GEOG researchers, J.-C. Roger, S. Skakun, B. Franch and C. Justice, in collaboration with NASA Goddard Space Flight Center, J. Masek, Adjunct Associate Professor, E. Vermote, Adjunct Professor, and Junchang Ju, contributed to the NASA's Harmonized Landsat/Sentinel-2 (HLS) product. A new HLS version 1.4 was publicly released in November 2017.

HLS is a NASA initiative to produce a Virtual Constellation (VC) of surface reflectance (SR) data from the Operational Land Imager (OLI) and MultiSpectral Instrument (MSI) onboard the Landsat 8 and Sentinel-2 remote sensing satellites, respectively. The combined measurement enables global observations of the land every 2-3 days at moderate (<30 m) spatial resolution. The HLS project uses a set of algorithms to obtain seamless products from OLI and MSI: atmospheric correction, cloud and cloud-shadow masking, spatial co-registration and common gridding, illumination and view angle normalization and spectral bandpass adjustment. The HLS data products can be regarded as the building blocks for a “data cube” such that a user may examine any given pixel through time, and treat the near-daily reflectance time series as though it came from a single sensor.

Landsat 8 (left) and Sentinel-2 (right) images over the Washington DC/Baltimore area and part of the Chesapeake Bay. Washington DC is located in the bottom left part of the images, while Baltimore is located in the center of the images.

Details on the HLS generation were published in the top remote sensing journal Remote Sensing of Environment:

Claverie, M., Ju, J., Masek, J. G., Dungan, J. L., Vermote, E. F., Roger, J.-C., Skakun, S. V., & Justice, C. (2018). The Harmonized Landsat and Sentinel-2 surface reflectance data set. Remote Sensing of Environment, 219, 145-161. (

More information on HLS can be found on the web site, which also includes a link for downloading data, a program tool for automated/bulk downloads, and a comprehensive user guide.