N: 90 S: -90 E: 180 W: -180
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The HLSL30 V1.5 data product was decommissioned on January 4, 2022. Users are encouraged to use the improved HLSL30 V2 data product.
The Harmonized Landsat Sentinel-2 (HLS) project provides consistent surface reflectance (SR) and top of atmosphere (TOA) brightness data from the Operational Land Imager (OLI) aboard the joint NASA/USGS Landsat 8 satellite and the Multi-Spectral Instrument (MSI) aboard Europe’s Copernicus Sentinel-2A and Sentinel-2B satellites. The combined measurement enables global observations of the land every 1.6 days at 30-meter (m) spatial resolution. The HLS project uses a set of algorithms to obtain seamless products from OLI and MSI that include atmospheric correction, cloud and cloud-shadow masking, spatial co-registration and common gridding, illumination and view angle normalization, and spectral bandpass adjustment.
The HLSL30 product provides 30-m Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR) and is derived from Landsat 8 OLI data products. The HLSS30 and HLSL30 products are gridded to the same resolution and Military Grid Reference System (MGRS) tiling system and thus are “stackable” for time series analysis.
The HLSL30 product is provided in Cloud Optimized GeoTIFF (COG) format, and each band is distributed as a separate file. There are 10 bands included in the HLSL30 product along with one quality assessment (QA) band and four angle bands. For a more detailed description of the individual bands provided in the HLSL30 product, please see the User Guide.
The HLS project is funded by NASA’s Satellite Needs Working Group (SNWG) which provides data products developed to meet the needs of stakeholders from US government agencies.
Known Issues
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HLSL30.015 products are based on input Landsat 8 L1TP (precision terrain corrected) products, which require identification of ground control targets for precision geometric correction. Images where ground control is not available (e.g., very cloudy images) cannot be processed to L1TP and are not included in the HLSL30 dataset.
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Interruptions in data service occurred during a restaging of backlogged data between June 1 and June 15, 2021 for both HLSS30 and HLSL30 version 1.5 data products. During this time period increased errors in the processing workflow resulted in a significant number of data ingestion failures and thus, significant gaps in data availability. Given the pending release of the version 2.0, science quality HLS products, these missing data will not be filled for version 1.5. Users of the provisional version 1.5 products should be aware of the significant data gap in this two week window. The version 2.0 products will incorporate these data back into the archive. If you have any feedback or questions on the data please contact Customer Services or join our HLS conversion on the Earthdata Forum.
Version Description
Product Summary
Citation
Citation is critically important for dataset documentation and discovery. This dataset is openly shared, without restriction, in accordance with the EOSDIS Data Use and Citation Guidance.
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File Naming Convention
The file name begins with the Product Identifier (HLS.L30) followed by T plus the 5-character MGRS Tile Identifier (T55GEN), the Julian Date and Time of Production designated as YYYYDDDTHHMMSS (2025238T234638), the Version of the data collection (v2.0), the Variable/Band (B11), and the Data Format (tif).
Documents
USER'S GUIDE
ALGORITHM THEORETICAL BASIS DOCUMENT (ATBD)
Publications Citing This Dataset
| Title | Year Sort ascending | Author | Topic |
|---|---|---|---|
| Spatial-Temporal Dynamics of Vegetation Indices in Response to Drought | Crespo, Nazaret, Padua, Luis, Paredes, Paula, Rebollo, Francisco J., Moral, Francisco J., Santos, Joao A., Fraga, Helder | Reflectance | |
