IMPACT’s HLS project takes input data from Landsat-8 and Sentinel-2 to generate a harmonized analysis ready data product that improves the temporal resolution of these sensors when used independently. Current publicly available land surface observation data requires the science user community to pick between high resolution data available every couple of weeks or coarser resolution data available every day. By harmonizing observations from platforms with similar instrument characteristics, IMPACT’s HLS project team is providing a unique opportunity for the science community to get higher resolution observations every 2-4 days. HLS data products should greatly improve upon current capabilities for applied science initiatives related to natural disasters, land cover land use change, and seasonal vegetation health.
TThe HLS algorithm is currently applied to 120+ test locations. The HLS project refactors and expands the algorithm from the test locations to global land coverage and generates data by processing new Landsat and Sentinel-2 data as it is retrieved from the satellite (i.e. forward mode).
A primary benefit of HLS data is the ability to use it to examine how the land surface changes at the plot scale (30-meter resolution) over time. To maximize the usefulness of HLS data for the land surface community, the complete historic archive of the data needs to be generated (back to 2013 for L30 data and to 2015 for S30 data). Processing historical data (i.e. backward processing) leverages the updated global algorithm to develop the full global archive of HLS from 2013 when Landsat 8 was launched.
The HLS v1.5 algorithm was recently refactored for cloud optimization and initial data output is currently being tested by the HLS science team at NASA GSFC.
Browse imagery created using v1.5 data has been created and formatted for ingestion into NASA’s Global Imagery Browse Service (GIBS) and Worldview applications.
"The Harmonized Landsat and Sentinel-2 surface reflectance data set" in Remote Sensing of Environment, vol. 219, Dec. 2018