA Advanced Clear-Sky Processor for Ocean (ACSPO) Level 2 Preprocessed (L2P) SST product is derived at the full AVHRR FRAC resolution and reported in 10 minute granules in NetCDF4 format, compliant with the GHRSST Data Specification version 2 (GDS2). Subskin SSTs are derived using the regression Nonlinear SST (NLSST) algorithm, which employs three bands (3.7, 11 and 12 microns) at night and two bands (11 and 12 microns) during the day. The ACSPO AVHRR FRAC L2P product is monitored and validated against quality controlled in situ data, provided by the NOAA in situ SST Quality Monitor system (iQuam; Xu and Ignatov, 2014, https://doi.org/10.1175/JTECH-D-13-00121.1 ), in another NOAA system, SST Quality Monitor (SQUAM; Dash et al, 2010, https://doi.org/10.1175/2010JTECHO756.1 ). SST imagery and clear-sky masking are continuously evaluated, and checked for consistency with other sensors and platforms, in the ACSPO Regional Monitor for SST (ARMS) system. MetOp-A orbital characteristics and AVHRR/3 sensor performance are tracked in the NOAA 3S system (He et al., 2016, https://doi.org/10.3390/rs8040346 ).The L2P Near Real Time (NRT) SST files are archived at PO.DAAC with 3-6 hours latency, and then replaced by the Re-ANalysis (RAN) SST after about 2 months later with identical file names. Two features can be used to identify them: different file name time stamps and netCDF global attribute metadata source=NOAA-NCEP-GFS for NRT and source=MERRA-2 for RAN. A reduced size (0.45GB/day), equal-angle gridded (0.02-deg resolution) ACSPO L3U product is available at https://doi.org/10.5067/GHMTB-3US28
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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.