| Enhanced Polarimetric Radar Vegetation Index and Integration with | Chang, Jisung Geba, Kraatz, Simon, Anderson, Martha, Gao, Feng | Reflectance | |
| Estimating Brazilian Amazon Canopy Height Using Landsat Reflectance Products in a Random Forest Model with Lidar as Reference Data | Oliveira, Pedro V. C., Zhang, Hankui K., Zhang, Xiaoyang | Reflectance | |
| Modeling wildland fire burn severity in California using a spatial Super Learner approach | Simafranca, Nicholas, Willoughby, Bryant, ONeil, Erin, Farr, Sophie, Reich, Brian J., Giertych, Naomi, Johnson, Margaret C., Pascolini-Campbell, Madeleine A. | RADAR IMAGERY, Terrain Elevation, Topographical Relief Maps, Digital Elevation/Terrain Model (DEM), Reflectance, Land Use/Land Cover Classification, Evapotranspiration, Land Surface Temperature, Emissivity, Potential Evapotranspiration, Plant Characteristics | |
| Novel Use of Image Time Series to Distinguish Dryland Vegetation Responses to Wet and Dry Years | Myers, Emily R., Browning, Dawn M., Burkett, Laura M., James, Darren K., Bestelmeyer, Brandon T. | Reflectance | |
| Phenology and Plant Functional Type Link Optical Properties of Vegetation Canopies to Patterns of Vertical Vegetation Complexity | Jurayj, Duncan, Bowers, Rebecca, Fayne, Jessica V. | Aquatic Ecosystems, Terrestrial Ecosystems, Vegetation, Soils, Maximum/Minimum Temperature, 24 Hour Precipitation Amount, Snow Water Equivalent, Shortwave Radiation, Vapor Pressure, Reflectance, Terrain Elevation, Glacier Elevation/Ice Sheet Elevation, Sea Ice Elevation, Vegetation Height, Land Use/Land Cover Classification, Forests, Vegetation Cover, Alpine/Tundra, Dominant Species, Plant Phenology, Land Use/Land Cover, Enhanced Vegetation Index (EVI), Sensor Counts | |
| Relationships between Woodland Phenology, Precipitation, and Flooding Patterns in the Brazilian Pantanal Wetland | Ribeiro, Uelison Mateus, Corgne, Samuel, Bacani, Vitor Matheus, Da Silva, Mauro Henrique Soares, Arvor, Damien | Reflectance | |
| Impacts of terrain on land surface phenology derived from Harmonized Landsat 8 and Sentinel-2 in the Tianshan Mountains, China | Ding, Chao, Li, Yao, Xie, Qiaoyun, Li, Hao, Zhang, Bingwei | Plant Phenology, Enhanced Vegetation Index (EVI), Terrain Elevation, RADAR IMAGERY, Topographical Relief Maps, Reflectance | |
| Impact of high-cadence Earth observation in maize crop phenology classification | Nieto, Luciana, Houborg, Rasmus, Zajdband, Ariel, Jumpasut, Arin, Prasad, P. V. Vara, Olson, Brad J. S. C., Ciampitti, Ignacio A. | Reflectance | |
| Classification of wetland vegetation based on NDVI time series from the HLS dataset | Ju, Yang, Bohrer, Gil | Reflectance | |
| Multi-season phenology mapping of Nile Delta croplands using time series of Sentinel-2 and Landsat 8 Green LAI | Amin, Eatidal, Belda, Santiago, Pipia, Luca, Szantoi, Zoltan, El Baroudy, Ahmed, Moreno, Jose, Verrelst, Jochem | Reflectance | |
| Monitoring standing herbaceous biomass and thresholds in semiarid rangelands from harmonized Landsat 8 and Sentinel-2 imagery to support within-season adaptive management | Kearney, Sean P., Porensky, Lauren M., Augustine, David J., Gaffney, Rowan, Derner, Justin D. | Reflectance | |
| Near-real-time monitoring of land disturbance with harmonized Landsats 78 and Sentinel-2 data | Shang, Rong, Zhu, Zhe, Zhang, Junxue, Qiu, Shi, Yang, Zhiqiang, Li, Tian, Yang, Xiucheng | Reflectance | |
| Aerosol models from the AERONET databaseApplication to surface reflectance validation | Roger, Jean-Claude, Vermote, Eric, Skakun, Sergii, Murphy, Emilie, Dubovik, Oleg, Kalecinski, Natacha, Korgo, Bruno, Holben, Brent | Reflectance | |
| Can we detect more ephemeral floods with higher density harmonized Landsat Sentinel 2 data compared to Landsat 8 alone? | Tulbure, Mirela G., Broich, Mark, Perin, Vinicius, Gaines, Mollie, Ju, Junchang, Stehman, Stephen V., Pavelsky, Tamlin, Masek, Jeffrey G., Yin, Simon, Mai, Joachim, Betbeder-Matibet, Luc | Reflectance | |
