Description:

The NASA Making Earth System Data Records for Use in Research Environments ([MEaSUREs](https://earthdata.nasa.gov/about/competitive-programs/measures)) Global Web-Enabled Landsat Data Annual (GWELDYR) Version 3.2 data product provides Landsat data at 30 meter (m) resolution for terrestrial non-Antarctica locations over annual reporting periods for the 2005 epoch. GWELD products are generated from all available Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data in the U.S. Geological Survey (USGS) Landsat archive. The GWELD suite of products provides a consistent data source to derive land cover as well as geophysical and biophysical information for regional assessment of land surface dynamics. The GWELD products include Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR) for the reflective wavelength bands and top of atmosphere (TOA) brightness temperature for the thermal bands. The products are defined in the Sinusoidal coordinate system to promote continuity of NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) land tile grid. Provided in the GWELDYR product are layers for surface reflectance bands 1-5 and 7, TOA brightness temperature for thermal bands, Normalized Difference Vegetation Index (NDVI), day of year, ancillary angle, and data quality information. A low-resolution red, green, blue (RGB) browse image of bands 5, 4, 3 is also available for each granule. Known Issues * GWELDYR Version 3.2 known issues can be found in Section 4 of the Algorithm Theoretical Basis Document (ATBD). * Within the CFMask_State layer, the valid range is listed in the granule metadata as 0 to 65534 which includes the fill value. To avoid inclusion of the fill value, the valid range should be considered 1 to 65534 as reflected in the Data Layers Characteristics table above. * Within the CFMask_State layer, the bit flag descriptions include a description for bit 0 that contradicts the listed fill value. In the description, bit 0 is stated as 1 when fill value is present, which prevents the use of 0 as the fill value. To avoid errors when using the CFMask_State layer, bit 0 should be ignored as an indicator of fill value.

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• Data link
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• Metadata link
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Temporal Extent:

Start: 2004-01-01T00:00:00.000Z

End: 2006-12-31T23:59:59.999Z

Spatial Extent:

Minimum Bounding Rectangle: -90 -180 90 180

LPCLOUD Short Name: GWELDYR Version ID: 032 Unique ID: C2763268463-LPCLOUD

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Description:

The NASA Making Earth System Data Records for Use in Research Environments ([MEaSUREs](https://earthdata.nasa.gov/about/competitive-programs/measures)) Global Web-Enabled Landsat Data Annual (GWELDYR) Version 3 data product provides Landsat data at 30 meter (m) resolution for terrestrial non-Antarctica locations over annual reporting periods for the 2010 epoch. GWELD data products are generated from all available Landsat 4 and 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data in the U.S. Geological Survey (USGS) Landsat archive. The GWELD suite of products provide consistent data to derive land cover as well as geophysical and biophysical information for regional assessment of land surface dynamics. The GWELD products include Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR) for the reflective wavelength bands and to top of atmosphere (TOA) brightness temperature for the thermal bands. The products are defined in the Sinusoidal coordinate system to promote continuity of NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) land tile grid Provided in the GWELDYR product are layers for surface reflectance bands 1 through 5 and 7, TOA brightness temperature for thermal bands, Normalized Difference Vegetation Index (NDVI), day of year, ancillary angle, and data quality information. A low-resolution red, green, blue (RGB) browse image of bands 5, 4, 3 is also available for each granule. Known Issues * GWELDYR known issues can be found in Section 4 of the Algorithm Theoretical Basis Document (ATBD). Please note that the version 3.0 GWELD products for 2009, 2010 and 2011 are defined in HDF4 which cannot be read correctly by GDAL/ArcGIS. This is not an issue for the version 3.1 GWELD products

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• Metadata link
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Temporal Extent:

Start: 2009-01-01T00:00:00.000Z

End: 2011-12-31T23:59:59.999Z

Spatial Extent:

Minimum Bounding Rectangle: -90 -180 90 180

LPCLOUD Short Name: GWELDYR Version ID: 003 Unique ID: C2763266356-LPCLOUD

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Description:

