Published: July 27, 2023
The Harmonized Landsat Sentinel-2 (HLS) Project produces seamless, harmonized surface reflectance data from the Operational Land Imager (OLI) and Multi-Spectral Instrument (MSI) aboard Landsat and Sentinel-2 Earth-observing satellites, respectively. The aim is to produce seamless products with normalized parameters, which include atmospheric correction, cloud and cloud-shadow masking, geographic co-registration and common gridding, normalized bidirectional reflectance distribution function, and spectral band adjustment. HLS provides global observation of the Earth’s surface every 2-3 days with 30-meter spatial resolution.
The HLS Data Resources GitHub repository provides guides, short how-tos, and tutorials to help users access and work with HLS data. In the interest of open science, this repository has been made public and is open to contributions. The repository is actively maintained by the LP DAAC. All resources should be functional; however, changes or additions may be made. We encourage users to check the most updated resources in the repository.
Below are data use resources available for HLS data.
| Name | Type | Summary | Topics |
|---|---|---|---|
| HLS_Tutorial | Python Notebook | Tutorial demonstrating how to search for, access, and process HLS data | earthaccess |
| HLS SuPER Script | Python Script | Find, download, and subset HLS data from a command line executable | CMR API |
| HLS Bulk Download Bash Script | Bash Script | Find and download HLS data | CMR API |
| Name | Type | Summary | Topics |
|---|---|---|---|
| HLS R Tutorial | R Markdown | Tutorial demonstrating how to search for, access, and process HLS data in R | CMR STAC API |