| Resolve the ClearSky Continuous Diurnal Cycle of HighResolution ECOSTRESS Evapotranspiration and Land Surface Temperature | Wen, Jiaming, Fisher, Joshua B., Parazoo, Nicholas C., Hu, Leiqiu, Litvak, Marcy E., Sun, Ying | Reflectance, Atmospheric Radiation, Longwave Radiation, Shortwave Radiation, Radiative Flux, Radiative Forcing, Surface Radiative Properties, Albedo, Emissivity, Cloud Properties, Cloud Fraction, Cloud Optical Depth/Thickness, Skin Temperature, Skin Temperature, Sea Surface Skin Temperature, Geopotential Height, Altitude, Surface Temperature, Upper Air Temperature, Dew Point Temperature, Air Temperature, Cloud Top Temperature, Atmospheric Winds, Surface Winds, U/V Wind Components, Upper Level Winds, U/V Wind Components, Vertical Wind Velocity/Speed, Atmospheric Pressure, Sea Level Pressure, Cloud Top Pressure, Sea Level Pressure, Surface Pressure, Specific Humidity, Total Precipitable Water, Cloud Liquid Water/Ice, Atmospheric Water Vapor, Atmospheric Ozone, Oxygen Compounds, Boundary Layer Winds, Total Ozone, Evapotranspiration, Latent Heat Flux, Ecosystem Functions, Precipitation Amount, Maximum/Minimum Temperature, Terrestrial Ecosystems, Land Use/Land Cover Classification, Trace Gases/Trace Species, Soil Gas/Air | |
| Multiscale assessment of land surface phenology from harmonized Landsat 8 and Sentinel-2, PlanetScope, and PhenoCam imagery | Moon, Minkyu, Richardson, Andrew D., Friedl, Mark A. | Plant Phenology, Land Use/Land Cover, Enhanced Vegetation Index (EVI), Reflectance, Land Use/Land Cover Classification, Plant Characteristics, Vegetation Cover, Vegetation Index | |
| Investigation of land surface phenology detections in shrublands using multiple scale satellite data | Peng, Dailiang, Wang, Yan, Xian, George, Huete, Alfredo R., Huang, Wenjiang, Shen, Miaogen, Wang, Fumin, Yu, Le, Liu, Liangyun, Xie, Qiaoyun, Liu, Lingling, Zhang, Xiaoyang | Reflectance, Anisotropy, Albedo, Plant Phenology, Enhanced Vegetation Index (EVI) | |
| Mapping daily evapotranspiration at field scale using the Harmonized Landsat and Sentinel-2 dataset, with sharpened VIIRS as a Sentinel-2 thermal proxy | Xue, Jie, Anderson, Martha C., Gao, Feng, Hain, Christopher, Yang, Yun, Knipper, Kyle R., Kustas, William P., Yang, Yang | Evapotranspiration, Land Surface Temperature, Emissivity, Reflectance, Albedo, Anisotropy, Leaf Characteristics, Photosynthetically Active Radiation, Leaf Area Index (LAI), Fraction Of Absorbed Photosynthetically Active Radiation (fapar), Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) | |
| Fusing geostationary satellite observations with harmonized Landsat-8 and sentinel-2 time series for monitoring field-scale land surface phenology | Shen, Yu, Zhang, Xiaoyang, Wang, Weile, Nemani, Ramakrishna, Ye, Yongchang, Wang, Jianmin | Reflectance | |
| Augmenting Landsat time series with Harmonized Landsat Sentinel-2 data productsAssessment of spectral correspondence | Wulder, Michael A., Hermosilla, Txomin, White, Joanne C., Hobart, Geordie, Masek, Jeffrey G. | Reflectance | |
| Assessing within-field corn and soybean yield variability from worldview-3, planet, sentinel-2, and landsat 8 satellite imagery | Skakun, Sergii, Kalecinski, Natacha I., Brown, Meredith G. L., Johnson, David M., Vermote, Eric F., Roger, Jean-Claude, Franch, Belen | Reflectance | |
| Land surface phenology as indicator of global terrestrial ecosystem dynamics: A systematic review | Caparros-Santiago, Jose A., Rodriguez-Galiano, Victor, Dash, Jadunandan | Reflectance, Anisotropy, Albedo, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Plant Phenology | |
| Land cover composition, climate, and topography drive land surface phenology in a recently burned landscape: An application of machine learning in phenological ... | Wang, Jianmin, Zhang, Xiaoyang, Rodman, Kyle | Reflectance, Anisotropy, RADAR IMAGERY, Terrain Elevation, Topographical Relief Maps, Digital Elevation/Terrain Model (DEM), Albedo | |
| Reconstructing daily 30 m NDVI over complex agricultural landscapes using a crop reference curve approach | Sun, Liang, Gao, Feng, Xie, Donghui, Anderson, Martha, Chen, Ruiqing, Yang, Yun, Yang, Yang, Chen, Zhongxin | Reflectance, Anisotropy |