MSLSP V1 data was decommissioned on December 14, 2021. Users are encouraged to use the improved MSLSP V1.1 data product.

NASA’s Multi-Source Land Imaging (MuSLI) Land Surface Phenology (LSP) Yearly North America 30 meter (m) Version 1 product (MSLSP) provides a Land Surface Phenology product for North America derived from Harmonized Landsat Sentinel-2 (HLS) data. Data from the combined Landsat 8 Operational Land Imager (OLI) and Sentinel 2A and 2B Multispectral Instrument (MSI) provide the user community with dates of phenophase transitions, including the timing of greenup, maturity, senescence, and dormancy. MSLSP30NA is aligned with the Military Grid Reference System (MGRS) at 30 m spatial resolution. These datasets are useful for a wide range of applications, including ecosystem and agro-ecosystem modeling, monitoring the response of terrestrial ecosystems to climate variability and extreme events, crop-type discrimination, land cover, land use, and land cover change mapping.

Provided in the MSLSP product are variables for percent greenness, onset greenness dates, Enhanced Vegetative Index (EVI2) amplitude, maximum EVI2, and data quality information for up to two phenological cycles per year. For areas where the data values are missing due to cloud cover or other reasons, the data gaps are filled with good quality values from the year directly preceding or following the product year. A low-resolution browse image representing maximum EVI is also available for each MSLSP30NA granule.

Known Issues

• Data are sparse in 2016 and early 2017, as Sentinel-2B was not yet launched, and Sentinel-2A was not fully operational, leading to poorer quality retrievals of phenology in 2016 and 2017. However, poor quality pixels can be masked with Quality Assurance (QA) flags.
• Disturbance has not been explicitly accounted for or mapped, which can lead to premature detections of senescence and dormancy when sharp spectral changes occur.
• Pixels with more than two growth cycles per year (e.g., alfalfa fields) may not be accurately characterized, especially if they occur in rapid succession.