This dataset contains the Lakes Essential Climate Variable, which is comprised of processed satellite observations at the global scale, over the period 1992-2022, for over 2000 inland water bodies. This dataset was produced by the European Space Agency (ESA) Lakes Climate Change Initiative (Lakes_cci) project. For more information about the Lakes_cci please visit the project website. This is version 2.1.0 of the dataset.The six thematic climate variables included in this dataset are:• Lake Water Level (LWL), derived from satellite altimetry, is fundamental to understand the balance between water inputs and water loss and their connection with regional and global climate change.• Lake Water Extent (LWE), modelled from the relation between LWL and high-resolution spatial extent observed at set time-points, describes the areal extent of the water body. This allows the observation of drought in arid environments, expansion in high Asia, or impact of large-scale atmospheric oscillations on lakes in tropical regions for example. .• Lake Surface Water temperature (LSWT), derived from optical and thermal satellite observations, is correlated with regional air temperatures and is informative about vertical mixing regimes, driving biogeochemical cycling and seasonality.• Lake Ice Cover (LIC), determined from optical observations, describes the freeze-up in autumn and break-up of ice in spring, which are proxies for gradually changing climate patterns and seasonality.• Lake Water-Leaving Reflectance (LWLR), derived from optical satellite observations, is a direct indicator of biogeochemical processes and habitats in the visible part of the water column (e.g. seasonal phytoplankton biomass fluctuations), and an indicator of the frequency of extreme events (peak terrestrial run-off, changing mixing conditions).• Lake Ice Thickness (LIT), containing LIT information over Great Slave lake from 2002-2022.Data generated in the Lakes_cci are derived from multiple satellite sensors including: TOPEX/Poseidon, Jason, ENVISAT, SARAL, Sentinel 2-3, Landsat 4, 5, 7 and 8, ERS-1, ERS-2, Terra/Aqua and Metop-A/B.Satellite sensors associated with the thematic climate variables are as follows:LWL: TOPEX/Poseidon, Jason-1, Jason-2, Jason-3, Sentinel-6A, Envisat RA/RA-2, SARAL AltiKa, GFO, Sentinel-3A SRAL, Sentinel-3B SRAL, ERS-1 RA, ERS-2; LWE: Landsat 4 TM, 5 TM, 7 ETM+, 8 OLI, Sentinel-1 C-band SAR, Sentinel-2 MSI, Sentinel-3A SRAL, Sentinel-3B SRAL, ERS-1 AMI, ERS-2 AMI;LSWT: Envisat AATSR, Terra/Aqua MODIS, Sentinel-3A ATTSR-2, Sentinel-3B, ERS-2 AVHRR, Metop-A/B; LIC: Terra/Aqua MODIS; LWLR: Envisat MERIS, Sentinel-3A OLCI A/B, Aqua MODIS;LIT: Jason1, Jason2, Jason3, POSEIDON-2, POSEIDON-3 and POSEIDON-3B.Detailed information about the generation and validation of this dataset is available from the Lakes_cci documentation available on the project website and in Carrea, L., Crétaux, JF., Liu, X. et al. Satellite-derived multivariate world-wide lake physical variable timeseries for climate studies. Sci Data 10, 30 (2023). https://doi.org/10.1038/s41597-022-01889-z

Links:

• Data link
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• 7fc9df8070d34cacab8092e45ef276f1

Temporal Extent:

Start: 1992-09-26T00:00:00.000Z

End: 2022-12-31T23:59:59.000Z

Spatial Extent:

Minimum Bounding Rectangle: -90 -180 90 180

FEDEO Short Name: 7fc9df8070d34cacab8092e45ef276f1 Version ID: NA Unique ID: C3327360101-FEDEO

Description:

A time series of ice velocity values have been derived by analysis of LandSat-7 ETM+ images for the Lambert Glacier and Amery Ice Shelf system. The analysis technique uses feature tracking in pairs of Landsat-7 ETM+ images. This process uses surface features that persist with time and move with the ice as tracers of the ice motion. The displacement of these features over the time interval between acquisition of the two images in a pair is determined by image correlation. The analysis is made at regular increments across and along the images, to produce a regular grid of values. The derived values are filtered and validated according to set of a prior constraints for the flow in a local region and the statistics of a set of velocity values within a window. The images have been projected onto a common reference system, and spliced together in order to produce a seamless set of velocity values. Horizontal components of strain rate are derived from the velocity data using a set of derivative operators in a least-squares solution of an over-constrained set of equations, which uses all velocity values within a computation window. This procedure effectively produces a set of average velocity and strain rate values and accounts for much of the noise in the individual velocity observations. Values of the local longitudinal, transverse and shear strain rate components are derived by rotation of the cartesian values to the local flow direction. The procedure is described in Young and Hyland (2002). This metadata record has been derived from work performed under the auspices of ASAC project 3067 (ASAC_3067).

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• Metadata link
• AAD_Ant_AIS_vel_series

Temporal Extent:

Start: 1999-01-01T00:00:00.000Z

End: 2006-12-31T23:59:59.999Z

Spatial Extent:

Minimum Bounding Rectangle: -75 62 -73 70

AU_AADC Short Name: AAD_Ant_AIS_vel_series Version ID: 1 Unique ID: C1214305516-AU_AADC

Description:

This dataset provides annual aboveground biomass (AGB) maps and associated uncertainty maps for Alaska and Canada from 1984 to 2022 at ~30 m resolution (0.00027 degrees). The dataset was derived using predictors from synthetic spectral features from Landsat Collection 2 and Continuous Change Detection and Classification algorithm. Extensive collections of ground plots (n = 45,002) and airborne lidar data (n = 421,942) were compiled for reference AGB in order to calibrate AGB models using Extreme Gradient Boosting (XGBoost) per ecoregion. Fifty AGB predictions were derived, of which the mean and standard deviation was used as per-pixel AGB prediction and uncertainty, respectively. The dataset can promote better understanding of carbon dynamics across arctic and boreal regions of North America. The data are provided in cloud optimized GeoTIFF format.

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• Metadata link
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Temporal Extent:

Start: 1984-01-01T00:00:00.000Z

End: 2022-12-31T23:59:59.999Z

Spatial Extent:

Minimum Bounding Rectangle: 41.9212 -171.845 82.3001 -52.6617

ORNL_CLOUD Short Name: ABoVE_AGBD_Uncertainty_Maps_2465 Version ID: 1 Unique ID: C3895347745-ORNL_CLOUD

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