Geospatial data

Inter-mission Time Series of Land Ice Velocity and Elevation (ITSLIVE)

The Inter-mission Time Series of Land Ice Velocity and Elevation (ITSLIVE) project has a singular mission: to accelerate ice sheet and glacier research by producing globally comprehensive, high resolution, low latency, temporally dense, multi-sensor records of land ice and ice shelf change while minimizing barriers between the data and the user. ITSLIVE data currently consists of NetCDF Level 2 scene-pair ice flow products posted to a standard 120 m grid derived from Landsat 4/5/7/8/9, Sentinel-2 optical scenes, and Sentinel-1 SAR scenes. We have processed all land-ice intersecting image pairs separated by ≤546 days for optical...

Listed for discovery. Access is provided by the original publisher under its terms.

Data coverage

The Inter-mission Time Series of Land Ice Velocity and Elevation (ITSLIVE) project has a singular mission: to accelerate ice sheet and glacier research by producing globally comprehensive, high resolution, low latency, temporally dense, multi-sensor records of land ice and ice shelf change while minimizing barriers between the data and the user. ITSLIVE data currently consists of NetCDF Level 2 scene-pair ice flow products posted to a standard 120 m grid derived from Landsat 4/5/7/8/9, Sentinel-2 optical scenes, and Sentinel-1 SAR scenes. We have processed all land-ice intersecting image pairs separated by ≤546 days for optical and ≤12 for SAR sensors, for all missions from each mission start to the end of 2022. The ITSLIVE project will continue processing new optical and radar scene pairs as they come in, and will soon increase production to include SAR image pairs separated by more than 12 days. We also expect to extend processing to include ASTER, RADARSAT, and NISAR imagery. Further, all scene pair data are combined into a set of Zarr datacubes that are cloud-optimized for time-series analysis, with a suite of user tools available to query the data effectively. The ITSLIVE project is also producing a suite of Level 3 products, including quarterly and annual ice-sheet and regional velocity mosaics as Cloud-Optimized GeoTIFFs, standardized records of elevation change rates for Greenland and Antarctica, and ice shelf and tidewater glacier front positions. For more information about the ITSLIVE project, please see .

Access & permitted use

Review the publisher’s documentation for availability, eligibility and permitted uses, including commercial analysis, model training and redistribution.

Creative Commons Zero (CC0) 1.0 Universal License

Need help sourcing data?

Tell us your required fields, population, geography and time period. We can review suitable sources and licensing options.

Request sourcing help

Related data sources

Climate and weatherPublic download

NOAA Global Daily Climate Observations

Daily precipitation, temperature, snowfall and other surface observations from the Global Historical Climatology Network across international stations.

NOAA National Centers for Environmental Information
Climate & weatherExternal source; review access terms

(EXPERIMENTAL) NOAA FourCastNet Global Forecast System (FourCastNetGFS) (EXPERIMENTAL)

The FourCastNet Global Forecast System (FourCastNetGFS) is an experimental system set up by the National Centers for Environmental Prediction (NCEP) to produce medium range global forecasts. The model runs on a 0.25 degree latitude-longitude grid (about 28 km) and 13 pressure levels. The model produces forecasts 4 times a day at 00Z, 06Z, 12Z and 18Z cycles. Major atmospheric and surface fields including temperature, wind components, geopotential height, relative humidity and 2 meter temperature and 10 meter winds are available. The products are 6 hourly forecasts up to 10 days. The data format is GRIB2. The FourCastNetGFS...

NOAA
Geospatial dataExternal source; review access terms

10m Annual Land Use Land Cover (9-class)

This dataset, produced by Impact Observatory, Microsoft, and Esri, displays a global map of land use and land cover (LULC) derived from ESA Sentinel-2 imagery at 10 meter resolution for the years 2017 - 2024. Each map is a composite of LULC predictions for 9 classes throughout the year in order to generate a representative snapshot of each year. This dataset was generated by Impact Observatory, which used billions of human-labeled pixels (curated by the National Geographic Society) to train a deep learning model for land classification. Each global map was produced by applying this model to the Sentinel-2 annual scene...

Impact Observatory